introduction of research about covid 19

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• Open access
• Published: 04 June 2021

Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews

• Israel Júnior Borges do Nascimento 1 , 2 ,
• Dónal P. O’Mathúna 3 , 4 ,
• Thilo Caspar von Groote 5 ,
• Hebatullah Mohamed Abdulazeem 6 ,
• Ishanka Weerasekara 7 , 8 ,
• Ana Marusic 9 ,
• Livia Puljak   ORCID: orcid.org/0000-0002-8467-6061 10 ,
• Vinicius Tassoni Civile 11 ,
• Irena Zakarija-Grkovic 9 ,
• Tina Poklepovic Pericic 9 ,
• Alvaro Nagib Atallah 11 ,
• Santino Filoso 12 ,
• Nicola Luigi Bragazzi 13 &
• Milena Soriano Marcolino 1

On behalf of the International Network of Coronavirus Disease 2019 (InterNetCOVID-19)

BMC Infectious Diseases volume  21 , Article number:  525 ( 2021 ) Cite this article

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Navigating the rapidly growing body of scientific literature on the SARS-CoV-2 pandemic is challenging, and ongoing critical appraisal of this output is essential. We aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic.

Nine databases (Medline, EMBASE, Cochrane Library, CINAHL, Web of Sciences, PDQ-Evidence, WHO’s Global Research, LILACS, and Epistemonikos) were searched from December 1, 2019, to March 24, 2020. Systematic reviews analyzing primary studies of COVID-19 were included. Two authors independently undertook screening, selection, extraction (data on clinical symptoms, prevalence, pharmacological and non-pharmacological interventions, diagnostic test assessment, laboratory, and radiological findings), and quality assessment (AMSTAR 2). A meta-analysis was performed of the prevalence of clinical outcomes.

Eighteen systematic reviews were included; one was empty (did not identify any relevant study). Using AMSTAR 2, confidence in the results of all 18 reviews was rated as “critically low”. Identified symptoms of COVID-19 were (range values of point estimates): fever (82–95%), cough with or without sputum (58–72%), dyspnea (26–59%), myalgia or muscle fatigue (29–51%), sore throat (10–13%), headache (8–12%) and gastrointestinal complaints (5–9%). Severe symptoms were more common in men. Elevated C-reactive protein and lactate dehydrogenase, and slightly elevated aspartate and alanine aminotransferase, were commonly described. Thrombocytopenia and elevated levels of procalcitonin and cardiac troponin I were associated with severe disease. A frequent finding on chest imaging was uni- or bilateral multilobar ground-glass opacity. A single review investigated the impact of medication (chloroquine) but found no verifiable clinical data. All-cause mortality ranged from 0.3 to 13.9%.

Conclusions

In this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all reviews was “critically low”. Thus, systematic reviews that were published early on in the pandemic were of questionable usefulness. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards.

Peer Review reports

The spread of the “Severe Acute Respiratory Coronavirus 2” (SARS-CoV-2), the causal agent of COVID-19, was characterized as a pandemic by the World Health Organization (WHO) in March 2020 and has triggered an international public health emergency [ 1 ]. The numbers of confirmed cases and deaths due to COVID-19 are rapidly escalating, counting in millions [ 2 ], causing massive economic strain, and escalating healthcare and public health expenses [ 3 , 4 ].

The research community has responded by publishing an impressive number of scientific reports related to COVID-19. The world was alerted to the new disease at the beginning of 2020 [ 1 ], and by mid-March 2020, more than 2000 articles had been published on COVID-19 in scholarly journals, with 25% of them containing original data [ 5 ]. The living map of COVID-19 evidence, curated by the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre), contained more than 40,000 records by February 2021 [ 6 ]. More than 100,000 records on PubMed were labeled as “SARS-CoV-2 literature, sequence, and clinical content” by February 2021 [ 7 ].

Due to publication speed, the research community has voiced concerns regarding the quality and reproducibility of evidence produced during the COVID-19 pandemic, warning of the potential damaging approach of “publish first, retract later” [ 8 ]. It appears that these concerns are not unfounded, as it has been reported that COVID-19 articles were overrepresented in the pool of retracted articles in 2020 [ 9 ]. These concerns about inadequate evidence are of major importance because they can lead to poor clinical practice and inappropriate policies [ 10 ].

Systematic reviews are a cornerstone of today’s evidence-informed decision-making. By synthesizing all relevant evidence regarding a particular topic, systematic reviews reflect the current scientific knowledge. Systematic reviews are considered to be at the highest level in the hierarchy of evidence and should be used to make informed decisions. However, with high numbers of systematic reviews of different scope and methodological quality being published, overviews of multiple systematic reviews that assess their methodological quality are essential [ 11 , 12 , 13 ]. An overview of systematic reviews helps identify and organize the literature and highlights areas of priority in decision-making.

In this overview of systematic reviews, we aimed to summarize and critically appraise systematic reviews of coronavirus disease (COVID-19) in humans that were available at the beginning of the pandemic.

Methodology

Research question.

This overview’s primary objective was to summarize and critically appraise systematic reviews that assessed any type of primary clinical data from patients infected with SARS-CoV-2. Our research question was purposefully broad because we wanted to analyze as many systematic reviews as possible that were available early following the COVID-19 outbreak.

Study design

We conducted an overview of systematic reviews. The idea for this overview originated in a protocol for a systematic review submitted to PROSPERO (CRD42020170623), which indicated a plan to conduct an overview.

Overviews of systematic reviews use explicit and systematic methods for searching and identifying multiple systematic reviews addressing related research questions in the same field to extract and analyze evidence across important outcomes. Overviews of systematic reviews are in principle similar to systematic reviews of interventions, but the unit of analysis is a systematic review [ 14 , 15 , 16 ].

We used the overview methodology instead of other evidence synthesis methods to allow us to collate and appraise multiple systematic reviews on this topic, and to extract and analyze their results across relevant topics [ 17 ]. The overview and meta-analysis of systematic reviews allowed us to investigate the methodological quality of included studies, summarize results, and identify specific areas of available or limited evidence, thereby strengthening the current understanding of this novel disease and guiding future research [ 13 ].

A reporting guideline for overviews of reviews is currently under development, i.e., Preferred Reporting Items for Overviews of Reviews (PRIOR) [ 18 ]. As the PRIOR checklist is still not published, this study was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 statement [ 19 ]. The methodology used in this review was adapted from the Cochrane Handbook for Systematic Reviews of Interventions and also followed established methodological considerations for analyzing existing systematic reviews [ 14 ].

Approval of a research ethics committee was not necessary as the study analyzed only publicly available articles.

Eligibility criteria

Systematic reviews were included if they analyzed primary data from patients infected with SARS-CoV-2 as confirmed by RT-PCR or another pre-specified diagnostic technique. Eligible reviews covered all topics related to COVID-19 including, but not limited to, those that reported clinical symptoms, diagnostic methods, therapeutic interventions, laboratory findings, or radiological results. Both full manuscripts and abbreviated versions, such as letters, were eligible.

No restrictions were imposed on the design of the primary studies included within the systematic reviews, the last search date, whether the review included meta-analyses or language. Reviews related to SARS-CoV-2 and other coronaviruses were eligible, but from those reviews, we analyzed only data related to SARS-CoV-2.

No consensus definition exists for a systematic review [ 20 ], and debates continue about the defining characteristics of a systematic review [ 21 ]. Cochrane’s guidance for overviews of reviews recommends setting pre-established criteria for making decisions around inclusion [ 14 ]. That is supported by a recent scoping review about guidance for overviews of systematic reviews [ 22 ].

Thus, for this study, we defined a systematic review as a research report which searched for primary research studies on a specific topic using an explicit search strategy, had a detailed description of the methods with explicit inclusion criteria provided, and provided a summary of the included studies either in narrative or quantitative format (such as a meta-analysis). Cochrane and non-Cochrane systematic reviews were considered eligible for inclusion, with or without meta-analysis, and regardless of the study design, language restriction and methodology of the included primary studies. To be eligible for inclusion, reviews had to be clearly analyzing data related to SARS-CoV-2 (associated or not with other viruses). We excluded narrative reviews without those characteristics as these are less likely to be replicable and are more prone to bias.

Scoping reviews and rapid reviews were eligible for inclusion in this overview if they met our pre-defined inclusion criteria noted above. We included reviews that addressed SARS-CoV-2 and other coronaviruses if they reported separate data regarding SARS-CoV-2.

Information sources

Nine databases were searched for eligible records published between December 1, 2019, and March 24, 2020: Cochrane Database of Systematic Reviews via Cochrane Library, PubMed, EMBASE, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Sciences, LILACS (Latin American and Caribbean Health Sciences Literature), PDQ-Evidence, WHO’s Global Research on Coronavirus Disease (COVID-19), and Epistemonikos.

The comprehensive search strategy for each database is provided in Additional file 1 and was designed and conducted in collaboration with an information specialist. All retrieved records were primarily processed in EndNote, where duplicates were removed, and records were then imported into the Covidence platform [ 23 ]. In addition to database searches, we screened reference lists of reviews included after screening records retrieved via databases.

Study selection

All searches, screening of titles and abstracts, and record selection, were performed independently by two investigators using the Covidence platform [ 23 ]. Articles deemed potentially eligible were retrieved for full-text screening carried out independently by two investigators. Discrepancies at all stages were resolved by consensus. During the screening, records published in languages other than English were translated by a native/fluent speaker.

Data collection process

We custom designed a data extraction table for this study, which was piloted by two authors independently. Data extraction was performed independently by two authors. Conflicts were resolved by consensus or by consulting a third researcher.

We extracted the following data: article identification data (authors’ name and journal of publication), search period, number of databases searched, population or settings considered, main results and outcomes observed, and number of participants. From Web of Science (Clarivate Analytics, Philadelphia, PA, USA), we extracted journal rank (quartile) and Journal Impact Factor (JIF).

We categorized the following as primary outcomes: all-cause mortality, need for and length of mechanical ventilation, length of hospitalization (in days), admission to intensive care unit (yes/no), and length of stay in the intensive care unit.

The following outcomes were categorized as exploratory: diagnostic methods used for detection of the virus, male to female ratio, clinical symptoms, pharmacological and non-pharmacological interventions, laboratory findings (full blood count, liver enzymes, C-reactive protein, d-dimer, albumin, lipid profile, serum electrolytes, blood vitamin levels, glucose levels, and any other important biomarkers), and radiological findings (using radiography, computed tomography, magnetic resonance imaging or ultrasound).

We also collected data on reporting guidelines and requirements for the publication of systematic reviews and meta-analyses from journal websites where included reviews were published.

Quality assessment in individual reviews

Two researchers independently assessed the reviews’ quality using the “A MeaSurement Tool to Assess Systematic Reviews 2 (AMSTAR 2)”. We acknowledge that the AMSTAR 2 was created as “a critical appraisal tool for systematic reviews that include randomized or non-randomized studies of healthcare interventions, or both” [ 24 ]. However, since AMSTAR 2 was designed for systematic reviews of intervention trials, and we included additional types of systematic reviews, we adjusted some AMSTAR 2 ratings and reported these in Additional file 2 .

Adherence to each item was rated as follows: yes, partial yes, no, or not applicable (such as when a meta-analysis was not conducted). The overall confidence in the results of the review is rated as “critically low”, “low”, “moderate” or “high”, according to the AMSTAR 2 guidance based on seven critical domains, which are items 2, 4, 7, 9, 11, 13, 15 as defined by AMSTAR 2 authors [ 24 ]. We reported our adherence ratings for transparency of our decision with accompanying explanations, for each item, in each included review.

One of the included systematic reviews was conducted by some members of this author team [ 25 ]. This review was initially assessed independently by two authors who were not co-authors of that review to prevent the risk of bias in assessing this study.

Synthesis of results

For data synthesis, we prepared a table summarizing each systematic review. Graphs illustrating the mortality rate and clinical symptoms were created. We then prepared a narrative summary of the methods, findings, study strengths, and limitations.

For analysis of the prevalence of clinical outcomes, we extracted data on the number of events and the total number of patients to perform proportional meta-analysis using RStudio© software, with the “meta” package (version 4.9–6), using the “metaprop” function for reviews that did not perform a meta-analysis, excluding case studies because of the absence of variance. For reviews that did not perform a meta-analysis, we presented pooled results of proportions with their respective confidence intervals (95%) by the inverse variance method with a random-effects model, using the DerSimonian-Laird estimator for τ 2 . We adjusted data using Freeman-Tukey double arcosen transformation. Confidence intervals were calculated using the Clopper-Pearson method for individual studies. We created forest plots using the RStudio© software, with the “metafor” package (version 2.1–0) and “forest” function.

Managing overlapping systematic reviews

Some of the included systematic reviews that address the same or similar research questions may include the same primary studies in overviews. Including such overlapping reviews may introduce bias when outcome data from the same primary study are included in the analyses of an overview multiple times. Thus, in summaries of evidence, multiple-counting of the same outcome data will give data from some primary studies too much influence [ 14 ]. In this overview, we did not exclude overlapping systematic reviews because, according to Cochrane’s guidance, it may be appropriate to include all relevant reviews’ results if the purpose of the overview is to present and describe the current body of evidence on a topic [ 14 ]. To avoid any bias in summary estimates associated with overlapping reviews, we generated forest plots showing data from individual systematic reviews, but the results were not pooled because some primary studies were included in multiple reviews.

Our search retrieved 1063 publications, of which 175 were duplicates. Most publications were excluded after the title and abstract analysis ( n = 860). Among the 28 studies selected for full-text screening, 10 were excluded for the reasons described in Additional file 3 , and 18 were included in the final analysis (Fig. 1 ) [ 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ]. Reference list screening did not retrieve any additional systematic reviews.

PRISMA flow diagram

Characteristics of included reviews

Summary features of 18 systematic reviews are presented in Table 1 . They were published in 14 different journals. Only four of these journals had specific requirements for systematic reviews (with or without meta-analysis): European Journal of Internal Medicine, Journal of Clinical Medicine, Ultrasound in Obstetrics and Gynecology, and Clinical Research in Cardiology . Two journals reported that they published only invited reviews ( Journal of Medical Virology and Clinica Chimica Acta ). Three systematic reviews in our study were published as letters; one was labeled as a scoping review and another as a rapid review (Table 2 ).

All reviews were published in English, in first quartile (Q1) journals, with JIF ranging from 1.692 to 6.062. One review was empty, meaning that its search did not identify any relevant studies; i.e., no primary studies were included [ 36 ]. The remaining 17 reviews included 269 unique studies; the majority ( N = 211; 78%) were included in only a single review included in our study (range: 1 to 12). Primary studies included in the reviews were published between December 2019 and March 18, 2020, and comprised case reports, case series, cohorts, and other observational studies. We found only one review that included randomized clinical trials [ 38 ]. In the included reviews, systematic literature searches were performed from 2019 (entire year) up to March 9, 2020. Ten systematic reviews included meta-analyses. The list of primary studies found in the included systematic reviews is shown in Additional file 4 , as well as the number of reviews in which each primary study was included.

Population and study designs

Most of the reviews analyzed data from patients with COVID-19 who developed pneumonia, acute respiratory distress syndrome (ARDS), or any other correlated complication. One review aimed to evaluate the effectiveness of using surgical masks on preventing transmission of the virus [ 36 ], one review was focused on pediatric patients [ 34 ], and one review investigated COVID-19 in pregnant women [ 37 ]. Most reviews assessed clinical symptoms, laboratory findings, or radiological results.

Systematic review findings

The summary of findings from individual reviews is shown in Table 2 . Overall, all-cause mortality ranged from 0.3 to 13.9% (Fig. 2 ).

A meta-analysis of the prevalence of mortality

Clinical symptoms

Seven reviews described the main clinical manifestations of COVID-19 [ 26 , 28 , 29 , 34 , 35 , 39 , 41 ]. Three of them provided only a narrative discussion of symptoms [ 26 , 34 , 35 ]. In the reviews that performed a statistical analysis of the incidence of different clinical symptoms, symptoms in patients with COVID-19 were (range values of point estimates): fever (82–95%), cough with or without sputum (58–72%), dyspnea (26–59%), myalgia or muscle fatigue (29–51%), sore throat (10–13%), headache (8–12%), gastrointestinal disorders, such as diarrhea, nausea or vomiting (5.0–9.0%), and others (including, in one study only: dizziness 12.1%) (Figs. 3 , 4 , 5 , 6 , 7 , 8 and 9 ). Three reviews assessed cough with and without sputum together; only one review assessed sputum production itself (28.5%).

A meta-analysis of the prevalence of fever

A meta-analysis of the prevalence of cough

A meta-analysis of the prevalence of dyspnea

A meta-analysis of the prevalence of fatigue or myalgia

A meta-analysis of the prevalence of headache

A meta-analysis of the prevalence of gastrointestinal disorders

A meta-analysis of the prevalence of sore throat

Diagnostic aspects

Three reviews described methodologies, protocols, and tools used for establishing the diagnosis of COVID-19 [ 26 , 34 , 38 ]. The use of respiratory swabs (nasal or pharyngeal) or blood specimens to assess the presence of SARS-CoV-2 nucleic acid using RT-PCR assays was the most commonly used diagnostic method mentioned in the included studies. These diagnostic tests have been widely used, but their precise sensitivity and specificity remain unknown. One review included a Chinese study with clinical diagnosis with no confirmation of SARS-CoV-2 infection (patients were diagnosed with COVID-19 if they presented with at least two symptoms suggestive of COVID-19, together with laboratory and chest radiography abnormalities) [ 34 ].

Therapeutic possibilities

Pharmacological and non-pharmacological interventions (supportive therapies) used in treating patients with COVID-19 were reported in five reviews [ 25 , 27 , 34 , 35 , 38 ]. Antivirals used empirically for COVID-19 treatment were reported in seven reviews [ 25 , 27 , 34 , 35 , 37 , 38 , 41 ]; most commonly used were protease inhibitors (lopinavir, ritonavir, darunavir), nucleoside reverse transcriptase inhibitor (tenofovir), nucleotide analogs (remdesivir, galidesivir, ganciclovir), and neuraminidase inhibitors (oseltamivir). Umifenovir, a membrane fusion inhibitor, was investigated in two studies [ 25 , 35 ]. Possible supportive interventions analyzed were different types of oxygen supplementation and breathing support (invasive or non-invasive ventilation) [ 25 ]. The use of antibiotics, both empirically and to treat secondary pneumonia, was reported in six studies [ 25 , 26 , 27 , 34 , 35 , 38 ]. One review specifically assessed evidence on the efficacy and safety of the anti-malaria drug chloroquine [ 27 ]. It identified 23 ongoing trials investigating the potential of chloroquine as a therapeutic option for COVID-19, but no verifiable clinical outcomes data. The use of mesenchymal stem cells, antifungals, and glucocorticoids were described in four reviews [ 25 , 34 , 35 , 38 ].

Laboratory and radiological findings

Of the 18 reviews included in this overview, eight analyzed laboratory parameters in patients with COVID-19 [ 25 , 29 , 30 , 32 , 33 , 34 , 35 , 39 ]; elevated C-reactive protein levels, associated with lymphocytopenia, elevated lactate dehydrogenase, as well as slightly elevated aspartate and alanine aminotransferase (AST, ALT) were commonly described in those eight reviews. Lippi et al. assessed cardiac troponin I (cTnI) [ 25 ], procalcitonin [ 32 ], and platelet count [ 33 ] in COVID-19 patients. Elevated levels of procalcitonin [ 32 ] and cTnI [ 30 ] were more likely to be associated with a severe disease course (requiring intensive care unit admission and intubation). Furthermore, thrombocytopenia was frequently observed in patients with complicated COVID-19 infections [ 33 ].

Chest imaging (chest radiography and/or computed tomography) features were assessed in six reviews, all of which described a frequent pattern of local or bilateral multilobar ground-glass opacity [ 25 , 34 , 35 , 39 , 40 , 41 ]. Those six reviews showed that septal thickening, bronchiectasis, pleural and cardiac effusions, halo signs, and pneumothorax were observed in patients suffering from COVID-19.

Quality of evidence in individual systematic reviews

Table 3 shows the detailed results of the quality assessment of 18 systematic reviews, including the assessment of individual items and summary assessment. A detailed explanation for each decision in each review is available in Additional file 5 .

Using AMSTAR 2 criteria, confidence in the results of all 18 reviews was rated as “critically low” (Table 3 ). Common methodological drawbacks were: omission of prospective protocol submission or publication; use of inappropriate search strategy: lack of independent and dual literature screening and data-extraction (or methodology unclear); absence of an explanation for heterogeneity among the studies included; lack of reasons for study exclusion (or rationale unclear).

Risk of bias assessment, based on a reported methodological tool, and quality of evidence appraisal, in line with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) method, were reported only in one review [ 25 ]. Five reviews presented a table summarizing bias, using various risk of bias tools [ 25 , 29 , 39 , 40 , 41 ]. One review analyzed “study quality” [ 37 ]. One review mentioned the risk of bias assessment in the methodology but did not provide any related analysis [ 28 ].

This overview of systematic reviews analyzed the first 18 systematic reviews published after the onset of the COVID-19 pandemic, up to March 24, 2020, with primary studies involving more than 60,000 patients. Using AMSTAR-2, we judged that our confidence in all those reviews was “critically low”. Ten reviews included meta-analyses. The reviews presented data on clinical manifestations, laboratory and radiological findings, and interventions. We found no systematic reviews on the utility of diagnostic tests.

Symptoms were reported in seven reviews; most of the patients had a fever, cough, dyspnea, myalgia or muscle fatigue, and gastrointestinal disorders such as diarrhea, nausea, or vomiting. Olfactory dysfunction (anosmia or dysosmia) has been described in patients infected with COVID-19 [ 43 ]; however, this was not reported in any of the reviews included in this overview. During the SARS outbreak in 2002, there were reports of impairment of the sense of smell associated with the disease [ 44 , 45 ].

The reported mortality rates ranged from 0.3 to 14% in the included reviews. Mortality estimates are influenced by the transmissibility rate (basic reproduction number), availability of diagnostic tools, notification policies, asymptomatic presentations of the disease, resources for disease prevention and control, and treatment facilities; variability in the mortality rate fits the pattern of emerging infectious diseases [ 46 ]. Furthermore, the reported cases did not consider asymptomatic cases, mild cases where individuals have not sought medical treatment, and the fact that many countries had limited access to diagnostic tests or have implemented testing policies later than the others. Considering the lack of reviews assessing diagnostic testing (sensitivity, specificity, and predictive values of RT-PCT or immunoglobulin tests), and the preponderance of studies that assessed only symptomatic individuals, considerable imprecision around the calculated mortality rates existed in the early stage of the COVID-19 pandemic.

Few reviews included treatment data. Those reviews described studies considered to be at a very low level of evidence: usually small, retrospective studies with very heterogeneous populations. Seven reviews analyzed laboratory parameters; those reviews could have been useful for clinicians who attend patients suspected of COVID-19 in emergency services worldwide, such as assessing which patients need to be reassessed more frequently.

All systematic reviews scored poorly on the AMSTAR 2 critical appraisal tool for systematic reviews. Most of the original studies included in the reviews were case series and case reports, impacting the quality of evidence. Such evidence has major implications for clinical practice and the use of these reviews in evidence-based practice and policy. Clinicians, patients, and policymakers can only have the highest confidence in systematic review findings if high-quality systematic review methodologies are employed. The urgent need for information during a pandemic does not justify poor quality reporting.

We acknowledge that there are numerous challenges associated with analyzing COVID-19 data during a pandemic [ 47 ]. High-quality evidence syntheses are needed for decision-making, but each type of evidence syntheses is associated with its inherent challenges.

The creation of classic systematic reviews requires considerable time and effort; with massive research output, they quickly become outdated, and preparing updated versions also requires considerable time. A recent study showed that updates of non-Cochrane systematic reviews are published a median of 5 years after the publication of the previous version [ 48 ].

Authors may register a review and then abandon it [ 49 ], but the existence of a public record that is not updated may lead other authors to believe that the review is still ongoing. A quarter of Cochrane review protocols remains unpublished as completed systematic reviews 8 years after protocol publication [ 50 ].

Rapid reviews can be used to summarize the evidence, but they involve methodological sacrifices and simplifications to produce information promptly, with inconsistent methodological approaches [ 51 ]. However, rapid reviews are justified in times of public health emergencies, and even Cochrane has resorted to publishing rapid reviews in response to the COVID-19 crisis [ 52 ]. Rapid reviews were eligible for inclusion in this overview, but only one of the 18 reviews included in this study was labeled as a rapid review.

Ideally, COVID-19 evidence would be continually summarized in a series of high-quality living systematic reviews, types of evidence synthesis defined as “ a systematic review which is continually updated, incorporating relevant new evidence as it becomes available ” [ 53 ]. However, conducting living systematic reviews requires considerable resources, calling into question the sustainability of such evidence synthesis over long periods [ 54 ].

Research reports about COVID-19 will contribute to research waste if they are poorly designed, poorly reported, or simply not necessary. In principle, systematic reviews should help reduce research waste as they usually provide recommendations for further research that is needed or may advise that sufficient evidence exists on a particular topic [ 55 ]. However, systematic reviews can also contribute to growing research waste when they are not needed, or poorly conducted and reported. Our present study clearly shows that most of the systematic reviews that were published early on in the COVID-19 pandemic could be categorized as research waste, as our confidence in their results is critically low.

Our study has some limitations. One is that for AMSTAR 2 assessment we relied on information available in publications; we did not attempt to contact study authors for clarifications or additional data. In three reviews, the methodological quality appraisal was challenging because they were published as letters, or labeled as rapid communications. As a result, various details about their review process were not included, leading to AMSTAR 2 questions being answered as “not reported”, resulting in low confidence scores. Full manuscripts might have provided additional information that could have led to higher confidence in the results. In other words, low scores could reflect incomplete reporting, not necessarily low-quality review methods. To make their review available more rapidly and more concisely, the authors may have omitted methodological details. A general issue during a crisis is that speed and completeness must be balanced. However, maintaining high standards requires proper resourcing and commitment to ensure that the users of systematic reviews can have high confidence in the results.

Furthermore, we used adjusted AMSTAR 2 scoring, as the tool was designed for critical appraisal of reviews of interventions. Some reviews may have received lower scores than actually warranted in spite of these adjustments.

Another limitation of our study may be the inclusion of multiple overlapping reviews, as some included reviews included the same primary studies. According to the Cochrane Handbook, including overlapping reviews may be appropriate when the review’s aim is “ to present and describe the current body of systematic review evidence on a topic ” [ 12 ], which was our aim. To avoid bias with summarizing evidence from overlapping reviews, we presented the forest plots without summary estimates. The forest plots serve to inform readers about the effect sizes for outcomes that were reported in each review.

Several authors from this study have contributed to one of the reviews identified [ 25 ]. To reduce the risk of any bias, two authors who did not co-author the review in question initially assessed its quality and limitations.

Finally, we note that the systematic reviews included in our overview may have had issues that our analysis did not identify because we did not analyze their primary studies to verify the accuracy of the data and information they presented. We give two examples to substantiate this possibility. Lovato et al. wrote a commentary on the review of Sun et al. [ 41 ], in which they criticized the authors’ conclusion that sore throat is rare in COVID-19 patients [ 56 ]. Lovato et al. highlighted that multiple studies included in Sun et al. did not accurately describe participants’ clinical presentations, warning that only three studies clearly reported data on sore throat [ 56 ].

In another example, Leung [ 57 ] warned about the review of Li, L.Q. et al. [ 29 ]: “ it is possible that this statistic was computed using overlapped samples, therefore some patients were double counted ”. Li et al. responded to Leung that it is uncertain whether the data overlapped, as they used data from published articles and did not have access to the original data; they also reported that they requested original data and that they plan to re-do their analyses once they receive them; they also urged readers to treat the data with caution [ 58 ]. This points to the evolving nature of evidence during a crisis.

Our study’s strength is that this overview adds to the current knowledge by providing a comprehensive summary of all the evidence synthesis about COVID-19 available early after the onset of the pandemic. This overview followed strict methodological criteria, including a comprehensive and sensitive search strategy and a standard tool for methodological appraisal of systematic reviews.

In conclusion, in this overview of systematic reviews, we analyzed evidence from the first 18 systematic reviews that were published after the emergence of COVID-19. However, confidence in the results of all the reviews was “critically low”. Thus, systematic reviews that were published early on in the pandemic could be categorized as research waste. Even during public health emergencies, studies and systematic reviews should adhere to established methodological standards to provide patients, clinicians, and decision-makers trustworthy evidence.

Availability of data and materials

All data collected and analyzed within this study are available from the corresponding author on reasonable request.

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Acknowledgments

We thank Catherine Henderson DPhil from Swanscoe Communications for pro bono medical writing and editing support. We acknowledge support from the Covidence Team, specifically Anneliese Arno. We thank the whole International Network of Coronavirus Disease 2019 (InterNetCOVID-19) for their commitment and involvement. Members of the InterNetCOVID-19 are listed in Additional file 6 . We thank Pavel Cerny and Roger Crosthwaite for guiding the team supervisor (IJBN) on human resources management.

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Israel Júnior Borges do Nascimento & Milena Soriano Marcolino

Medical College of Wisconsin, Milwaukee, WI, USA

Israel Júnior Borges do Nascimento

Helene Fuld Health Trust National Institute for Evidence-based Practice in Nursing and Healthcare, College of Nursing, The Ohio State University, Columbus, OH, USA

Dónal P. O’Mathúna

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Thilo Caspar von Groote

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Livia Puljak

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IJBN conceived the research idea and worked as a project coordinator. DPOM, TCVG, HMA, IW, AM, LP, VTC, IZG, TPP, ANA, SF, NLB and MSM were involved in data curation, formal analysis, investigation, methodology, and initial draft writing. All authors revised the manuscript critically for the content. The author(s) read and approved the final manuscript.

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Supplementary Information

Additional file 1: appendix 1..

Search strategies used in the study.

Additional file 2: Appendix 2.

Adjusted scoring of AMSTAR 2 used in this study for systematic reviews of studies that did not analyze interventions.

Additional file 3: Appendix 3.

List of excluded studies, with reasons.

Additional file 4: Appendix 4.

Table of overlapping studies, containing the list of primary studies included, their visual overlap in individual systematic reviews, and the number in how many reviews each primary study was included.

Additional file 5: Appendix 5.

A detailed explanation of AMSTAR scoring for each item in each review.

Additional file 6: Appendix 6.

List of members and affiliates of International Network of Coronavirus Disease 2019 (InterNetCOVID-19).

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Borges do Nascimento, I.J., O’Mathúna, D.P., von Groote, T.C. et al. Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews. BMC Infect Dis 21 , 525 (2021). https://doi.org/10.1186/s12879-021-06214-4

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A novel coronavirus (CoV) named ‘2019-nCoV’ or ‘2019 novel coronavirus’ or ‘COVID-19’ by the World Health Organization (WHO) is in charge of the current outbreak of pneumonia that began at the beginning of December 2019 near in Wuhan City, Hubei Province, China [1–4]. COVID-19 is a pathogenic virus. From the phylogenetic analysis carried out with obtainable full genome sequences, bats occur to be the COVID-19 virus reservoir, but the intermediate host(s) has not been detected till now.

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1.1 A Brief History of the Coronavirus Outbreak

A novel coronavirus (CoV) named ‘2019-nCoV’ or ‘2019 novel coronavirus’ or ‘COVID-19’ by the World Health Organization (WHO) is in charge of the current outbreak of pneumonia that began at the beginning of December 2019 near in Wuhan City, Hubei Province, China [ 1 , 2 , 3 , 4 ]. COVID-19 is a pathogenic virus. From the phylogenetic analysis carried out with obtainable full genome sequences, bats occur to be the COVID-19 virus reservoir, but the intermediate host(s) has not been detected till now. Though three major areas of work already are ongoing in China to advise our awareness of the pathogenic origin of the outbreak. These include early inquiries of cases with symptoms occurring near in Wuhan during December 2019, ecological sampling from the Huanan Wholesale Seafood Market as well as other area markets, and the collection of detailed reports of the point of origin and type of wildlife species marketed on the Huanan market and the destination of those animals after the market has been closed [ 5 , 6 , 7 , 8 ].

Coronaviruses mostly cause gastrointestinal and respiratory tract infections and are inherently categorized into four major types: Gammacoronavirus, Deltacoronavirus, Betacoronavirus and Alphacoronavirus [ 9 , 10 , 11 ]. The first two types mainly infect birds, while the last two mostly infect mammals. Six types of human CoVs have been formally recognized. These comprise HCoVHKU1, HCoV-OC43, Middle East Respiratory Syndrome coronavirus (MERS-CoV), Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) which is the type of the Betacoronavirus, HCoV229E and HCoV-NL63, which are the member of the Alphacoronavirus. Coronaviruses did not draw global concern until the 2003 SARS pandemic [ 12 , 13 , 14 ], preceded by the 2012 MERS [ 15 , 16 , 17 ] and most recently by the COVID-19 outbreaks. SARS-CoV and MERS-CoV are known to be extremely pathogenic and spread from bats to palm civets or dromedary camels and eventually to humans.

COVID-19 is spread by dust particles and fomites while close unsafe touch between the infector and the infected individual. Airborne distribution has not been recorded for COVID-19 and is not known to be a significant transmission engine based on empirical evidence; although it can be imagined if such aerosol-generating practices are carried out in medical facilities. Faecal spreading has been seen in certain patients, and the active virus has been reported in a small number of clinical studies [ 18 , 19 , 20 ]. Furthermore, the faecal-oral route does not seem to be a COVID-19 transmission engine; its function and relevance for COVID-19 need to be identified.

For about 18,738,58 laboratory-confirmed cases recorded as of 2nd week of April 2020, the maximum number of cases (77.8%) was between 30 and 69 years of age. Among the recorded cases, 21.6% are farmers or employees by profession, 51.1% are male and 77.0% are Hubei.

However, there are already many concerns regarding the latest coronavirus. Although it seems to be transferred to humans by animals, it is important to recognize individual animals and other sources, the path of transmission, the incubation cycle, and the features of the susceptible community and the survival rate. Nonetheless, very little clinical knowledge on COVID-19 disease is currently accessible and details on age span, the animal origin of the virus, incubation time, outbreak curve, viral spectroscopy, dissemination pathogenesis, autopsy observations, and any clinical responses to antivirals are lacking among the serious cases.

1.2 How Different and Deadly COVID-19 is Compared to Plagues in History

COVID-19 has reached to more than 150 nations, including China, and has caused WHO to call the disease a worldwide pandemic. By the time of 2nd week of April 2020, this COVID-19 cases exceeded 18,738,58, although more than 1,160,45 deaths were recorded worldwide and United States of America became the global epicentre of coronavirus. More than one-third of the COVID-19 instances are outside of China. Past pandemics that have existed in the past decade or so, like bird flu, swine flu, and SARS, it is hard to find out the comparison between those pandemics and this coronavirus. Following is a guide to compare coronavirus with such diseases and recent pandemics that have reformed the world community.

1.2.1 Coronavirus Versus Seasonal Influenza

Influenza, or seasonal flu, occurs globally every year–usually between December and February. It is impossible to determine the number of reports per year because it is not a reportable infection (so no need to be recorded to municipality), so often patients with minor symptoms do not go to a physician. Recent figures placed the Rate of Case Fatality at 0.1% [ 21 , 22 , 23 ].

There are approximately 3–5 million reports of serious influenza a year, and about 250,000–500,000 deaths globally. In most developed nations, the majority of deaths arise in persons over 65 years of age. Moreover, it is unsafe for pregnant mothers, children under 59 months of age and individuals with serious illnesses.

The annual vaccination eliminates infection and severe risks in most developing countries but is nevertheless a recognized yet uncomfortable aspect of the season.

In contrast to the seasonal influenza, coronavirus is not so common, has led to fewer cases till now, has a higher rate of case fatality and has no antidote.

1.2.2 Coronavirus Versus Bird Flu (H5N1 and H7N9)

Several cases of bird flu have existed over the years, with the most severe in 2013 and 2016. This is usually from two separate strains—H5N1 and H7N9 [ 24 , 25 , 26 ].

The H7N9 outbreak in 2016 accounted for one-third of all confirmed human cases but remained confined relative to both coronavirus and other pandemics/outbreak cases. After the first outbreak, about 1,233 laboratory-confirmed reports of bird flu have occurred. The disease has a Rate of Case Fatality of 20–40%.

Although the percentage is very high, the blowout from individual to individual is restricted, which, in effect, has minimized the number of related deaths. It is also impossible to monitor as birds do not necessarily expire from sickness.

In contrast to the bird flu, coronavirus becomes more common, travels more quickly through human to human interaction, has an inferior cardiothoracic ratio, resulting in further total fatalities and spread from the initial source.

1.2.3 Coronavirus Versus Ebola Epidemic

The Ebola epidemic of 2013 was primarily centred in 10 nations, including Sierra Leone, Guinea and Liberia have the greatest effects, but the extremely high Case Fatality Rate of 40% has created this as a significant problem for health professionals nationwide [ 27 , 28 , 29 ].

Around 2013 and 2016, there were about 28,646 suspicious incidents and about 11,323 fatalities, although these are expected to be overlooked. Those who survived from the original epidemic may still become sick months or even years later, because the infection may stay inactive for prolonged periods. Thankfully, a vaccination was launched in December 2016 and is perceived to be effective.

In contrast to the Ebola, coronavirus is more common globally, has caused in fewer fatalities, has a lesser case fatality rate, has no reported problems during treatment and after recovery, does not have an appropriate vaccination.

1.2.4 Coronavirus Versus Camel Flu (MERS)

Camel flu is a misnomer–though camels have MERS antibodies and may have been included in the transmission of the disease; it was originally transmitted to humans through bats [ 30 , 31 , 32 ]. Like Ebola, it infected only a limited number of nations, i.e. about 27, but about 858 fatalities from about 2,494 laboratory-confirmed reports suggested that it was a significant threat if no steps were taken in place to control it.

In contrast to the camel flu, coronavirus is more common globally, has occurred more fatalities, has a lesser case fatality rate, and spreads more easily among humans.

1.2.5 Coronavirus Versus Swine Flu (H1N1)

Swine flu is the same form of influenza that wiped 1.7% of the world population in 1918. This was deemed a pandemic again in June 2009 an approximately-21% of the global population infected by this [ 33 , 34 , 35 ].

Thankfully, the case fatality rate is substantially lower than in the last pandemic, with 0.1%–0.5% of events ending in death. About 18,500 of these fatalities have been laboratory-confirmed, but statistics range as high as 151,700–575,400 worldwide. 50–80% of severe occurrences have been reported in individuals with chronic illnesses like asthma, obesity, cardiovascular diseases and diabetes.

In contrast to the swine flu, coronavirus is not so common, has caused fewer fatalities, has more case fatality rate, has a longer growth time and less impact on young people.

1.2.6 Coronavirus Versus Severe Acute Respiratory Syndrome (SARS)

SARS was discovered in 2003 as it spread from bats to humans resulted in about 774 fatalities. By May there were eventually about 8,100 reports across 17 countries, with a 15% case fatality rate. The number is estimated to be closer to 9.6% as confirmed cases are counted, with 0.9% cardiothoracic ratio for people aged 20–29, rising to 28% for people aged 70–79. Similar to coronavirus, SARS had bad results for males than females in all age categories [ 36 , 37 , 38 ].

Coronavirus is more common relative to SARS, which ended in more overall fatalities, lower case fatality rate, the even higher case fatality rate in older ages, and poorer results for males.

1.2.7 Coronavirus Versus Hong Kong Flu (H3N2)

The Hong Kong flu pandemic erupted on 13 July 1968, with 1–4 million deaths globally by 1969. It was one of the greatest flu pandemics of the twentieth century, but thankfully the case fatality rate was smaller than the epidemic of 1918, resulting in fewer fatalities overall. That may have been attributed to the fact that citizens had generated immunity owing to a previous epidemic in 1957 and to better medical treatment [ 39 ].

In contrast to the Hong Kong flu, coronavirus is not so common, has caused in fewer fatalities and has a higher case fatality rate.

1.2.8 Coronavirus Versus Spanish Flu (H1N1)

The 1918 Spanish flu pandemic was one of the greatest occurrences of recorded history. During the first year of the pandemic, lifespan in the US dropped by 12 years, with more civilians killed than HIV/AIDS in 24 h [ 40 , 41 , 42 ].

Regardless of the name, the epidemic did not necessarily arise in Spain; wartime censors in Germany, the United States, the United Kingdom and France blocked news of the disease, but Spain did not, creating the misleading perception that more cases and fatalities had occurred relative to its neighbours

This strain of H1N1 eventually affected more than 500 million men, or 27% of the world’s population at the moment, and had deaths of between 40 and 50 million. At the end of 1920, 1.7% of the world’s people had expired of this illness, including an exceptionally high death rate for young adults aged between 20 and 40 years.

In contrast to the Spanish flu, coronavirus is not so common, has caused in fewer fatalities, has a higher case fatality rate, is more harmful to older ages and is less risky for individuals aged 20–40 years.

1.2.9 Coronavirus Versus Common Cold (Typically Rhinovirus)

Common cold is the most common illness impacting people—Typically, a person suffers from 2–3 colds each year and the average kid will catch 6–8 during the similar time span. Although there are more than 200 cold-associated virus types, infections are uncommon and fatalities are very rare and typically arise mainly in extremely old, extremely young or immunosuppressed cases [ 43 , 44 ].

In contrast to the common cold, coronavirus is not so prevalent, causes more fatalities, has more case fatality rate, is less infectious and is less likely to impact small children.

1.3 Reviews of Online Portals and Social Media for Epidemic Information Dissemination

As COVID-19 started to propagate across the globe, the outbreak contributed to a significant change in the broad technology platforms. Where they once declined to engage in the affairs of their systems, except though the possible danger to public safety became obvious, the advent of a novel coronavirus placed them in a different interventionist way of thought. Big tech firms and social media are taking concrete steps to guide users to relevant, credible details on the virus [ 45 , 46 , 47 , 48 ]. And some of the measures they’re doing proactively. Below are a few of them.

Facebook started adding a box in the news feed that led users to the Centers for Disease Control website regarding COVID-19. It reflects a significant departure from the company’s normal strategy of placing items in the News Feed. The purpose of the update, after all, is personalization—Facebook tries to give the posts you’re going to care about, whether it is because you’re connected with a person or like a post. In the virus package, Facebook has placed a remarkable algorithmic thumb on the scale, potentially pushing millions of people to accurate, authenticated knowledge from a reputable source.

Similar initiatives have been adopted by Twitter. Searching for COVID-19 will carry you to a page highlighting the latest reports from public health groups and credible national news outlets. The search also allows for common misspellings. Twitter has stated that although Russian-style initiatives to cause discontent by large-scale intelligence operations have not yet been observed, a zero-tolerance approach to network exploitation and all other attempts to exploit their service at this crucial juncture will be expected. The problem has the attention of the organization. It also offers promotional support to public service agencies and other non-profit groups.

Google has made a step in making it better for those who choose to operate or research from home, offering specialized streaming services to all paying G Suite customers. Google also confirmed that free access to ‘advanced’ Hangouts Meet apps will be rolled out to both G Suite and G Suite for Education clients worldwide through 1st July. It ensures that companies can hold meetings of up to 250 people, broadcast live to up to about 100,000 users within a single network, and archive and export meetings to Google Drive. Usually, Google pays an additional $13 per person per month for these services in comparison to G Suite’s ‘enterprise’ membership, which adds up to a total of about $25 per client each month.

Microsoft took a similar move, introducing the software ‘Chat Device’ to help public health and protection in the coronavirus epidemic, which enables collaborative collaboration via video and text messaging. There’s an aspect of self-interest in this. Tech firms are offering out their goods free of charge during periods of emergency for the same purpose as newspapers are reducing their paywalls: it’s nice to draw more paying consumers.

Pinterest, which has introduced much of the anti-misinformation strategies that Facebook and Twitter are already embracing, is now restricting the search results for ‘coronavirus’, ‘COVID-19’ and similar words for ‘internationally recognized health organizations’.

Google-owned YouTube, traditionally the most conspiratorial website, has recently introduced a connection to the World Health Organization virus epidemic page to the top of the search results. In the early days of the epidemic, BuzzFeed found famous coronavirus conspiratorial videos on YouTube—especially in India, where one ‘explain’ with a false interpretation of the sources of the disease racketeered 13 million views before YouTube deleted it. Yet in the United States, conspiratorial posts regarding the illness have failed to gain only 1 million views.

That’s not to suggest that misinformation doesn’t propagate on digital platforms—just as it travels through the broader Internet, even though interaction with friends and relatives. When there’s a site that appears to be under-performing in the global epidemic, it’s Facebook-owned WhatsApp, where the Washington Post reported ‘a torrent of disinformation’ in places like Nigeria, Indonesia, Peru, Pakistan and Ireland. Given the encrypted existence of the app, it is difficult to measure the severity of the problem. Misinformation is also spread in WhatsApp communities, where participation is restricted to about 250 individuals. Knowledge of one category may be readily exchanged with another; however, there is a considerable amount of complexity of rotating several groups to peddle affected healing remedies or propagate false rumours.

1.4 Preventative Measures and Policies Enforced by the World Health Organization (WHO) and Different Countries

Coronavirus is already an ongoing epidemic, so it is necessary to take precautions to minimize both the risk of being sick and the transmission of the disease.

1.4.1 WHO Advice [ 49 ]

Wash hands regularly with alcohol-based hand wash or soap and water.

Preserve contact space (at least 1 m/3 feet between you and someone who sneezes or coughs).

Don’t touch your nose, head and ears.

Cover your nose and mouth as you sneeze or cough, preferably with your bent elbow or tissue.

Try to find early medical attention if you have fatigue, cough and trouble breathing.

Take preventive precautions if you are in or have recently go to places where coronavirus spreads.

1.4.2 China

The first person believed to have become sick because of the latest virus was near in Wuhan on 1 December 2019. A formal warning of the epidemic was released on 31 December. The World Health Organization was informed of the epidemic on the same day. Through 7 January, the Chinese Government addressed the avoidance and regulation of COVID-19. A curfew was declared on 23 January to prohibit flying in and out of Wuhan. Private usage of cars has been banned in the region. Chinese New Year (25 January) festivities have been cancelled in many locations [ 50 ].

On 26 January, the Communist Party and the Government adopted more steps to contain the COVID-19 epidemic, including safety warnings for travellers and improvements to national holidays. The leading party has agreed to prolong the Spring Festival holiday to control the outbreak. Universities and schools across the world have already been locked down. Many steps have been taken by the Hong Kong and Macau governments, in particular concerning schools and colleges. Remote job initiatives have been placed in effect in many regions of China. Several immigration limits have been enforced.

Certain counties and cities outside Hubei also implemented travel limits. Public transit has been changed and museums in China have been partially removed. Some experts challenged the quality of the number of cases announced by the Chinese Government, which constantly modified the way coronavirus cases were recorded.

1.4.3 Italy

Italy, a member state of the European Union and a popular tourist attraction, entered the list of coronavirus-affected nations on 30 January, when two positive cases in COVID-19 were identified among Chinese tourists. Italy has the largest number of coronavirus infections both in Europe and outside of China [ 51 ].

Infections, originally limited to northern Italy, gradually spread to all other areas. Many other nations in Asia, Europe and the Americas have tracked their local cases to Italy. Several Italian travellers were even infected with coronavirus-positive in foreign nations.

Late in Italy, the most impacted coronavirus cities and counties are Lombardia, accompanied by Veneto, Emilia-Romagna, Marche and Piedmonte. Milan, the second most populated city in Italy, is situated in Lombardy. Other regions in Italy with coronavirus comprised Campania, Toscana, Liguria, Lazio, Sicilia, Friuli Venezia Giulia, Umbria, Puglia, Trento, Abruzzo, Calabria, Molise, Valle d’Aosta, Sardegna, Bolzano and Basilicata.

Italy ranks 19th of the top 30 nations getting high-risk coronavirus airline passengers in China, as per WorldPop’s provisional study of the spread of COVID-19.

The Italian State has taken steps like the inspection and termination of large cultural activities during the early days of the coronavirus epidemic and has gradually declared the closing of educational establishments and airport hygiene/disinfection initiatives.

The Italian National Institute of Health suggested social distancing and agreed that the broader community of the country’s elderly is a problem. In the meantime, several other nations, including the US, have recommended that travel to Italy should be avoided temporarily, unless necessary.

The Italian government has declared the closing (quarantine) of the impacted areas in the northern region of the nation so as not to spread to the rest of the world. Italy has declared the immediate suspension of all to-and-fro air travel with China following coronavirus discovery by a Chinese tourist to Italy. Italian airlines, like Ryan Air, have begun introducing protective steps and have begun calling for the declaration forms to be submitted by passengers flying to Poland, Slovakia and Lithuania.

The Italian government first declined to permit fans to compete in sporting activities until early April to prevent the potential transmission of coronavirus. The step ensured players of health and stopped event cancellations because of coronavirus fears. Two days of the declaration, the government cancelled all athletic activities owing to the emergence of the outbreak asking for an emergency. Sports activities in Veneto, Lombardy and Emilia-Romagna, which recorded coronavirus-positive infections, were confirmed to be temporarily suspended. Schools and colleges in Italy have also been forced to shut down.

Iran announced the first recorded cases of SARS-CoV-2 infection on 19 February when, as per the Medical Education and Ministry of Health, two persons died later that day. The Ministry of Islamic Culture and Guidance has declared the cancellation of all concerts and other cultural activities for one week. The Medical Education and Ministry of Health has also declared the closing of universities, higher education colleges and schools in many cities and regions. The Department of Sports and Culture has taken action to suspend athletic activities, including football matches [ 52 ].

On 2 March 2020, the government revealed plans to train about 300,000 troops and volunteers to fight the outbreak of the epidemic, and also send robots and water cannons to clean the cities. The State also developed an initiative and a webpage to counter the epidemic. On 9 March 2020, nearly 70,000 inmates were immediately released from jail owing to the epidemic, presumably to prevent the further dissemination of the disease inside jails. The Revolutionary Guards declared a campaign on 13 March 2020 to clear highways, stores and public areas in Iran. President Hassan Rouhani stated on 26 February 2020 that there were no arrangements to quarantine areas impacted by the epidemic and only persons should be quarantined. The temples of Shia in Qom stayed open to pilgrims.

1.4.5 South Korea

On 20 January, South Korea announced its first occurrence. There was a large rise in cases on 20 February, possibly due to the meeting in Daegu of a progressive faith community recognized as the Shincheonji Church of Christ. Any citizens believed that the hospital was propagating the disease. As of 22 February, 1,261 of the 9,336 members of the church registered symptoms. A petition was distributed calling for the abolition of the church. More than 2,000 verified cases were registered on 28 February, increasing to 3,150 on 29 February [ 53 ].

Several educational establishments have been partially closing down, including hundreds of kindergartens in Daegu and many primary schools in Seoul. As of 18 February, several South Korean colleges had confirmed intentions to delay the launch of the spring semester. That included 155 institutions deciding to postpone the start of the semester by two weeks until 16 March, and 22 institutions deciding to delay the start of the semester by one week until 9 March. Also, on 23 February 2020, all primary schools, kindergartens, middle schools and secondary schools were declared to postpone the start of the semester from 2 March to 9 March.

South Korea’s economy is expected to expand by 1.9%, down from 2.1%. The State has given 136.7 billion won funding to local councils. The State has also coordinated the purchase of masks and other sanitary supplies. Entertainment Company SM Entertainment is confirmed to have contributed five hundred million won in attempts to fight the disease.

In the kpop industry, the widespread dissemination of coronavirus within South Korea has contributed to the cancellation or postponement of concerts and other programmes for kpop activities inside and outside South Korea. For instance, circumstances such as the cancellation of the remaining Asian dates and the European leg for the Seventeen’s Ode To You Tour on 9 February 2020 and the cancellation of all Seoul dates for the BTS Soul Tour Map. As of 15 March, a maximum of 136 countries and regions provided entry restrictions and/or expired visas for passengers from South Korea.

1.4.6 France

The overall reported cases of coronavirus rose significantly in France on 12 March. The areas with reported cases include Paris, Amiens, Bordeaux and Eastern Haute-Savoie. The first coronaviral death happened in France on 15 February, marking it the first death in Europe. The second death of a 60-year-old French national in Paris was announced on 26 February [ 54 ].

On February 28, fashion designer Agnès B. (not to be mistaken with Agnès Buzyn) cancelled fashion shows at the Paris Fashion Week, expected to continue until 3 March. On a subsequent day, the Paris half-marathon, planned for Sunday 1 March with 44,000 entrants, was postponed as one of a series of steps declared by Health Minister Olivier Véran.

On 13 March, the Ligue de Football Professional disbanded Ligue 1 and Ligue 2 (France’s tier two professional divisions) permanently due to safety threats.

1.4.7 Germany

Germany has a popular Regional Pandemic Strategy detailing the roles and activities of the health care system participants in the case of a significant outbreak. Epidemic surveillance is carried out by the federal government, like the Robert Koch Center, and by the German governments. The German States have their preparations for an outbreak. The regional strategy for the treatment of the current coronavirus epidemic was expanded by March 2020. Four primary goals are contained in this plan: (1) to minimize mortality and morbidity; (2) to guarantee the safety of sick persons; (3) to protect vital health services and (4) to offer concise and reliable reports to decision-makers, the media and the public [ 55 ].

The programme has three phases that may potentially overlap: (1) isolation (situation of individual cases and clusters), (2) safety (situation of further dissemination of pathogens and suspected causes of infection), (3) prevention (situation of widespread infection). So far, Germany has not set up border controls or common health condition tests at airports. Instead, while at the isolation stage-health officials are concentrating on recognizing contact individuals that are subject to specific quarantine and are tracked and checked. Specific quarantine is regulated by municipal health authorities. By doing so, the officials are seeking to hold the chains of infection small, contributing to decreased clusters. At the safety stage, the policy should shift to prevent susceptible individuals from being harmed by direct action. By the end of the day, the prevention process should aim to prevent cycles of acute treatment to retain emergency facilities.

1.4.8 United States

The very first case of coronavirus in the United States was identified in Washington on 21 January 2020 by an individual who flew to Wuhan and returned to the United States. The second case was recorded in Illinois by another individual who had travelled to Wuhan. Some of the regions with reported novel coronavirus infections in the US are California, Arizona, Connecticut, Illinois, Texas, Wisconsin and Washington [ 56 ].

As the epidemic increased, requests for domestic air travel decreased dramatically. By 4 March, U.S. carriers, like United Airlines and JetBlue Airways, started growing their domestic flight schedules, providing generous unpaid leave to workers and suspending recruits.

A significant number of universities and colleges cancelled classes and reopened dormitories in response to the epidemic, like Cornell University, Harvard University and the University of South Carolina.

On 3 March 2020, the Federal Reserve reduced its goal interest rate from 1.75% to 1.25%, the biggest emergency rate cut following the 2008 global financial crash, in combat the effect of the recession on the American economy. In February 2020, US businesses, including Apple Inc. and Microsoft, started to reduce sales projections due to supply chain delays in China caused by the COVID-19.

The pandemic, together with the subsequent financial market collapse, also contributed to greater criticism of the crisis in the United States. Researchers disagree about when a recession is likely to take effect, with others suggesting that it is not unavoidable, while some claim that the world might already be in recession. On 3 March, Federal Reserve Chairman Jerome Powell reported a 0.5% (50 basis point) interest rate cut from the coronavirus in the context of the evolving threats to economic growth.

When ‘social distance’ penetrated the national lexicon, disaster response officials promoted the cancellation of broad events to slow down the risk of infection. Technical conferences like E3 2020, Apple Inc.’s Worldwide Developers Conference (WWDC), Google I/O, Facebook F8, and Cloud Next and Microsoft’s MVP Conference have been either having replaced or cancelled in-person events with internet streaming events.

On February 29, the American Physical Society postponed its annual March gathering, planned for March 2–6 in Denver, Colorado, even though most of the more than 11,000 physicist attendees already had arrived and engaged in the pre-conference day activities. On March 6, the annual South to Southwest (SXSW) seminar and festival planned to take place from March 13–22 in Austin, Texas, was postponed after the city council announced a local disaster and forced conferences to be shut down for the first time in 34 years.

Four of North America’s major professional sports leagues—the National Hockey League (NHL), National Basketball Association (NBA), Major League Soccer (MLS) and Major League Baseball (MLB) —jointly declared on March 9 that they would all limit the media access to player accommodations (such as locker rooms) to control probable exposure.

1.5 Emergency Funding to Fight the COVID-19

COVID-19 pandemic has become a common international concern. Different countries are donating funds to fight against it [ 57 , 58 , 59 , 60 ]. Some of them are mentioned here.

China has allocated about 110.48 billion yuan ($15.93 billion) in coronavirus-related funding.

Foreign Minister Mohammad Javad Zarif said that Iran has requested the International Monetary Fund (IMF) of about $5 billion in emergency funding to help to tackle the coronavirus epidemic that has struck the Islamic Republic hard.

President Donald Trump approved the Emergency Supplementary Budget Bill to support the US response to a novel coronavirus epidemic. The budget plan would include about $8.3 billion in discretionary funding to local health authorities to promote vaccine research for production. Trump originally requested just about $2 billion to combat the epidemic, but Congress quadrupled the number in its version of the bill. Mr. Trump formally announced a national emergency that he claimed it will give states and territories access to up to about $50 billion in federal funding to tackle the spread of the coronavirus outbreak.

California politicians approved a plan to donate about $1 billion on the state’s emergency medical responses as it readies hospitals to fight an expected attack of patients because of the COVID-19 pandemic. The plans, drawn up rapidly in reaction to the dramatic rise in reported cases of the virus, would include the requisite funds to establish two new hospitals in California, with the assumption that the state may not have the resources to take care of the rise in patients. The bill calls for an immediate response of about $500 million from the State General Fund, with an additional about $500 million possible if requested.

India committed about $10 million to the COVID-19 Emergency Fund and said it was setting up a rapid response team of physicians for the South Asian Association for Regional Cooperation (Saarc) countries.

South Korea unveiled an economic stimulus package of about 11.7 trillion won ($9.8 billion) to soften the effects of the biggest coronavirus epidemic outside China as attempts to curb the disease exacerbate supply shortages and drain demand. Of the 11,7 trillion won expected, about 3.2 trillion won would cover up the budget shortfall, while an additional fiscal infusion of about 8.5 trillion won. An estimated 10.3 trillion won in government bonds will be sold this year to fund the extra expenditure. About 2.3 trillion won will be distributed to medical establishments and would support quarantine operations, with another 3.0 trillion won heading to small and medium-sized companies unable to pay salaries to their employees and child care supports.

The Swedish Parliament announced a set of initiatives costing more than 300 billion Swedish crowns ($30.94 billion) to help the economy in the view of the coronavirus pandemic. The plan contained steps like the central government paying the entire expense of the company’s sick leave during April and May, and also the high cost of compulsory redundancies owing to the crisis.

In consideration of the developing scenario, an updating of this strategy is planned to take place before the end of March and will recognize considerably greater funding demands for the country response, R&D and WHO itself.

1.6 Artificial Intelligence, Data Science and Technological Solutions Against COVID-19

These days, Artificial Intelligence (AI) takes a major role in health care. Throughout a worldwide pandemic such as the COVID-19, technology, artificial intelligence and data analytics have been crucial in helping communities cope successfully with the epidemic [ 61 , 62 , 63 , 64 , 65 ]. Through the aid of data mining and analytical modelling, medical practitioners are willing to learn more about several diseases.

1.6.1 Public Health Surveillance

The biggest risk of coronavirus is the level of spreading. That’s why policymakers are introducing steps like quarantines around the world because they can’t adequately monitor local outbreaks. One of the simplest measures to identify ill patients through the study of CCTV images that are still around us and to locate and separate individuals that have serious signs of the disease and who have touched and disinfected the related surfaces. Smartphone applications are often used to keep a watch on people’s activities and to assess whether or not they have come in touch with an infected human.

1.6.2 Remote Biosignal Measurement

Many of the signs such as temperature or heartbeat are very essential to overlook and rely entirely on the visual image that may be misleading. However, of course, we can’t prevent someone from checking their blood pressure, heart or temperature. Also, several advances in computer vision can predict pulse and blood pressure based on facial skin examination. Besides, there are several advances in computer vision that can predict pulse and blood pressure based on facial skin examination.

Access to public records has contributed to the development of dashboards that constantly track the virus. Several companies are designing large data dashboards. Face recognition and infrared temperature monitoring technologies have been mounted in all major cities. Chinese AI companies including Hanwang Technology and SenseTime have reported having established a special facial recognition system that can correctly identify people even though they are covered.

1.6.3 IoT and Wearables

Measurements like pulse are much more natural and easier to obtain from tracking gadgets like activity trackers and smartwatches that nearly everybody has already. Some work suggests that the study of cardiac activity and its variations from the standard will reveal early signs of influenza and, in this case, coronavirus.

1.6.4 Chatbots and Communication

Apart from public screening, people’s knowledge and self-assessment may also be used to track their health. If you can check your temperature and pulse every day and monitor your coughs time-to-time, you can even submit that to your record. If the symptoms are too serious, either an algorithm or a doctor remotely may prescribe a person to stay home, take several other preventive measures, or recommend a visit from the doctor.

Al Jazeera announced that China Mobile had sent text messages to state media departments, telling them about the citizens who had been affected. The communications contained all the specifics of the person’s travel history.

Tencent runs WeChat, and via it, citizens can use free online health consultation services. Chatbots have already become important connectivity platforms for transport and tourism service providers to keep passengers up-to-date with the current transport protocols and disturbances.

1.6.5 Social Media and Open Data

There are several people who post their health diary with total strangers via Facebook or Twitter. Such data becomes helpful for more general research about how far the epidemic has progressed. For consumer knowledge, we may even evaluate the social network group to attempt to predict what specific networks are at risk of being viral.

Canadian company BlueDot analyses far more than just social network data: for instance, global activities of more than four billion passengers on international flights per year; animal, human and insect population data; satellite environment data and relevant knowledge from health professionals and journalists, across 100,000 news posts per day covering 65 languages. This strategy was so successful that the corporation was able to alert clients about coronavirus until the World Health Organization and the Centers for Disease Control and Prevention notified the public.

1.6.6 Automated Diagnostics

COVID-19 has brought up another healthcare issue today: it will not scale when the number of patients increases exponentially (actually stressed doctors are always doing worse) and the rate of false-negative diagnosis remains very high. Machine learning therapies don’t get bored and scale simply by growing computing forces.

Baidu, the Chinese Internet company, has made the Lineatrfold algorithm accessible to the outbreak-fighting teams, according to the MIT Technology Review. Unlike HIV, Ebola and Influenza, COVID-19 has just one strand of RNA and it can mutate easily. The algorithm is also simpler than other algorithms that help to determine the nature of the virus. Baidu has also developed software to efficiently track large populations. It has also developed an Ai-powered infrared device that can detect a difference in the body temperature of a human. This is currently being used in Beijing’s Qinghe Railway Station to classify possibly contaminated travellers where up to 200 individuals may be checked in one minute without affecting traffic movement, reports the MIT Review.

Singapore-based Veredus Laboratories, a supplier of revolutionary molecular diagnostic tools, has currently announced the launch of the VereCoV detector package, a compact Lab-on-Chip device able to detect MERS-CoV, SARS-CoV and COVID-19, i.e. Wuhan Coronavirus, in a single study.

The VereCoV identification package is focused on VereChip technology, a Lab-on-Chip device that incorporates two important molecular biological systems, Polymerase Chain Reaction (PCR) and a microarray, which will be able to classify and distinguish within 2 h MERS-CoV, SARS-CoV and COVID-19 with high precision and responsiveness.

This is not just the medical activities of healthcare facilities that are being charged, but also the corporate and financial departments when they cope with the increase in patients. Ant Financials’ blockchain technology helps speed-up the collection of reports and decreases the number of face-to-face encounters with patients and medical personnel.

Companies like the Israeli company Sonovia are aiming to provide healthcare systems and others with face masks manufactured from their anti-pathogenic, anti-bacterial cloth that depends on metal-oxide nanoparticles.

1.6.7 Drug Development Research

Aside from identifying and stopping the transmission of pathogens, the need to develop vaccinations on a scale is also needed. One of the crucial things to make that possible is to consider the origin and essence of the virus. Google’s DeepMind, with their expertise in protein folding research, has rendered a jump in identifying the protein structure of the virus and making it open-source.

BenevolentAI uses AI technologies to develop medicines that will combat the most dangerous diseases in the world and is also working to promote attempts to cure coronavirus, the first time the organization has based its product on infectious diseases. Within weeks of the epidemic, it used its analytical capability to recommend new medicines that might be beneficial.

1.6.8 Robotics

Robots are not vulnerable to the infection, and they are used to conduct other activities, like cooking meals in hospitals, doubling up as waiters in hotels, spraying disinfectants and washing, selling rice and hand sanitizers, robots are on the front lines all over to deter coronavirus spread. Robots also conduct diagnostics and thermal imaging in several hospitals. Shenzhen-based firm Multicopter uses robotics to move surgical samples. UVD robots from Blue Ocean Robotics use ultraviolet light to destroy viruses and bacteria separately. In China, Pudu Technology has introduced its robots, which are usually used in the cooking industry, to more than 40 hospitals throughout the region. According to the Reuters article, a tiny robot named Little Peanut is distributing food to passengers who have been on a flight from Singapore to Hangzhou, China, and are presently being quarantined in a hotel.

1.6.9 Colour Coding

Using its advanced and vast public service monitoring network, the Chinese government has collaborated with software companies Alibaba and Tencent to establish a colour-coded health ranking scheme that monitors millions of citizens every day. The mobile device was first introduced in Hangzhou with the cooperation of Alibaba. This applies three colours to people—red, green or yellow—based on their transportation and medical records. Tencent also developed related applications in the manufacturing centre of Shenzhen.

The decision of whether an individual will be quarantined or permitted in public spaces is dependent on the colour code. Citizens will sign into the system using pay wallet systems such as Alibaba’s Alipay and Ant’s wallet. Just those citizens who have been issued a green colour code will be permitted to use the QR code in public spaces at metro stations, workplaces, and other public areas. Checkpoints are in most public areas where the body temperature and the code of individual are tested. This programme is being used by more than 200 Chinese communities and will eventually be expanded nationwide.

1.6.10 Drones

In some of the seriously infected regions where people remain at risk of contracting the infection, drones are used to rescue. One of the easiest and quickest ways to bring emergency supplies where they need to go while on an epidemic of disease is by drone transportation. Drones carry all surgical instruments and patient samples. This saves time, improves the pace of distribution and reduces the chance of contamination of medical samples. Drones often operate QR code placards that can be checked to record health records. There are also agricultural drones distributing disinfectants in the farmland. Drones, operated by facial recognition, are often used to warn people not to leave their homes and to chide them for not using face masks. Terra Drone uses its unmanned drones to move patient samples and vaccination content at reduced risk between the Xinchang County Disease Control Center and the People’s Hospital. Drones are often used to monitor public areas, document non-compliance with quarantine laws and thermal imaging.

1.6.11 Autonomous Vehicles

At a period of considerable uncertainty to medical professionals and the danger to people-to-people communication, automated vehicles are proving to be of tremendous benefit in the transport of vital products, such as medications and foodstuffs. Apollo, the Baidu Autonomous Vehicle Project, has joined hands with the Neolix self-driving company to distribute food and supplies to a big hospital in Beijing. Baidu Apollo has also provided its micro-car packages and automated cloud driving systems accessible free of charge to virus-fighting organizations.

Idriverplus, a Chinese self-driving organization that runs electrical street cleaning vehicles, is also part of the project. The company’s signature trucks are used to clean hospitals.

1.7 Summary

This chapter provides an introduction to the coronavirus outbreak (COVID-19). A brief history of this virus along with the symptoms are reported in this chapter. Then the comparison between COVID-19 and other plagues like seasonal influenza, bird flu (H5N1 and H7N9), Ebola epidemic, camel flu (MERS), swine flu (H1N1), severe acute respiratory syndrome, Hong Kong flu (H3N2), Spanish flu and the common cold are included in this chapter. Reviews of online portal and social media like Facebook, Twitter, Google, Microsoft, Pinterest, YouTube and WhatsApp concerning COVID-19 are reported in this chapter. Also, the preventive measures and policies enforced by WHO and different countries such as China, Italy, Iran, South Korea, France, Germany and the United States for COVID-19 are included in this chapter. Emergency funding provided by different countries to fight the COVID-19 is mentioned in this chapter. Lastly, artificial intelligence, data science and technological solutions like public health surveillance, remote biosignal measurement, IoT and wearables, chatbots and communication, social media and open data, automated diagnostics, drug development research, robotics, colour coding, drones and autonomous vehicles are included in this chapter.

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Fong, S.J., Dey, N., Chaki, J. (2021). An Introduction to COVID-19. In: Artificial Intelligence for Coronavirus Outbreak. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-15-5936-5_1

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Based on data from World Health Organization (WHO) COVID-19 situation reports. The COVID-19 outbreak was first recognized in Wuhan, China, in early December 2019. The number of confirmed COVID-19 cases is displayed by date of report and WHO region. SARS-CoV-2 indicates severe acute respiratory syndrome coronavirus 2.

Current understanding of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)–induced host immune response. SARS-CoV-2 targets cells through the viral structural spike (S) protein that binds to the angiotensin-converting enzyme 2 (ACE2) receptor. The serine protease type 2 transmembrane serine proteas (TMPRSS2) in the host cell further promotes viral uptake by cleaving ACE2 and activating the SARS-CoV-2 S protein. In the early stage, viral copy numbers can be high in the lower respiratory tract. Inflammatory signaling molecules are released by infected cells and alveolar macrophages in addition to recruited T lymphocytes, monocytes, and neutrophils. In the late stage, pulmonary edema can fill the alveolar spaces with hyaline membrane formation, compatible with early-phase acute respiratory distress syndrome.

A, Transverse thin-section computed tomographic scan of a 76-year-old man, 5 days after symptom onset, showing subpleural ground-glass opacity and consolidation with subpleural sparing. B, Transverse thin-section computed tomographic scan of a 76-year-old man, 21 days after symptom onset, showing bilateral and peripheral predominant consolidation, ground-glass with reticulation, and bronchodilatation. C, Pathological manifestations of lung tissue in a patient with severe pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) showing interstitial mononuclear inflammatory infiltrates dominated by lymphocytes (magnification, ×10). D, Pathological manifestations of lung tissue in a patient with severe pneumonia caused by SARS-CoV-2 showing diffuse alveolar damage with edema and fibrine deposition, indicating acute respiratory distress syndrome with early fibrosis (magnification, ×10). Images courtesy of Inge A. H. van den Berk, MD (Department of Radiology, Amsterdam UMC), and Bernadette Schurink, MD (Department of Pathology, Amsterdam UMC).

Eric Topol, MD, Scripps Research EVP and omnivorous science health care and tech commentator, discusses the evolving COVID-19 pandemic. Recorded July 23, 2020.

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• Strongyloides Hyperinfection Risk in COVID-19 Patients Treated With Dexamethasone JAMA Viewpoint August 18, 2020 Anticipating widespread global use of dexamethasone for COVID-19 in the wake of RECOVERY trial findings, this Viewpoint summarizes the theoretical risk of triggering Strongyloides hyperinfection/dissemination syndrome in people with asymptomatic strongyloidiasis, and proposes an algorithm to for assessing and managing the risk in outpatient and hospital settings. William M. Stauffer, MD, MSPH; Jonathan D. Alpern, MD; Patricia F. Walker, MD, DTM&H
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Wiersinga WJ , Rhodes A , Cheng AC , Peacock SJ , Prescott HC. Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19) : A Review . JAMA. 2020;324(8):782–793. doi:10.1001/jama.2020.12839

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Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19) : A Review

• 1 Division of Infectious Diseases, Department of Medicine, Amsterdam UMC, location AMC, University of Amsterdam, Amsterdam, the Netherlands
• 2 Center for Experimental and Molecular Medicine (CEMM), Amsterdam UMC, location AMC, University of Amsterdam, Amsterdam, the Netherlands
• 3 Department of Intensive Care Medicine, St George's University Hospitals Foundation Trust, London, United Kingdom
• 4 Infection Prevention and Healthcare Epidemiology Unit, Alfred Health, Melbourne, Australia
• 5 School of Public Health and Preventive Medicine, Monash University, Monash University, Melbourne, Australia
• 6 National Infection Service, Public Health England, London, United Kingdom
• 7 Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
• 8 Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor
• 9 VA Center for Clinical Management Research, Ann Arbor, Michigan
• Review Pharmacologic Treatments for Coronavirus Disease 2019 (COVID-19) James M. Sanders, PhD, PharmD; Marguerite L. Monogue, PharmD; Tomasz Z. Jodlowski, PharmD; James B. Cutrell, MD JAMA
• Viewpoint Ensuring Scientific Integrity and Public Confidence in the Search for Effective COVID-19 Treatment Jesse L. Goodman, MD, MPH; Luciana Borio, MD JAMA
• Viewpoint Monoclonal Antibodies for Prevention and Treatment of COVID-19 Mary Marovich, MD; John R. Mascola, MD; Myron S. Cohen, MD JAMA
• Preliminary Communication Presence of Genetic Variants Among Young Men With Severe COVID-19 Caspar I. van der Made, MD; Annet Simons, PhD; Janneke Schuurs-Hoeijmakers, MD, PhD; Guus van den Heuvel, MD; Tuomo Mantere, PhD; Simone Kersten, MSc; Rosanne C. van Deuren, MSc; Marloes Steehouwer, BSc; Simon V. van Reijmersdal, BSc; Martin Jaeger, PhD; Tom Hofste, BSc; Galuh Astuti, PhD; Jordi Corominas Galbany, PhD; Vyne van der Schoot, MD, PhD; Hans van der Hoeven, MD, PhD; Wanda Hagmolen of ten Have, MD, PhD; Eva Klijn, MD, PhD; Catrien van den Meer, MD; Jeroen Fiddelaers, MD; Quirijn de Mast, MD, PhD; Chantal P. Bleeker-Rovers, MD, PhD; Leo A. B. Joosten, PhD; Helger G. Yntema, PhD; Christian Gilissen, PhD; Marcel Nelen, PhD; Jos W. M. van der Meer, MD, PhD; Han G. Brunner, MD, PhD; Mihai G. Netea, MD, PhD; Frank L. van de Veerdonk, MD, PhD; Alexander Hoischen, PhD JAMA
• Viewpoint Strongyloides Hyperinfection Risk in COVID-19 Patients Treated With Dexamethasone William M. Stauffer, MD, MSPH; Jonathan D. Alpern, MD; Patricia F. Walker, MD, DTM&H JAMA
• JAMA Patient Page Patient Information: COVID-19 W. Joost Wiersinga, MD, PhD, MBA; Hallie C. Prescott, MD, MSc JAMA
• Research Letter Cytokine Levels in Critically Ill Patients With COVID-19 and Other Conditions Matthijs Kox, PhD; Nicole J. B. Waalders, BSc; Emma J. Kooistra, BSc; Jelle Gerretsen, BSc; Peter Pickkers, MD, PhD JAMA
• Research Letter Racial/Ethnic Variation in Nasal Transmembrane Serine Protease 2 ( TMPRSS2 ) Gene Expression Facilitating Coronavirus Entry Supinda Bunyavanich, MD, MPH, MPhil; Chantal Grant, MD; Alfin Vicencio, MD JAMA
• Viewpoint Therapy for Early COVID-19—A Critical Need Peter S. Kim, MD; Sarah W. Read, MD, MHS; Anthony S. Fauci, MD JAMA

Importance   The coronavirus disease 2019 (COVID-19) pandemic, due to the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a worldwide sudden and substantial increase in hospitalizations for pneumonia with multiorgan disease. This review discusses current evidence regarding the pathophysiology, transmission, diagnosis, and management of COVID-19.

Observations   SARS-CoV-2 is spread primarily via respiratory droplets during close face-to-face contact. Infection can be spread by asymptomatic, presymptomatic, and symptomatic carriers. The average time from exposure to symptom onset is 5 days, and 97.5% of people who develop symptoms do so within 11.5 days. The most common symptoms are fever, dry cough, and shortness of breath. Radiographic and laboratory abnormalities, such as lymphopenia and elevated lactate dehydrogenase, are common, but nonspecific. Diagnosis is made by detection of SARS-CoV-2 via reverse transcription polymerase chain reaction testing, although false-negative test results may occur in up to 20% to 67% of patients; however, this is dependent on the quality and timing of testing. Manifestations of COVID-19 include asymptomatic carriers and fulminant disease characterized by sepsis and acute respiratory failure. Approximately 5% of patients with COVID-19, and 20% of those hospitalized, experience severe symptoms necessitating intensive care. More than 75% of patients hospitalized with COVID-19 require supplemental oxygen. Treatment for individuals with COVID-19 includes best practices for supportive management of acute hypoxic respiratory failure. Emerging data indicate that dexamethasone therapy reduces 28-day mortality in patients requiring supplemental oxygen compared with usual care (21.6% vs 24.6%; age-adjusted rate ratio, 0.83 [95% CI, 0.74-0.92]) and that remdesivir improves time to recovery (hospital discharge or no supplemental oxygen requirement) from 15 to 11 days. In a randomized trial of 103 patients with COVID-19, convalescent plasma did not shorten time to recovery. Ongoing trials are testing antiviral therapies, immune modulators, and anticoagulants. The case-fatality rate for COVID-19 varies markedly by age, ranging from 0.3 deaths per 1000 cases among patients aged 5 to 17 years to 304.9 deaths per 1000 cases among patients aged 85 years or older in the US. Among patients hospitalized in the intensive care unit, the case fatality is up to 40%. At least 120 SARS-CoV-2 vaccines are under development. Until an effective vaccine is available, the primary methods to reduce spread are face masks, social distancing, and contact tracing. Monoclonal antibodies and hyperimmune globulin may provide additional preventive strategies.

Conclusions and Relevance   As of July 1, 2020, more than 10 million people worldwide had been infected with SARS-CoV-2. Many aspects of transmission, infection, and treatment remain unclear. Advances in prevention and effective management of COVID-19 will require basic and clinical investigation and public health and clinical interventions.

The coronavirus disease 2019 (COVID-19) pandemic has caused a sudden significant increase in hospitalizations for pneumonia with multiorgan disease. COVID-19 is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 infection may be asymptomatic or it may cause a wide spectrum of symptoms, such as mild symptoms of upper respiratory tract infection and life-threatening sepsis. COVID-19 first emerged in December 2019, when a cluster of patients with pneumonia of unknown cause was recognized in Wuhan, China. As of July 1, 2020, SARS-CoV-2 has affected more than 200 countries, resulting in more than 10 million identified cases with 508 000 confirmed deaths ( Figure 1 ). This review summarizes current evidence regarding pathophysiology, transmission, diagnosis, and management of COVID-19.

We searched PubMed, LitCovid, and MedRxiv using the search terms coronavirus , severe acute respiratory syndrome coronavirus 2 , 2019-nCoV , SARS-CoV-2 , SARS-CoV , MERS-CoV , and COVID-19 for studies published from January 1, 2002, to June 15, 2020, and manually searched the references of select articles for additional relevant articles. Ongoing or completed clinical trials were identified using the disease search term coronavirus infection on ClinicalTrials.gov, the Chinese Clinical Trial Registry, and the International Clinical Trials Registry Platform. We selected articles relevant to a general medicine readership, prioritizing randomized clinical trials, systematic reviews, and clinical practice guidelines.

Coronaviruses are large, enveloped, single-stranded RNA viruses found in humans and other mammals, such as dogs, cats, chicken, cattle, pigs, and birds. Coronaviruses cause respiratory, gastrointestinal, and neurological disease. The most common coronaviruses in clinical practice are 229E, OC43, NL63, and HKU1, which typically cause common cold symptoms in immunocompetent individuals. SARS-CoV-2 is the third coronavirus that has caused severe disease in humans to spread globally in the past 2 decades. 1 The first coronavirus that caused severe disease was severe acute respiratory syndrome (SARS), which was thought to originate in Foshan, China, and resulted in the 2002-2003 SARS-CoV pandemic. 2 The second was the coronavirus-caused Middle East respiratory syndrome (MERS), which originated from the Arabian peninsula in 2012. 3

SARS-CoV-2 has a diameter of 60 nm to 140 nm and distinctive spikes, ranging from 9 nm to 12 nm, giving the virions the appearance of a solar corona ( Figure 2 ). 4 Through genetic recombination and variation, coronaviruses can adapt to and infect new hosts. Bats are thought to be a natural reservoir for SARS-CoV-2, but it has been suggested that humans became infected with SARS-CoV-2 via an intermediate host, such as the pangolin. 5 , 6

Early in infection, SARS-CoV-2 targets cells, such as nasal and bronchial epithelial cells and pneumocytes, through the viral structural spike (S) protein that binds to the angiotensin-converting enzyme 2 (ACE2) receptor 7 ( Figure 2 ). The type 2 transmembrane serine protease (TMPRSS2), present in the host cell, promotes viral uptake by cleaving ACE2 and activating the SARS-CoV-2 S protein, which mediates coronavirus entry into host cells. 7 ACE2 and TMPRSS2 are expressed in host target cells, particularly alveolar epithelial type II cells. 8 , 9 Similar to other respiratory viral diseases, such as influenza, profound lymphopenia may occur in individuals with COVID-19 when SARS-CoV-2 infects and kills T lymphocyte cells. In addition, the viral inflammatory response, consisting of both the innate and the adaptive immune response (comprising humoral and cell-mediated immunity), impairs lymphopoiesis and increases lymphocyte apoptosis. Although upregulation of ACE2 receptors from ACE inhibitor and angiotensin receptor blocker medications has been hypothesized to increase susceptibility to SARS-CoV-2 infection, large observational cohorts have not found an association between these medications and risk of infection or hospital mortality due to COVID-19. 10 , 11 For example, in a study 4480 patients with COVID-19 from Denmark, previous treatment with ACE inhibitors or angiotensin receptor blockers was not associated with mortality. 11

In later stages of infection, when viral replication accelerates, epithelial-endothelial barrier integrity is compromised. In addition to epithelial cells, SARS-CoV-2 infects pulmonary capillary endothelial cells, accentuating the inflammatory response and triggering an influx of monocytes and neutrophils. Autopsy studies have shown diffuse thickening of the alveolar wall with mononuclear cells and macrophages infiltrating airspaces in addition to endothelialitis. 12 Interstitial mononuclear inflammatory infiltrates and edema develop and appear as ground-glass opacities on computed tomographic imaging. Pulmonary edema filling the alveolar spaces with hyaline membrane formation follows, compatible with early-phase acute respiratory distress syndrome (ARDS). 12 Bradykinin-dependent lung angioedema may contribute to disease. 13 Collectively, endothelial barrier disruption, dysfunctional alveolar-capillary oxygen transmission, and impaired oxygen diffusion capacity are characteristic features of COVID-19.

In severe COVID-19, fulminant activation of coagulation and consumption of clotting factors occur. 14 , 15 A report from Wuhan, China, indicated that 71% of 183 individuals who died of COVID-19 met criteria for diffuse intravascular coagulation. 14 Inflamed lung tissues and pulmonary endothelial cells may result in microthrombi formation and contribute to the high incidence of thrombotic complications, such as deep venous thrombosis, pulmonary embolism, and thrombotic arterial complications (eg, limb ischemia, ischemic stroke, myocardial infarction) in critically ill patients. 16 The development of viral sepsis, defined as life-threatening organ dysfunction caused by a dysregulated host response to infection, may further contribute to multiorgan failure.

Epidemiologic data suggest that droplets expelled during face-to-face exposure during talking, coughing, or sneezing is the most common mode of transmission ( Box 1 ). Prolonged exposure to an infected person (being within 6 feet for at least 15 minutes) and briefer exposures to individuals who are symptomatic (eg, coughing) are associated with higher risk for transmission, while brief exposures to asymptomatic contacts are less likely to result in transmission. 25 Contact surface spread (touching a surface with virus on it) is another possible mode of transmission. Transmission may also occur via aerosols (smaller droplets that remain suspended in air), but it is unclear if this is a significant source of infection in humans outside of a laboratory setting. 26 , 27 The existence of aerosols in physiological states (eg, coughing) or the detection of nucleic acid in the air does not mean that small airborne particles are infectious. 28 Maternal COVID-19 is currently believed to be associated with low risk for vertical transmission. In most reported series, the mothers' infection with SARS-CoV-2 occurred in the third trimester of pregnancy, with no maternal deaths and a favorable clinical course in the neonates. 29 - 31

Transmission, Symptoms, and Complications of Coronavirus Disease 2019 (COVID-19)

Transmission 17 of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurs primarily via respiratory droplets from face-to-face contact and, to a lesser degree, via contaminated surfaces. Aerosol spread may occur, but the role of aerosol spread in humans remains unclear. An estimated 48% to 62% of transmission may occur via presymptomatic carriers.

Common symptoms 18 in hospitalized patients include fever (70%-90%), dry cough (60%-86%), shortness of breath (53%-80%), fatigue (38%), myalgias (15%-44%), nausea/vomiting or diarrhea (15%-39%), headache, weakness (25%), and rhinorrhea (7%). Anosmia or ageusia may be the sole presenting symptom in approximately 3% of individuals with COVID-19.

Common laboratory abnormalities 19 among hospitalized patients include lymphopenia (83%), elevated inflammatory markers (eg, erythrocyte sedimentation rate, C-reactive protein, ferritin, tumor necrosis factor-α, IL-1, IL-6), and abnormal coagulation parameters (eg, prolonged prothrombin time, thrombocytopenia, elevated D-dimer [46% of patients], low fibrinogen).

Common radiographic findings of individuals with COVID-19 include bilateral, lower-lobe predominate infiltrates on chest radiographic imaging and bilateral, peripheral, lower-lobe ground-glass opacities and/or consolidation on chest computed tomographic imaging.

Common complications 18 , 20 - 24 among hospitalized patients with COVID-19 include pneumonia (75%); acute respiratory distress syndrome (15%); acute liver injury, characterized by elevations in aspartate transaminase, alanine transaminase, and bilirubin (19%); cardiac injury, including troponin elevation (7%-17%), acute heart failure, dysrhythmias, and myocarditis; prothrombotic coagulopathy resulting in venous and arterial thromboembolic events (10%-25%); acute kidney injury (9%); neurologic manifestations, including impaired consciousness (8%) and acute cerebrovascular disease (3%); and shock (6%).

Rare complications among critically ill patients with COVID-19 include cytokine storm and macrophage activation syndrome (ie, secondary hemophagocytic lymphohistiocytosis).

The clinical significance of SARS-CoV-2 transmission from inanimate surfaces is difficult to interpret without knowing the minimum dose of virus particles that can initiate infection. Viral load appears to persist at higher levels on impermeable surfaces, such as stainless steel and plastic, than permeable surfaces, such as cardboard. 32 Virus has been identified on impermeable surfaces for up to 3 to 4 days after inoculation. 32 Widespread viral contamination of hospital rooms has been documented. 28 However, it is thought that the amount of virus detected on surfaces decays rapidly within 48 to 72 hours. 32 Although the detection of virus on surfaces reinforces the potential for transmission via fomites (objects such as a doorknob, cutlery, or clothing that may be contaminated with SARS-CoV-2) and the need for adequate environmental hygiene, droplet spread via face-to-face contact remains the primary mode of transmission.

Viral load in the upper respiratory tract appears to peak around the time of symptom onset and viral shedding begins approximately 2 to 3 days prior to the onset of symptoms. 33 Asymptomatic and presymptomatic carriers can transmit SARS-CoV-2. 34 , 35 In Singapore, presymptomatic transmission has been described in clusters of patients with close contact (eg, through churchgoing or singing class) approximately 1 to 3 days before the source patient developed symptoms. 34 Presymptomatic transmission is thought to be a major contributor to the spread of SARS-CoV-2. Modeling studies from China and Singapore estimated the percentage of infections transmitted from a presymptomatic individual as 48% to 62%. 17 Pharyngeal shedding is high during the first week of infection at a time in which symptoms are still mild, which might explain the efficient transmission of SARS-CoV-2, because infected individuals can be infectious before they realize they are ill. 36 Although studies have described rates of asymptomatic infection, ranging from 4% to 32%, it is unclear whether these reports represent truly asymptomatic infection by individuals who never develop symptoms, transmission by individuals with very mild symptoms, or transmission by individuals who are asymptomatic at the time of transmission but subsequently develop symptoms. 37 - 39 A systematic review on this topic suggested that true asymptomatic infection is probably uncommon. 38

Although viral nucleic acid can be detectable in throat swabs for up to 6 weeks after the onset of illness, several studies suggest that viral cultures are generally negative for SARS-CoV-2 8 days after symptom onset. 33 , 36 , 40 This is supported by epidemiological studies that have shown that transmission did not occur to contacts whose exposure to the index case started more than 5 days after the onset of symptoms in the index case. 41 This suggests that individuals can be released from isolation based on clinical improvement. The Centers for Disease Control and Prevention recommend isolating for at least 10 days after symptom onset and 3 days after improvement of symptoms. 42 However, there remains uncertainty about whether serial testing is required for specific subgroups, such as immunosuppressed patients or critically ill patients for whom symptom resolution may be delayed or older adults residing in short- or long-term care facilities.

The mean (interquartile range) incubation period (the time from exposure to symptom onset) for COVID-19 is approximately 5 (2-7) days. 43 , 44 Approximately 97.5% of individuals who develop symptoms will do so within 11.5 days of infection. 43 The median (interquartile range) interval from symptom onset to hospital admission is 7 (3-9) days. 45 The median age of hospitalized patients varies between 47 and 73 years, with most cohorts having a male preponderance of approximately 60%. 44 , 46 , 47 Among patients hospitalized with COVID-19, 74% to 86% are aged at least 50 years. 45 , 47

COVID-19 has various clinical manifestations ( Box 1 and Box 2 ). In a study of 44 672 patients with COVID-19 in China, 81% of patients had mild manifestations, 14% had severe manifestations, and 5% had critical manifestations (defined by respiratory failure, septic shock, and/or multiple organ dysfunction). 48 A study of 20 133 individuals hospitalized with COVID-19 in the UK reported that 17.1% were admitted to high-dependency or intensive care units (ICUs). 47

Commonly Asked Questions About Coronavirus Disease 2019 (COVID-19)

How is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) most commonly transmitted?

SARS-CoV-2 is most commonly spread via respiratory droplets (eg, from coughing, sneezing, shouting) during face-to-face exposure or by surface contamination.

What are the most common symptoms of COVID-19?

The 3 most common symptoms are fever, cough, and shortness of breath. Additional symptoms include weakness, fatigue, nausea, vomiting, diarrhea, changes to taste and smell.

How is the diagnosis made?

Diagnosis of COVID-19 is typically made by polymerase chain reaction testing of a nasopharyngeal swab. However, given the possibility of false-negative test results, clinical, laboratory, and imaging findings may also be used to make a presumptive diagnosis for individuals for whom there is a high index of clinical suspicion of infection.

What are current evidence-based treatments for individuals with COVID-19?

Supportive care, including supplemental oxygen, is the main treatment for most patients. Recent trials indicate that dexamethasone decreases mortality (subgroup analysis suggests benefit is limited to patients who require supplemental oxygen and who have symptoms for >7 d) and remdesivir improves time to recovery (subgroup analysis suggests benefit is limited to patients not receiving mechanical ventilation).

What percentage of people are asymptomatic carriers, and how important are they in transmitting the disease?

True asymptomatic infection is believed to be uncommon. The average time from exposure to symptoms onset is 5 days, and up to 62% of transmission may occur prior to the onset of symptoms.

Are masks effective at preventing spread?

Yes. Face masks reduce the spread of viral respiratory infection. N95 respirators and surgical masks both provide substantial protection (compared with no mask), and surgical masks provide greater protection than cloth masks. However, physical distancing is also associated with substantial reduction of viral transmission, with greater distances providing greater protection. Additional measures such as hand and environmental disinfection are also important.

Although only approximately 25% of infected patients have comorbidities, 60% to 90% of hospitalized infected patients have comorbidities. 45 - 49 The most common comorbidities in hospitalized patients include hypertension (present in 48%-57% of patients), diabetes (17%-34%), cardiovascular disease (21%-28%), chronic pulmonary disease (4%-10%), chronic kidney disease (3%-13%), malignancy (6%-8%), and chronic liver disease (<5%). 45 , 46 , 49

The most common symptoms in hospitalized patients are fever (up to 90% of patients), dry cough (60%-86%), shortness of breath (53%-80%), fatigue (38%), nausea/vomiting or diarrhea (15%-39%), and myalgia (15%-44%). 18 , 44 - 47 , 49 , 50 Patients can also present with nonclassical symptoms, such as isolated gastrointestinal symptoms. 18 Olfactory and/or gustatory dysfunctions have been reported in 64% to 80% of patients. 51 - 53 Anosmia or ageusia may be the sole presenting symptom in approximately 3% of patients. 53

Complications of COVID-19 include impaired function of the heart, brain, lung, liver, kidney, and coagulation system. COVID-19 can lead to myocarditis, cardiomyopathy, ventricular arrhythmias, and hemodynamic instability. 20 , 54 Acute cerebrovascular disease and encephalitis are observed with severe illness (in up to 8% of patients). 21 , 52 Venous and arterial thromboembolic events occur in 10% to 25% in hospitalized patients with COVID-19. 19 , 22 In the ICU, venous and arterial thromboembolic events may occur in up to 31% to 59% of patients with COVID-19. 16 , 22

Approximately 17% to 35% of hospitalized patients with COVID-19 are treated in an ICU, most commonly due to hypoxemic respiratory failure. Among patients in the ICU with COVID-19, 29% to 91% require invasive mechanical ventilation. 47 , 49 , 55 , 56 In addition to respiratory failure, hospitalized patients may develop acute kidney injury (9%), liver dysfunction (19%), bleeding and coagulation dysfunction (10%-25%), and septic shock (6%). 18 , 19 , 23 , 49 , 56

Approximately 2% to 5% of individuals with laboratory-confirmed COVID-19 are younger than 18 years, with a median age of 11 years. Children with COVID-19 have milder symptoms that are predominantly limited to the upper respiratory tract, and rarely require hospitalization. It is unclear why children are less susceptible to COVID-19. Potential explanations include that children have less robust immune responses (ie, no cytokine storm), partial immunity from other viral exposures, and lower rates of exposure to SARS-CoV-2. Although most pediatric cases are mild, a small percentage (<7%) of children admitted to the hospital for COVID-19 develop severe disease requiring mechanical ventilation. 57 A rare multisystem inflammatory syndrome similar to Kawasaki disease has recently been described in children in Europe and North America with SARS-CoV-2 infection. 58 , 59 This multisystem inflammatory syndrome in children is uncommon (2 in 100 000 persons aged <21 years). 60

Diagnosis of COVID-19 is typically made using polymerase chain reaction testing via nasal swab ( Box 2 ). However, because of false-negative test result rates of SARS-CoV-2 PCR testing of nasal swabs, clinical, laboratory, and imaging findings may also be used to make a presumptive diagnosis.

Reverse transcription polymerase chain reaction–based SARS-CoV-2 RNA detection from respiratory samples (eg, nasopharynx) is the standard for diagnosis. However, the sensitivity of testing varies with timing of testing relative to exposure. One modeling study estimated sensitivity at 33% 4 days after exposure, 62% on the day of symptom onset, and 80% 3 days after symptom onset. 61 - 63 Factors contributing to false-negative test results include the adequacy of the specimen collection technique, time from exposure, and specimen source. Lower respiratory samples, such as bronchoalveolar lavage fluid, are more sensitive than upper respiratory samples. Among 1070 specimens collected from 205 patients with COVID-19 in China, bronchoalveolar lavage fluid specimens had the highest positive rates of SARS-CoV-2 PCR testing results (93%), followed by sputum (72%), nasal swabs (63%), and pharyngeal swabs (32%). 61 SARS-CoV-2 can also be detected in feces, but not in urine. 61 Saliva may be an alternative specimen source that requires less personal protective equipment and fewer swabs, but requires further validation. 64

Several serological tests can also aid in the diagnosis and measurement of responses to novel vaccines. 62 , 65 , 66 However, the presence of antibodies may not confer immunity because not all antibodies produced in response to infection are neutralizing. Whether and how frequently second infections with SARS-CoV-2 occur remain unknown. Whether presence of antibody changes susceptibility to subsequent infection or how long antibody protection lasts are unknown. IgM antibodies are detectable within 5 days of infection, with higher IgM levels during weeks 2 to 3 of illness, while an IgG response is first seen approximately 14 days after symptom onset. 62 , 65 Higher antibody titers occur with more severe disease. 66 Available serological assays include point-of-care assays and high throughput enzyme immunoassays. However, test performance, accuracy, and validity are variable. 67

A systematic review of 19 studies of 2874 patients who were mostly from China (mean age, 52 years), of whom 88% were hospitalized, reported the typical range of laboratory abnormalities seen in COVID-19, including elevated serum C-reactive protein (increased in >60% of patients), lactate dehydrogenase (increased in approximately 50%-60%), alanine aminotransferase (elevated in approximately 25%), and aspartate aminotransferase (approximately 33%). 24 Approximately 75% of patients had low albumin. 24 The most common hematological abnormality is lymphopenia (absolute lymphocyte count <1.0 × 10 9 /L), which is present in up to 83% of hospitalized patients with COVID-19. 44 , 50 In conjunction with coagulopathy, modest prolongation of prothrombin times (prolonged in >5% of patients), mild thrombocytopenia (present in approximately 30% of patients) and elevated D-dimer values (present in 43%-60% of patients) are common. 14 , 15 , 19 , 44 , 68 However, most of these laboratory characteristics are nonspecific and are common in pneumonia. More severe laboratory abnormalities have been associated with more severe infection. 44 , 50 , 69 D-dimer and, to a lesser extent, lymphopenia seem to have the largest prognostic associations. 69

The characteristic chest computed tomographic imaging abnormalities for COVID-19 are diffuse, peripheral ground-glass opacities ( Figure 3 ). 70 Ground-glass opacities have ill-defined margins, air bronchograms, smooth or irregular interlobular or septal thickening, and thickening of the adjacent pleura. 70 Early in the disease, chest computed tomographic imaging findings in approximately 15% of individuals and chest radiograph findings in approximately 40% of individuals can be normal. 44 Rapid evolution of abnormalities can occur in the first 2 weeks after symptom onset, after which they subside gradually. 70 , 71

Chest computed tomographic imaging findings are nonspecific and overlap with other infections, so the diagnostic value of chest computed tomographic imaging for COVID-19 is limited. Some patients admitted to the hospital with polymerase chain reaction testing–confirmed SARS-CoV-2 infection have normal computed tomographic imaging findings, while abnormal chest computed tomographic imaging findings compatible with COVID-19 occur days before detection of SARS-CoV-2 RNA in other patients. 70 , 71

Currently, best practices for supportive management of acute hypoxic respiratory failure and ARDS should be followed. 72 - 74 Evidence-based guideline initiatives have been established by many countries and professional societies, 72 - 74 including guidelines that are updated regularly by the National Institutes of Health. 74

More than 75% of patients hospitalized with COVID-19 require supplemental oxygen therapy. For patients who are unresponsive to conventional oxygen therapy, heated high-flow nasal canula oxygen may be administered. 72 For patients requiring invasive mechanical ventilation, lung-protective ventilation with low tidal volumes (4-8 mL/kg, predicted body weight) and plateau pressure less than 30 mg Hg is recommended. 72 Additionally, prone positioning, a higher positive end-expiratory pressure strategy, and short-term neuromuscular blockade with cisatracurium or other muscle relaxants may facilitate oxygenation. Although some patients with COVID-19–related respiratory failure have high lung compliance, 75 they are still likely to benefit from lung-protective ventilation. 76 Cohorts of patients with ARDS have displayed similar heterogeneity in lung compliance, and even patients with greater compliance have shown benefit from lower tidal volume strategies. 76

The threshold for intubation in COVID-19–related respiratory failure is controversial, because many patients have normal work of breathing but severe hypoxemia. 77 “Earlier” intubation allows time for a more controlled intubation process, which is important given the logistical challenges of moving patients to an airborne isolation room and donning personal protective equipment prior to intubation. However, hypoxemia in the absence of respiratory distress is well tolerated, and patients may do well without mechanical ventilation. Earlier intubation thresholds may result in treating some patients with mechanical ventilation unnecessarily and exposing them to additional complications. Currently, insufficient evidence exists to make recommendations regarding earlier vs later intubation.

In observational studies, approximately 8% of hospitalized patients with COVID-19 experience a bacterial or fungal co-infection, but up to 72% are treated with broad-spectrum antibiotics. 78 Awaiting further data, it may be prudent to withhold antibacterial drugs in patients with COVID-19 and reserve them for those who present with radiological findings and/or inflammatory markers compatible with co-infection or who are immunocompromised and/or critically ill. 72

The following classes of drugs are being evaluated or developed for the management of COVID-19: antivirals (eg, remdesivir, favipiravir), antibodies (eg, convalescent plasma, hyperimmune immunoglobulins), anti-inflammatory agents (dexamethasone, statins), targeted immunomodulatory therapies (eg, tocilizumab, sarilumab, anakinra, ruxolitinib), anticoagulants (eg, heparin), and antifibrotics (eg, tyrosine kinase inhibitors). It is likely that different treatment modalities might have different efficacies at different stages of illness and in different manifestations of disease. Viral inhibition would be expected to be most effective early in infection, while, in hospitalized patients, immunomodulatory agents may be useful to prevent disease progression and anticoagulants may be useful to prevent thromboembolic complications.

More than 200 trials of chloroquine/hydroxychloroquine, compounds that inhibit viral entry and endocytosis of SARS-CoV-2 in vitro and may have beneficial immunomodulatory effects in vivo, 79 , 80 have been initiated, but early data from clinical trials in hospitalized patients with COVID-19 have not demonstrated clear benefit. 81 - 83 A clinical trial of 150 patients in China admitted to the hospital for mild to moderate COVID-19 did not find an effect on negative conversion of SARS-CoV-2 by 28 days (the main outcome measure) when compared with standard of care alone. 83 Two retrospective studies found no effect of hydroxychloroquine on risk of intubation or mortality among patients hospitalized for COVID-19. 84 , 85 One of these retrospective multicenter cohort studies compared in-hospital mortality between those treated with hydroxychloroquine plus azithromycin (735 patients), hydroxychloroquine alone (271 patients), azithromycin alone (211 patients), and neither drug (221 patients), but reported no differences across the groups. 84 Adverse effects are common, most notably QT prolongation with an increased risk of cardiac complications in an already vulnerable population. 82 , 84 These findings do not support off-label use of (hydroxy)chloroquine either with or without the coadministration of azithromycin. Randomized clinical trials are ongoing and should provide more guidance.

Most antiviral drugs undergoing clinical testing in patients with COVID-19 are repurposed antiviral agents originally developed against influenza, HIV, Ebola, or SARS/MERS. 79 , 86 Use of the protease inhibitor lopinavir-ritonavir, which disrupts viral replication in vitro, did not show benefit when compared with standard care in a randomized, controlled, open-label trial of 199 hospitalized adult patients with severe COVID-19. 87 Among the RNA-dependent RNA polymerase inhibitors, which halt SARS-CoV-2 replication, being evaluated, including ribavirin, favipiravir, and remdesivir, the latter seems to be the most promising. 79 , 88 The first preliminary results of a double-blind, randomized, placebo-controlled trial of 1063 adults hospitalized with COVID-19 and evidence of lower respiratory tract involvement who were randomly assigned to receive intravenous remdesivir or placebo for up to 10 days demonstrated that patients randomized to receive remdesivir had a shorter time to recovery than patients in the placebo group (11 vs 15 days). 88 A separate randomized, open-label trial among 397 hospitalized patients with COVID-19 who did not require mechanical ventilation reported that 5 days of treatment with remdesivir was not different than 10 days in terms of clinical status on day 14. 89 The effect of remdesivir on survival remains unknown.

Treatment with plasma obtained from patients who have recovered from viral infections was first reported during the 1918 flu pandemic. A first report of 5 critically ill patients with COVID-19 treated with convalescent plasma containing neutralizing antibody showed improvement in clinical status among all participants, defined as a combination of changes of body temperature, Sequential Organ Failure Assessment score, partial pressure of oxygen/fraction of inspired oxygen, viral load, serum antibody titer, routine blood biochemical index, ARDS, and ventilatory and extracorporeal membrane oxygenation supports before and after convalescent plasma transfusion status. 90 However, a subsequent multicenter, open-label, randomized clinical trial of 103 patients in China with severe COVID-19 found no statistical difference in time to clinical improvement within 28 days among patients randomized to receive convalescent plasma vs standard treatment alone (51.9% vs 43.1%). 91 However, the trial was stopped early because of slowing enrollment, which limited the power to detect a clinically important difference. Alternative approaches being studied include the use of convalescent plasma-derived hyperimmune globulin and monoclonal antibodies targeting SARS-CoV-2. 92 , 93

Alternative therapeutic strategies consist of modulating the inflammatory response in patients with COVID-19. Monoclonal antibodies directed against key inflammatory mediators, such as interferon gamma, interleukin 1, interleukin 6, and complement factor 5a, all target the overwhelming inflammatory response following SARS-CoV-2 infection with the goal of preventing organ damage. 79 , 86 , 94 Of these, the interleukin 6 inhibitors tocilizumab and sarilumab are best studied, with more than a dozen randomized clinical trials underway. 94 Tyrosine kinase inhibitors, such as imatinib, are studied for their potential to prevent pulmonary vascular leakage in individuals with COVID-19.

Studies of corticosteroids for viral pneumonia and ARDS have yielded mixed results. 72 , 73 However, the Randomized Evaluation of COVID-19 Therapy (RECOVERY) trial, which randomized 2104 patients with COVID-19 to receive 6 mg daily of dexamethasone for up to 10 days and 4321 to receive usual care, found that dexamethasone reduced 28-day all-cause mortality (21.6% vs 24.6%; age-adjusted rate ratio, 0.83 [95% CI, 0.74-0.92]; P  < .001). 95 The benefit was greatest in patients with symptoms for more than 7 days and patients who required mechanical ventilation. By contrast, there was no benefit (and possibility for harm) among patients with shorter symptom duration and no supplemental oxygen requirement. A retrospective cohort study of 201 patients in Wuhan, China, with confirmed COVID-19 pneumonia and ARDS reported that treatment with methylprednisolone was associated with reduced risk of death (hazard ratio, 0.38 [95% CI, 0.20-0.72]). 69

Thromboembolic prophylaxis with subcutaneous low molecular weight heparin is recommended for all hospitalized patients with COVID-19. 15 , 19 Studies are ongoing to assess whether certain patients (ie, those with elevated D-dimer) benefit from therapeutic anticoagulation.

A disproportionate percentage of COVID-19 hospitalizations and deaths occurs in lower-income and minority populations. 45 , 96 , 97 In a report by the Centers for Disease Control and Prevention of 580 hospitalized patients for whom race data were available, 33% were Black and 45% were White, while 18% of residents in the surrounding community were Black and 59% were White. 45 The disproportionate prevalence of COVID-19 among Black patients was separately reported in a retrospective cohort study of 3626 patients with COVID-19 from Louisiana, in which 77% of patients hospitalized with COVID-19 and 71% of patients who died of COVID-19 were Black, but Black individuals comprised only 31% of the area population. 97 , 98 This disproportionate burden may be a reflection of disparities in housing, transportation, employment, and health. Minority populations are more likely to live in densely populated communities or housing, depend on public transportation, or work in jobs for which telework was not possible (eg, bus driver, food service worker). Black individuals also have a higher prevalence of chronic health conditions than White individuals. 98 , 99

Overall hospital mortality from COVID-19 is approximately 15% to 20%, but up to 40% among patients requiring ICU admission. However, mortality rates vary across cohorts, reflecting differences in the completeness of testing and case identification, variable thresholds for hospitalization, and differences in outcomes. Hospital mortality ranges from less than 5% among patients younger than 40 years to 35% for patients aged 70 to 79 years and greater than 60% for patients aged 80 to 89 years. 46 Estimated overall death rates by age group per 1000 confirmed cases are provided in the Table . Because not all people who die during the pandemic are tested for COVID-19, actual numbers of deaths from COVID-19 are higher than reported numbers.

Although long-term outcomes from COVID-19 are currently unknown, patients with severe illness are likely to suffer substantial sequelae. Survival from sepsis is associated with increased risk for mortality for at least 2 years, new physical disability, new cognitive impairment, and increased vulnerability to recurrent infection and further health deterioration. Similar sequalae are likely to be seen in survivors of severe COVID-19. 100

COVID-19 is a potentially preventable disease. The relationship between the intensity of public health action and the control of transmission is clear from the epidemiology of infection around the world. 25 , 101 , 102 However, because most countries have implemented multiple infection control measures, it is difficult to determine the relative benefit of each. 103 , 104 This question is increasingly important because continued interventions will be required until effective vaccines or treatments become available. In general, these interventions can be divided into those consisting of personal actions (eg, physical distancing, personal hygiene, and use of protective equipment), case and contact identification (eg, test-trace-track-isolate, reactive school or workplace closure), regulatory actions (eg, governmental limits on sizes of gatherings or business capacity; stay-at-home orders; proactive school, workplace, and public transport closure or restriction; cordon sanitaire or internal border closures), and international border measures (eg, border closure or enforced quarantine). A key priority is to identify the combination of measures that minimizes societal and economic disruption while adequately controlling infection. Optimal measures may vary between countries based on resource limitations, geography (eg, island nations and international border measures), population, and political factors (eg, health literacy, trust in government, cultural and linguistic diversity).

The evidence underlying these public health interventions has not changed since the 1918 flu pandemic. 105 Mathematical modeling studies and empirical evidence support that public health interventions, including home quarantine after infection, restricting mass gatherings, travel restrictions, and social distancing, are associated with reduced rates of transmission. 101 , 102 , 106 Risk of resurgence follows when these interventions are lifted.

A human vaccine is currently not available for SARS-CoV-2, but approximately 120 candidates are under development. Approaches include the use of nucleic acids (DNA or RNA), inactivated or live attenuated virus, viral vectors, and recombinant proteins or virus particles. 107 , 108 Challenges to developing an effective vaccine consist of technical barriers (eg, whether S or receptor-binding domain proteins provoke more protective antibodies, prior exposure to adenovirus serotype 5 [which impairs immunogenicity in the viral vector vaccine], need for adjuvant), feasibility of large-scale production and regulation (eg, ensuring safety and effectiveness), and legal barriers (eg, technology transfer and licensure agreements). The SARS-CoV-2 S protein appears to be a promising immunogen for protection, but whether targeting the full-length protein or only the receptor-binding domain is sufficient to prevent transmission remains unclear. 108 Other considerations include the potential duration of immunity and thus the number of vaccine doses needed to confer immunity. 62 , 108 More than a dozen candidate SARS-CoV-2 vaccines are currently being tested in phase 1-3 trials.

Other approaches to prevention are likely to emerge in the coming months, including monoclonal antibodies, hyperimmune globulin, and convalscent titer. If proved effective, these approaches could be used in high-risk individuals, including health care workers, other essential workers, and older adults (particularly those in nursing homes or long-term care facilities).

This review has several limitations. First, information regarding SARS CoV-2 is limited. Second, information provided here is based on current evidence, but may be modified as more information becomes available. Third, few randomized trials have been published to guide management of COVID-19.

As of July 1, 2020, more than 10 million people worldwide had been infected with SARS-CoV-2. Many aspects of transmission, infection, and treatment remain unclear. Advances in prevention and effective management of COVID-19 will require basic and clinical investigation and public health and clinical interventions.

Accepted for Publication: June 30, 2020.

Corresponding Author: W. Joost Wiersinga, MD, PhD, Division of Infectious Diseases, Department of Medicine, Amsterdam UMC, location AMC, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands ( [email protected] ).

Published Online: July 10, 2020. doi:10.1001/jama.2020.12839

Conflict of Interest Disclosures: Dr Wiersinga is supported by the Netherlands Organisation of Scientific Research outside the submitted work. Dr Prescott reported receiving grants from the US Agency for Healthcare Research and Quality (HCP by R01 HS026725), the National Institutes of Health/National Institute of General Medical Sciences, and the US Department of Veterans Affairs outside the submitted work, being the sepsis physician lead for the Hospital Medicine Safety Continuous Quality Initiative funded by BlueCross/BlueShield of Michigan, and serving on the steering committee for MI-COVID-19, a Michigan statewide registry to improve care for patients with COVID-19 in Michigan. Dr Rhodes reported being the co-chair of the Surviving Sepsis Campaign. Dr Cheng reported being a member of Australian government advisory committees, including those involved in COVID-19. No other disclosures were reported.

Disclaimer: This article does not represent the views of the US Department of Veterans Affairs or the US government. This material is the result of work supported with resources and use of facilities at the Ann Arbor VA Medical Center. The opinions in this article do not necessarily represent those of the Australian government or advisory committees.

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REVIEW article

Coronavirus disease (covid-19): comprehensive review of clinical presentation.

• 1 Department of Medicine, King Edward Medical University/ Mayo Hospital, Lahore, Pakistan
• 2 Department of Anesthesia and Intensive Care, Post-Graduate Medical Institute/LGH, Lahore, Pakistan
• 3 Rajarshee Chhatrapati Shahu Maharaj Government Medical College, Kolhapur, India
• 4 Department of Medicine, Faculty of Medicine, University of Tlemcen, Tlemcen, Algeria
• 5 School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
• 6 Institute of Research and Development, Duy Tan University, Da Nang, Vietnam

COVID-19 is a rapidly growing pandemic with its first case identified during December 2019 in Wuhan, Hubei Province, China. Due to the rampant rise in the number of cases in China and globally, WHO declared COVID-19 as a pandemic on 11th March 2020. The disease is transmitted via respiratory droplets of infected patients during coughing or sneezing and affects primarily the lung parenchyma. The spectrum of clinical manifestations can be seen in COVID-19 patients ranging from asymptomatic infections to severe disease resulting in mortality. Although respiratory involvement is most common in COVID-19 patients, the virus can affect other organ systems as well. The systemic inflammation induced by the disease along with multisystem expression of Angiotensin Converting Enzyme 2 (ACE2), a receptor which allows viral entry into cells, explains the manifestation of extra-pulmonary symptoms affecting the gastrointestinal, cardiovascular, hematological, renal, musculoskeletal, and endocrine system. Here, we have reviewed the extensive literature available on COVID-19 about various clinical presentations based on the organ system involved as well as clinical presentation in specific population including children, pregnant women, and immunocompromised patients. We have also briefly discussed about the Multisystemic Inflammatory Syndrome occurring in children and adults with COVID-19. Understanding the various clinical presentations can help clinicians diagnose COVID-19 in an early stage and ensure appropriate measures to be undertaken in order to prevent further spread of the disease.

Introduction

COVID-19 is a growing pandemic with initial cases identified in Wuhan, Hubei province, China toward the end of December 2019. Labeled as Novel Coronavirus 2019 (2019-nCoV) initially by the Chinese Center for Disease Control and Prevention (CDC) which was subsequently renamed as Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) due to its homology with SARS-CoV by the International Committee on Taxonomy of Viruses (ICTV) ( 1 , 2 ). The World Health Organization (WHO) later renamed the disease caused by SARS-CoV-2 as Coronavirus Disease-2019 (COVID-19) ( 3 ). COVID-19 is primarily a disease of the respiratory system affecting lung parenchyma with fever, cough, and shortness of breath as the predominant symptoms. Recent studies have shown that it can affect multiple organ systems and cause development of extra-pulmonary symptoms. Presence of extra-pulmonary symptoms can often lead to late diagnosis and sometimes even mis-diagnosis of COVID-19 which can be detrimental to patients. As researchers globally continue to understand COVID-19 and its implications on the human body, knowledge about the various clinical presentations of COVID-19 is paramount in early diagnosing and treatment in order to decrease the morbidity and mortality caused by the disease.

Epidemiology and Pathophysiology

While studying the early transmission dynamics of COVID-19 outbreak in Wuhan, many cases were found to be linked to the Huanan wholesale seafood market. Further investigation revealed <10% of the total cases could be linked to the market which led to the conclusion of human-to-human transmission of the virus occurring through respiratory droplets and contact transmission contributing to the rise in the number of affected individuals ( 4 ). The exponential rise in the number of cases in China and reporting of cases outside China in multiple countries led WHO to declare COVID-19 as a pandemic on 11th March 2020 ( 5 ).

SARS-CoV-2 tends to infect all age groups and is transmitted via direct contact or respiratory droplets generated during coughing or sneezing by the infected patient during both symptomatic or pre-symptomatic phase of infection. Other routes of transmission include fecal-oral route and fomites along with small risk of vertical transmission from mother to child if infection occurs during third trimester of pregnancy ( 6 , 7 ). There has also been evidence of asymptomatic transmission of COVID-19 ( 8 ). The concept of super spreaders in relation to COVID-19 is emerging where a single individual either symptomatic or asymptomatic can infect a disproportionately large number of individuals in an appropriate super spreading conditions such as mass gathering due to production of large number of infectious agent for prolonged duration of time ( 9 ). As per the literature, the incubation period of COVID-19 ranges from 2 to 14 days with a mean incubation period of 3 days ( 10 ). The basic Reproduction number (Ro) of SARS-CoV-2 is 2–2.5. Each individual infected with COVID-19 can infect 2–2.5 other individuals in a naïve population which also explains the exponential growth in the number of cases ( 10 ). The disease tends to be of mild to moderate severity in roughly 80% of patients, and severe disease is associated with infants, elderly patients above 65 years, and patients with other comorbidities such as diabetes mellitus, hypertension, coronary artery disease, and other chronic conditions ( 1 , 2 ). COVID-19 has also been found to be more severe in males than in females with a case fatality rate of 2.8% in males and 1.7% in females ( 11 ). The major organ system affected by the virus is the respiratory system, but it can affect other organ systems either directly or by the effect of host immune response. SARS-CoV-2, the causative agent of COVID-19, after entering the human host initially replicates in the epithelial mucosa of the upper respiratory tract (nose and pharynx) followed by migration to the lungs where further replication of virus occurs causing transient viraemia. The virus uses Angiotensin Converting Enzyme 2 (ACE2) receptor as a primary entry to cells. ACE2 is found abundantly in the mucosal lining of the respiratory tract, vascular endothelial cells, heart, intestine, and kidney. Thus, the virus has potential for replication in all these organs. After entry into cells, the virus undergoes further rapid replication within the target cells and induces extensive epithelial and endothelial dysfunction leading to exponential inflammatory response with the production of a large amount of proinflammatory cytokines and chemokines. Activation of proinflammatory cytokines and chemokines leads to neutrophil activation and migrations and results in the characteristic cytokine storm. The immunological downregulation of ACE2 by the virus contributes to acute lung injury in COVID-19. ACE2 also regulates the renin angiotensin system (RAS); thus, downregulation of ACE2 also causes dysfunction of RAS which contributes to enhanced inflammation ( 2 , 11 – 15 ). These entire factors contribute to symptoms of COVID-19 with sepsis, multi-organ dysfunction, acute respiratory distress syndrome (ARDS), and prothrombotic state leading to an exacerbation of organ dysfunction.

Clinical Manifestation

We review here the system based clinical features of COVID-19.

Respiratory

According to report from WHO-China-Joint Mission on COVID-19, 55,924 laboratories confirmed cases of COVID-19 had fever (87.9%), dry cough (67.7%), fatigue (38.1%), sputum production (33.4%), difficulty breathing (18.6%), sore throat (13.9%), chills (11.4%), nasal congestion (4.8%), and hemoptysis (0.9%) ( 1 ).

Some patients may rapidly progress to acute lung injury and ARDS with septic shock. The median interval between the onset of initial symptoms to development of dyspnea, hospital admission, and ARDS was 5, 7, and 8 days respectively ( 10 ). Some patients with COVID-19 may have reduced oxygen saturation in blood (≤ 93%) with oxygen saturation down to 50 or 60% but remained stable without significant distress, and as such, were termed as salient hypoxia or happy hypoxia ( 16 , 17 ). Trial of oxygen therapy, prone positioning, high flow continuous positive airway pressure, non-re-breathable mask alongside trial of anticoagulation are often used to manage these patients ( 16 , 17 ). However, further study is required to define the role of these strategies in management.

The most frequent radiological abnormality among 975 patients with COVID-19 in computed tomography (CT) scan of chest was ground glass opacity (56.4%) and bilateral patchy shadowing (51.8%) ( 18 ). A scientific review of 2,814 patients have shown that the most common chest CT finding in COVID-19 patients was ground glass opacity followed by consolidation. However, the findings can vary in different patients and at various stages of diseases. Other CT findings include interlobular septal thickening, reticular pattern, crazy paving, etc. Atypical findings like air bronchogram, bronchial wall thickening, nodule, pleural effusion, and lymphadenopathy have also been noted in some studies ( 19 ). A study showed that among 877 patients with non-severe diseases and 173 patients with severe diseases, 17.9 and 2.9% of the patients did not have any detectable radiological abnormalities, respectively ( 18 ).

ENT (Ear, Nose, and Throat)

ENT manifestations are one of the most frequent symptoms encountered by physicians in COVID-19. A peculiar clinical presentation in some COVID-19 patients includes the deterioration of sense, taste (dysgeusia), and loss of smell (anosmia). A systematic review and meta-analysis of 10 studies with 1,627 participants surveyed for olfactory deterioration and 9 studies with 1,390 participants examined for gustatory symptoms demonstrated prevalence of 52.73 and 43.93% of these symptoms among COVID-19 patients, respectively. These clinical features may often present at earlier stages of the disease ( 20 ). Additionally, sore throat, rhinorrhea, nasal congestion, tonsil edema, and enlarged cervical lymph nodes are commonly seen among otolaryngological dysfunctions in patients ( 21 ). A large observational study of 1,099 COVID-19 patients reported tonsils swelling in 23 patients (2.1%), throat congestion in 19 patients (1.7%) and enlarged lymph nodes in 2 patients (0.2%) ( 18 ). This can be explained by the fact that there is a high expression of ACE2 receptors on the epithelial cells of the oral and nasal mucosa including the tongue. It has been known that the novel coronavirus has a strong binding affinity to ACE2 receptors through which it invades host cells ( 22 ). This theory may explain the exhibition of extra-respiratory symptoms including ENT manifestations as part of COVID-19 symptoms.

Cardiovascular

Cardiac manifestation in patient with COVID-19 can occur due to cardiac strain secondary to hypoxia and respiratory failure, direct effect of SARS-CoV-2 on heart or secondary to inflammation and cytokine storm, metabolic derangements, rupture of plaque and coronary occlusion by thrombus, and consequences of drugs used for treatment ( 23 – 25 ). The need for intensive care admission, non-invasive ventilation (46.3 vs. 3.9%), and invasive mechanical ventilation (22 vs. 4.2%) were higher among patients with cardiac ailments as compared to those without cardiac involvement as well as higher hospital mortality than those without myocardial involvement (51.2 vs. 4.5%) ( 26 ). These patients tend to have electrocardiographic (ECG) changes as well as elevations in high sensitivity cardiac troponin (hsCTn) and N- terminal pro-B-type natriuretic peptide (NT proBNP) which corresponded to raised inflammatory markers. Hypertension, acute and fulminant myocarditis, ventricular arrhythmias, atrial fibrillation, stress cardiomyopathy, hypotension and heart failure, acute coronary syndrome (ACS) with ST elevation or depression MI with normal coronaries have been reported ( 23 , 27 ). In a Chinese cohort of 138 patients, 16.7% had arrhythmias with risk higher among those needing ICU care with no mention of the type of arrhythmia that was present ( 28 ). Less frequently, cardiac symptoms like chest pain or tightness and palpitation can be the initial presenting features without fever producing a diagnostic dilemma. Some of these patients eventually go on to develop respiratory symptoms as diseases progress ( 29 ). Patients who have recovered from acute illness may develop arrhythmias as a result of myocardial scar and need future monitoring ( 27 ). One important point to note is use of Renin Angiotensin Aldosterone System (RAAS) modulators in patients with COVID-19. Guidelines from ACC/AHA/HFSA recommends continuing them in high risk patient based on goal directed therapy approach supported by a recent systematic review and meta-analysis conducted by Hasan et. Al. which demonstrated use of ACEI/ARB in COVID-19 patients is associated with lower odds/ hazards of mortality and development of severe/critical diseases as compared to no use of ACEI/ARB ( 30 , 31 ).

Gastrointestinal

In the initial cohort of patients from China, nausea or vomiting and diarrhea were present in 5 and 3.7% of patients ( 1 ). Review of data from 2,023 patients showed anorexia to be the most frequently occurring gastrointestinal symptom in adults. Diarrhea was the most common presenting gastrointestinal symptom in both adults and children while vomiting was found to be more common in children ( 32 ). Other rare symptoms included nausea, abdominal pain, and gastrointestinal bleeding. There have been few instances where COVID-19 patients presented with only gastrointestinal symptoms without the development of fever or respiratory symptoms at the onset and during disease progression ( 33 ). In a smaller cohort of 204 patients, 50.5% had some form of intestinal symptoms and of those, 5.8% had only intestinal symptoms while the remaining patients developed respiratory symptoms subsequently. The most common symptoms reported among them was anorexia (78.64%), non-dehydrating diarrhea (34%), vomiting (3.9%), and abdominal pain (1.94%) ( 34 ). In addition, those with GI symptoms tend to have a longer interval between symptom onset and hospital admission (9 vs. 7.3 days) possibly due to lack of clinical suspicion and delay in diagnosis. Patients with gastrointestinal symptoms tend to have higher elevation in AST and ALT indicating coexistent liver injury ( 34 ). The mechanism behind GI illness is not clearly known but could be due to direct invasion of virus via ACE2 receptor in the intestinal mucosa. This can be supported by the fact that viral RNA can be detected in stool samples of COVID-19 patients which may also hint toward possible fecal-oral transmission ( 35 ). Liver dysfunction is likely secondary to the use of hepatotoxic drugs, hypoxia induced liver injury, systemic inflammation, and multi organ failure ( 36 ).

Renal manifestation in patients with COVID-19 can occur due to direct invasion of podocytes and proximal tubular cells by SARS-CoV-2 virus, secondary endothelial dysfunction causing effacement of foot process with vacuolation and detachment of podocytes, and acute proximal tubular dysfunction ( 37 ). Furthermore, hypoxia, cytokine storm, rhabdomyolysis, nephrotoxic drugs, and overlying infections can all exacerbate renal injury ( 38 ). Based on initial reports, prevalence of Acute Kidney Injury (AKI) among COVID-19 hospitalized patients range from 0.5 to 29%. In a cohort of 701 patients, proteinuria (43.9%), hematuria (26.7%), elevated creatinine (14.4%), elevated blood urea nitrogen (13.1%), and low glomerular filtration rate (≤ 60 ml/min/1.73 m 2 ) (13.1%) were present at the time of hospital admission with 5.1% developing AKI during the illness. AKI was more prevalent among those with baseline renal impairment ( 39 ). In another large cohort of 5,449 patients, 36.6% had AKI with prevalence higher among mechanically ventilated patients compared to non-ventilated patients (89.7 vs. 21.7%) ( 40 ). Patients developing renal impairment are prone to have higher mortality within the hospital. Another point to highlight is the presentation of COVID-19 in renal transplant recipients. Due to immunosuppression, these patients are likely to have low fever at presentation with swift clinical decline and requirement for mechanical ventilation with high mortality as compared to the general population ( 41 ).

Neurological

Most patients with COVID-19 develop neurological symptoms along with respiratory symptoms during the course of illness; however, several case reports in review of literature document patient presentation of neurological dysfunction without typical symptoms of fever, cough, and difficulty breathing ( 42 ). There is a 2.5-fold enhanced risk of severe illness and increased death in patients with a history of previous stroke with similar findings among those with Parkinson's diseases. The prevalence of neurological features ranges from 6 to 36% along with hypoxic ischemic encephalopathy up to 20% in some series of patients ( 43 ). Neurological symptoms tend to occur early in the course of illness (median 1–2 days) with most common neurological features being headache, confusion, delirium, anosmia or hyposmia, dysgeusia or ageusia, altered mental status, ataxia, and seizures ( 44 ). Among patients admitted with COVID-19, the prevalence of ischemic stroke ranges from 2.5 to 5% despite receiving prophylaxis for venous thromboembolism. Patients prone to have established cardiovascular risk factors are likely to have a more severe diseases ( 43 ). Other presentations include viral encephalitis, acute necrotizing encephalopathy (ANE), infectious toxic encephalopathy, meningitis, Guillain Barre Syndrome (GBS), Miller Fisher syndrome, and polyneuritis cranialis with GBS being the first feature of COVID-19 in few cases ( 42 , 43 , 45 ). In COVID-19 patients, CNS features are possibly due to direct invasion of neurons and glial cells by SARS-CoV-2 as well as by endothelial dysfunction of blood brain barrier (BBB). Virus can gain access to CNS via hematogenous spread or retrograde movement across the olfactory bulb. The virus can be detected in CSF by RT-PCR and on brain parenchyma during autopsy. The fact that most patients develop anosmia or hyposmia during illness support this theory ( 45 ). After entry, the virus can cause reactive gliosis with activation of the inflammatory cascade. The combination of systemic inflammation, cytokine storm, and coagulation dysfunction can impair BBB function and alter brain equilibrium causing neuronal death ( 42 ).

Ocular manifestations can vary from conjunctival injection to frank conjunctivitis. In a Chinese cohort of 38 patients, 31.6% had ocular symptoms consisting primarily of conjunctivitis while conjunctival hyperemia, foreign body sensation in eye, chemosis, tearing or epiphora were more common among severe COVID-19 patients. Among them SARS-CoV-2 can be demonstrated in conjunctival as well as nasopharyngeal swab in 5.2% of patients, indicating a potential route for viral transmission ( 46 ). Conjunctivitis or tearing can be the initial presenting symptoms of COVID-19. Despite this fact, there is no documented case of severe ocular features relating to COVID-19.

Similar to other viral infections, SARS-CoV-2 can also produce varied dermatological features. A study of 88 patients from Italy showed that about 20.4% had some form of skin manifestations with 44.4% developing features at onset and duration of the disease progression ( 47 ). Maculopapular exanthem (36.1%) was identified as most common dermatological features followed by papulovesicular rash (34.7%), painful acral red purple papules (15.3%), urticaria (9.7%), livedo reticularis (2.8%), and petechiae (1.4%) ( 48 ). A study of 375 COVID-19 cases in Spain identified five different patterns of cutaneous manifestations in patients: acral areas of erythema with vesicles or pustules (pseudo-chilblain) (19%), other vesicular eruptions (9%), urticarial lesions (19%), maculopapular eruptions (47%), and livedo or necrosis (6%) ( 49 ). Majority of patients had lesions on the trunk with some experiencing lesions on hands and feet. There are case reports of COVID-19 associated with erythema multiforme and Kawasaki Disease in children ( 50 , 51 ). Pathogenesis behind skin involvement remains unclear with some features explained by small vessel vasculitis, thrombotic events like DIC, hyaline thrombus formation, acral ischemia, or the direct effect of the virus like other viral illnesses ( 52 ).

Musculoskeletal

The initial report from China revealed 14.8% of patients had myalgia or arthralgia among 55,924 COVID-19 patients. A review article reports that of 12,046 patients, fatigue was identified in 25.6% and myalgia and/or arthralgia in 15.5% with most patients reporting symptoms from the start of illness ( 53 ). There are reports suggesting myositis and rhabdomyolysis with markedly elevated creatinine kinase can occur during COVID-19 illness especially in patients with severe diseases and multi organ failure. Additionally, in some patients, rhabdomyolysis has been documented as the initial presentation of COVID-19 illness without typical respiratory symptoms ( 54 , 55 ). A case series of four patients developing acute arthritis during hospital admission for COVID-19 has been reported with exacerbation of crystal arthropathy (gout and calcium pyrophosphate diseases) but negative for SARS-CoV-2 RT-PCR in synovial fluid ( 56 ). Treatment with steroids and colchicine was used in all four cases. An important consideration to note was that all four patients developed arthritis despite previous treatment with immunomodulatory therapy (hydroxychloroquine, tocilizumab, and pulse methylprednisolone).

Hematological

As stated, COVID-19 is a systemic disease inducing systemic inflammation and occasionally cytokine storm. This can significantly impact the process of hematopoiesis and hemostasis. During early disease, normal or decreased leukocyte and lymphocyte counts were documented with marked lymphopenia as the diseases progressed, especially in those with cytokine storms and severe disease. In a study of 1,099 patients, lymphopenia, thrombocytopenia, and leukopenia were present in 83.2, 36.2, and 33.7%, respectively, with findings more marked in those with severe diseases ( 18 ). Leukocytosis in COVID-19 patients might suggest a bacterial infection or a superinfection with leukocytosis found more commonly in severe cases (11.4%) as compared to mild and moderate cases (4.8%) ( 18 ). Similarly, thrombocytopenia has been found to be more common (57.7%) in severe cases in contrast to mild and moderate cases (31.6%) ( 18 ). Lymphopenia was also linked with an increased necessity for ICU admission and the risk of ARDS. Thrombocytosis with elevated platelet to lymphocyte ratio may indicate a more marked cytokine storm ( 57 ).

Also, coagulation abnormality can manifest in the form of thrombocytopenia, prolonged prothrombin time (PT), low serum fibrinogen level, and raised D-dimer suggesting Disseminated Intravascular Coagulation (DIC) with these changes more marked in those with severe diseases ( 58 ). Raised lactate dehydrogenase (LDH) and serum ferritin were also present and correlated with the degree of systemic inflammation. In a study of 426 COVID-19 patients, C-Reactive Protein (CRP) was noted to be increased in 75–93% of patients, more commonly in patients with severe disease. Serum procalcitonin levels might not be altered at admission, but progressive increase in its value can suggest a worsening prognosis. Severe disease is linked to increased ALT, bilirubin, serum urea, creatinine, and lowered serum albumin ( 59 ). A study of 1,426 patients showed that Interleukin-6 (IL-6) were raised more in patients with severe COVID-19 than non-severe COVID-19 with progressive rise indicating an increased risk of mortality. Thus, its levels could be regarded as an important prognostic indicator for the extensive inflammation and cytokine storm in COVID-19 patients ( 60 ). Other plasma cytokines and chemokines like IL1B, IFNγ, IP10, MCP, etc. have also been found to be elevated in patients with COVID-19 both in severe and non-severe diseases. Additionally, GCSF, IP10, IL2, IL7, IL10, MCP1, MIP1A, and TNFα were increased in patients who require ICU admission which indicates that cytokine storm is associated with a severe disease ( 61 ).

Endocrine and Reproductive

From the available literature there is no doubt that diabetes mellitus is an important risk factor for COVID-19 illness and is associated with increased risk of development of severe disease. Additionally, there are case reports of subacute thyroiditis linked to SARS-CoV-2 infection ( 62 , 63 ). Based on the statement released from European Society of Endocrinology, patients with primary adrenal failure and congenital adrenal hyperplasia may have theoretically increased susceptibility to infection with higher risk of complications and ultimately mortality but there is no current evidence to support this ( 64 ). The dose of steroids may need to be doubled if there is a clinical suspicion of infection in these patients.

Several claims have been made regarding the impact of COVID-19 on male reproductive function, hypothesizing that COVID-19 can cause potential testicular damage either by binding directly to testicular ACE2 receptors, which are highly expressed in the testicles or by damaging the testis indirectly by exciting local immune system ( 65 ). A study comparing 81 male COVID-19 patients with 100 age matched healthy adults highlighted the presence of low testosterone levels, high levels of luteinizing hormone (LH), low testosterone/LH ratios, low Follicle stimulating hormone (FSH) to LH ratio, and raised serum prolactin. This may suggest a potential COVID-19 testicular damage affecting the Leydig cells in the testis ( 66 ). COVID-19 infected male patients may have reduced sperm count and decreased motility leading to diminished male fertility for 3 months post-infection ( 67 ).

Clinical Presentation in Specific Population

In children.

A case series of 72,314 cases published by the Chinese Center for Disease Control and Prevention reported that 0.9% of the total patients were between 0 and 9 years of age, and 1.2% of the total patients were between 10 and 19 years of age ( 68 ). The most common symptoms found in children are fever, (59%), cough (46%), few cases (12%) of gastrointestinal symptoms, and some cases (26%) showed no specific symptoms initially with patchy consolidation and ground glass opacities in CT chest findings ( 69 ). Chilblain-like acral eruptions, purpuric, and erythema multiforme-like lesions have been found to be more common in children and young adult patients mainly with asymptomatic or mild disease ( 70 ). Lymphopenia in children is relatively less common which is in direct contrast in cases of SARS in children where lymphopenia was more commonly noted ( 69 ).

Multisystem inflammatory syndrome (MIS) is another feared complication of Covid-19 seen in children. Abrams et al. systematically summarized the clinical evidence of 8 studies reporting MIS in 440 children. The median age of patients ranged from 7.3 to 10 years with 59% of all patients being male. The greatest proportion of patients had gastrointestinal symptoms (87%) followed by mucocutaneous symptoms (73%) and cardiovascular symptoms (71%) while fewer patients reported respiratory (47%), neurologic (22%), and musculoskeletal (21%) symptoms. Ferritin and d-dimer were elevated in 50% of patients, and C-reactive protein, interleukin-6, and fibrinogen were elevated in at least 75% of patients. Additionally, 100% of children with cardiovascular involvement reported elevated cardiac-damage markers such as Troponin. Although respiratory manifestation is most frequently expressed in adults, children with MIS exhibited less pulmonary symptoms and more of the other manifestations ( 71 ).

In Pregnant Women

The most common symptoms reported in pregnant women are fever (61.96%), cough (38.04%), malaise (30.49%), myalgia (21.43%), sore throat (12%), and dyspnea (12.05%). Other symptoms found in pregnant women are diarrhea and nasal congestion ( 72 ). In a systematic review including 92 patients, 67.4% manifested diseases at presentation with 31.7% having negative RT-PCR though they had features of viral pneumonia. Only one patient required admission to intensive care and 0% mortality. Fetal outcomes were reported as: 63.8% preterm delivery, 61.1% fetal distress, 80% Cesarean section delivery, 76.92% neonatal intensive care admission, 42.8% low birth weight, and 66.67% had lymphopenia ( 72 ). There was no evidence of vertical transmission. A study of 41 pregnant women with COVID-19 showed that consolidation was more commonly found in CT of pregnant women in contrast to ground-glass opacities in CT of non-pregnant adults ( 73 ). WHO also recommends encouraging lactating mothers with confirmed or suspected COVID-19 to begin or continue breastfeeding including 24-h rooming in, skin to skin contact, and kangaroo mother care especially in immediate postnatal period ( 74 ). On July 14th, 2020, Vivanti et al. published the first case of transplacental transmission of COVID-19 from a 23-years-old pregnant woman to her baby ( 75 ). Thereafter, more studies reported the possibility of the vertical transmission of COVID-19. In this context, Kotlayer et al. published a systematic review of 38 studies. Out of 936 neonates from COVID-19 mothers, 27 tested positive for the virus indicating a pooled proportion of 3.2% (2.2–4.3) for vertical transmission ( 7 ).

In Immuno-Compromised Population

Due to their impaired immune response, it is not surprising that immunocompromised patients with COVID-19 infection might be at greater risk of developing severe forms of the disease and co-infections in comparison to normal populations. Nevertheless, recent studies showed the association between cytokine storm syndrome and the overreaction of the immune system with COVID-19 raising the possibility that immunodeficient states might alleviate the overexpression of the host immune system and thereby prevent deadly forms of the disease ( 76 ). After the RECOVERY trial ( 77 ) that showed the efficacy of dexamethasone in lowering the mortality in severe forms of the disease, many questions were raised regarding whether immunocompromised patients have a greater or lower risk of developing severe forms of the disease. In order to address these questions, Minotti et al. recently published a systematic review that included 16 studies with 110 patients presenting mostly with cancer along with transplantation and immunodeficiency. Out of the 110 patients, 72 (65.5%) recovered without being admitted to the intensive care unit while 23 (20.9%) died ( 76 ). The authors concluded that immunosuppression in both children and adults seem to have a better disease course in comparison to normal population. One of the limitations of this study is that the conclusion was made only based on qualitative synthesis and no meta-analysis was performed. On the other hand, Gao et al. performed a meta-analysis on 8 relevant studies with 4,007 patients. The study showed that immunosuppression and immunodeficiency were associated with non-statistically significant increased risk of severe COVID-19 disease ( 78 ). Additionally, Mirzaei et al. summarized the clinical evidence of 252 HIV positive patients co-infected with COVID-19. The clinical manifestation did not differ from that of the general population. However, out of the 252 patients, 204 (80.9%) were male. Low CD4 count (<200 cells/mm 3 ) were reported for 23 of 176 patients (13.1%). COVID-19 symptoms were present in 223 patients with the most common symptoms of fever in 165 (74.0%) patients, cough in 130 (58.3%), headache in 44 (19.7%), arthralgia and myalgia in 33 (14.8%), gastrointestinal symptoms in 29 (13.0%) followed by sore throat in 18 (8.1%) patients ( 79 ). The number of deaths accounted for 36 (14.3%). Similar to the general population, immunocompromised, and HIV patients were no different in terms of clinical manifestation or severity. However, the results from these studies should be interpreted with caution and more studies are recommended to establish the link between this particular group of patients with severity of the disease.

Multisystem Involvement in COVID-19

As evident from the discussion above, SARS-CoV-2 can affect multiple organ systems and produce a wide array of clinical presentation of COVID-19. Certain studies conducted in Europe and United States have shown that COVID-19 can also have a multi-systemic presentation in individuals in form of a multi-system inflammatory syndrome (MIS) which has been found in both children and adults and is known as MIS-C and MIS-A, respectively ( 80 – 83 ).

According to a recent CDC report about MIS-A, it was found that only half of the patients with MIS-A had preceding respiratory symptoms of COVID-19 ~2–5 weeks before ( 80 ). The most common clinical signs and symptoms included fever, chest pain, palpitations, diarrhea, abdominal pain, vomiting, skin rash, etc. Nearly all patients had electro-cardiological abnormalities like arrythmias, elevated troponin levels, and electrocardiography evidence of left or right ventricular dysfunction. Even though most patients had minimal respiratory symptoms, chest imaging had features of ground glass opacity and pleural effusion. All patients had signs of elevated laboratory markers of inflammation, coagulation markers, and lymphopenia ( 80 ).

MIS-C can clinically mimic Kawasaki Disease ( 81 ). By the end of July, about 570 cases of MIS-C with COVID-19 were found in the United States ( 81 ). In MIS-C, there is involvement of at least four organ systems, most commonly the gastrointestinal system followed by cardiovascular and dermatological systems ( 81 ). Prominent signs and symptoms found in children with MIS-C were abdominal pain, vomiting, skin rash, diarrhea, hypotension, and conjunctival injection. The majority of the children needed ICU admission due to the development of severe complications including cardiac dysfunction, shock, myocarditis, coronary artery aneurysm, and acute kidney injury ( 81 ).

Association Between Clinical Presentations, COVID-19 Severity and Prognosis

Evaluation of 55,924 laboratory confirmed COVID-19 cases in China, the presence of dyspnea, respiratory rate ≥ 30/min, blood saturation levels ≤ 93%, PaO2/FiO2 ratio ≤ 300, lung infiltrates ≥ 50% of the lung fields between 12 and 48 h were associated with severe COVID-19 infection ( 1 ). Clinical signs suggestive of respiratory failure, septic shock, or multiple organ dysfunction/failure were associated with critical disease and poor prognosis ( 1 ). Individuals at highest risk of severe disease and deaths were patients with age > 80 years and associated co-morbidities such as underlying cardiovascular disease, diabetes, hypertension, chronic respiratory disease, and cancer ( 1 ). Another study done with 418 patients in Catalonia (Spain) showed that dyspnea was an important predictor of severe disease while confusion was an important predictor of death, and the presence of cough was strongly associated with good prognosis ( 84 ). Advanced age, male sex, and obesity were independent markers of poor prognosis while eosinophilia was a marker of less severe disease ( 84 ). The mortality was lower in patients with symptoms of diarrhea, arthromyalgia, headache, and loss of smell and taste sensations while low oxygen saturation, high CRP levels, and higher number of lung quadrants affected on Xray were found to be associated with severe disease and death ( 84 ).

COVID-19 is a viral illness which can cause multi-systemic manifestations. Review of existing literature concludes that SARS-CoV-2 can affect any organ system either directly or indirectly leading to a myriad of clinical presentation. The most commonly affected system is the respiratory system with presenting symptoms of fever, cough, and shortness of breath, etc. Other systems which can be affected in COVID-19 include ENT (sore throat, loss of taste, smell, and sensations, and rhinorrhea), cardiovascular system (chest pain, chest tightness, palpitations, and arrhythmias), gastrointestinal system (anorexia, diarrhea, vomiting, nausea, and abdominal pain), renal (proteinuria, hematuria, and acute kidney injury), neurological (headache, confusion, delirium, and altered mental status), ocular (conjunctival hyperemia, foreign body sensation in the eye, chemosis, and tearing), cutaneous (rash, papules, and urticaria), musculoskeletal system (myalgia and arthralgia), hematological (lymphopenia, thrombocytopenia, leukopenia, elevated inflammatory markers, and elevated coagulation markers), endocrine (low testosterone, low FSH, and high LH) and reproductive system (decreased sperm count and decreased sperm motility). Clinical presentation in specific populations like children, pregnant women, and immunocompromised people may vary which emphasizes the importance of further investigation in order to avoid late diagnosis of COVID-19. Severe multi-systemic involvement in COVID-19 in the form of MIS-C and MIS-A can cause significant morbidity and mortality if undiagnosed. The clinical presentations of respiratory failure, acute kidney injury, septic shock, cardiovascular arrest is associated with severe COVID-19 disease and can result in poor prognosis. In the light of exponentially growing pandemic, every patient presenting to hospital must be tested for SARS-CoV-2 by RT-PCR if resources are available to detect early presentations of diseases even if the features are atypical. Understanding of the various clinical presentations of COVID-19 will help the clinicians in early detection, treatment, and isolation of patients in order to contain the virus and slow down the pandemic.

Author Contributions

All authors have contributed equally to the work, and all agreed to be accountable for the content of the work.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank Ms. Sairah Zia (American University of Caribbean, School of Medicine, Sint Maarten), a native speaker of English, for proofreading the manuscript.

Abbreviations

ACC/AHA/HFSA, American College of Cardiology/American Heart Association/Heart Failure Society of America; IL1B, Interleukin 1B; IFNγ, Interferon Gamma; IP10, Interferon-inducible Protein 10; MCP1, Monocyte Chemoattractant Protein 1; GCSF, Granulocyte Colony Stimulating Factor; IL2, Interleukin 2; IL7, Interleukin 7; IL10, Interleukin 10; MIP1A, Macrophage Inflammatory Protein-1 alpha; TNFα, Tumor Necrosis Factor alpha.

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Keywords: SARS-CoV-2, Covid-19, symptomatology, clinical presentation, signs and symptoms, clinical features, coronavirus

Citation: Mehta OP, Bhandari P, Raut A, Kacimi SEO and Huy NT (2021) Coronavirus Disease (COVID-19): Comprehensive Review of Clinical Presentation. Front. Public Health 8:582932. doi: 10.3389/fpubh.2020.582932

Received: 13 July 2020; Accepted: 15 December 2020; Published: 15 January 2021.

Reviewed by:

Copyright © 2021 Mehta, Bhandari, Raut, Kacimi and Huy. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Nguyen Tien Huy, tienhuy@nagasaki-u.ac.jp

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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• Wear a properly fitted mask when physical distancing is not possible or when in poorly ventilated settings.
• Choose open, well-ventilated spaces over closed ones. Open a window if indoors.
• Wash your hands regularly with soap and water or clean them with alcohol-based hand rub.
• Cover your mouth and nose when coughing or sneezing.
• If you feel unwell, stay home and self-isolate until you recover.

COVID-19 affects different people in different ways. Most infected people will develop mild to moderate illness and recover without hospitalization.

Most common symptoms:

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• red or irritated eyes.

Serious symptoms:

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• loss of speech or mobility, or confusion
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Seek immediate medical attention if you have serious symptoms.  Always call before visiting your doctor or health facility. 

People with mild symptoms who are otherwise healthy should manage their symptoms at home. 

On average it takes 5–6 days from when someone is infected with the virus for symptoms to show, however it can take up to 14 days. 

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Coronavirus disease 2019 (COVID-19): A literature review

Affiliations.

• 1 Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
• 2 Division of Infectious Diseases, AichiCancer Center Hospital, Chikusa-ku Nagoya, Japan. Electronic address: [email protected].
• 3 Department of Family Medicine, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
• 4 Department of Pulmonology and Respiratory Medicine, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
• 5 School of Medicine, The University of Western Australia, Perth, Australia. Electronic address: [email protected].
• 6 Siem Reap Provincial Health Department, Ministry of Health, Siem Reap, Cambodia. Electronic address: [email protected].
• 7 Department of Microbiology and Parasitology, Faculty of Medicine and Health Sciences, Warmadewa University, Denpasar, Indonesia; Department of Medical Microbiology and Immunology, University of California, Davis, CA, USA. Electronic address: [email protected].
• 8 Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Clinical Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
• 9 Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, MI 48109, USA. Electronic address: [email protected].
• 10 Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia; Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia. Electronic address: [email protected].
• PMID: 32340833
• PMCID: PMC7142680
• DOI: 10.1016/j.jiph.2020.03.019

In early December 2019, an outbreak of coronavirus disease 2019 (COVID-19), caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), occurred in Wuhan City, Hubei Province, China. On January 30, 2020 the World Health Organization declared the outbreak as a Public Health Emergency of International Concern. As of February 14, 2020, 49,053 laboratory-confirmed and 1,381 deaths have been reported globally. Perceived risk of acquiring disease has led many governments to institute a variety of control measures. We conducted a literature review of publicly available information to summarize knowledge about the pathogen and the current epidemic. In this literature review, the causative agent, pathogenesis and immune responses, epidemiology, diagnosis, treatment and management of the disease, control and preventions strategies are all reviewed.

Keywords: 2019-nCoV; COVID-19; Novel coronavirus; Outbreak; SARS-CoV-2.

Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

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• COVID-19 pandemic and Internal Medicine Units in Italy: a precious effort on the front line. Montagnani A, Pieralli F, Gnerre P, Vertulli C, Manfellotto D; FADOI COVID-19 Observatory Group. Montagnani A, et al. Intern Emerg Med. 2020 Nov;15(8):1595-1597. doi: 10.1007/s11739-020-02454-5. Epub 2020 Jul 31. Intern Emerg Med. 2020. PMID: 32737837 Free PMC article. No abstract available.

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• Published: 15 February 2023

Coronavirus research: knowledge gaps and research priorities

• Stanley Perlman   ORCID: orcid.org/0000-0003-4213-2354 1 &
• Malik Peiris   ORCID: orcid.org/0000-0001-8217-5995 2 , 3  

Nature Reviews Microbiology volume  21 ,  pages 125–126 ( 2023 ) Cite this article

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• Policy and public health in microbiology

Decades of coronavirus research and intense studies of SARS-CoV-2 since the beginning of the COVID-19 pandemic have led to an unprecedented level of knowledge of coronavirus biology and pathogenesis, yet many outstanding questions remain. Here, we discuss knowledge gaps and research priorities in the field.

Introduction

The COVID-19 pandemic showed that, based on previous research efforts, we understood many aspects of coronavirus biology and pathogenesis, but also that there was much we did not know. In 2019, the worldwide number of coronavirus investigators was small, having increased after the severe acute respiratory syndrome coronavirus (SARS-CoV) outbreak in 2003 but decreasing thereafter. The influx of scientists with diverse expertise into the field after the pandemic onset contributed to an increased understanding of coronavirus replication, epidemiology, SARS-CoV-2 pathogenesis and immune responses in humans, to the development and characterization of experimentally infected animal models for COVID-19, and to SARS-CoV-2 vaccine and antiviral drug development. Here, as investigators who have studied coronaviruses for decades, we outline some of the outstanding research questions that we think need to be addressed.

SARS-CoV-2 emergence

Where did SARS-CoV-2 originate and how did it evolve to infect humans? The emergence of SARS-CoV-2 continues to be an area of controversy and has been, and is being, investigated by many national and international organizations, including the WHO (World Health Organization). It is almost certain that the virus originated in bats and crossed species to humans either directly or indirectly via intermediary hosts. There remains debate on whether the virus first infected humans from a zoonotic source or from a research laboratory, but, no matter what the answer to this question is, it is clear to us that in order to be prepared for the next pandemic, we need to further delineate the panoply of coronaviruses present in bats and possible intermediary hosts 1 . We need to better understand coronavirus circulation in hotspots, such as parts of China and Southeast Asia, where humans, wildlife gathered for food or medicinal purposes and bats are in close proximity. These investigations should include surveillance (virological and serological) of humans in close contact with bats and the game animal trade, with or without respiratory disease, for evidence of coronavirus infection. A related question, discussed below, is why coronaviruses are especially good at jumping species, to humans and other animals.

Zoonotic risk

Once coronaviruses in animal reservoirs are identified, can they be better risk assessed for threats for human spillover? Surveillance of bat reservoirs of sarbecoviruses (Sarbecovirus is the subgenus to which SARS-CoV-2 belongs) had previously found evidence of viruses with a capacity for infecting human cells using the angiotensin converting enzyme 2 (ACE2) receptor (reminiscent of SARS-CoV) 2 . Serological evidence of viral spillover to humans was demonstrated before the emergence of SARS-CoV-2 (ref. 3 ). Arguably, these signals together should have been triggers for action to develop countermeasures with greater urgency. The availability of human organoid cultures and ex vivo cultures of human respiratory tissue may enable the use of physiologically relevant systems for a more systematic risk assessment of animal coronaviruses in the future, analogous to ongoing risk assessments being carried out for animal influenza viruses 4 .

SARS-CoV-2 transmissibility

What explains the high transmissibility of SARS-CoV-2 compared with SARS-CoV or Middle East respiratory syndrome coronavirus (MERS-CoV)? A critical factor leading to the COVID-19 pandemic was the ability of SARS-CoV-2 to grow to high levels in the upper respiratory tract and therefore to readily transmit to other humans. Titres of SARS-CoV and MERS-CoV in the upper respiratory tract peak at later times after infection 5 , consistent with the ability to interrupt transmission with relevant public health infection-prevention methods. A second, related question is why SARS-CoV and a common cold coronavirus, HCoV-NL63, which both use the same receptor as SARS-CoV-2 (ACE2) 6 , have such different patterns of infection within the human respiratory tract. HCoV-NL63 rarely infects the lower respiratory tract, whereas SARS-CoV preferentially causes pneumonia. These different patterns of infection most likely relate to differences in cell entry, including differences in co-receptor usage, host protease usage or fusogenicity of the spike protein, but there are other possibilities. Understanding these differences will provide information on which coronavirus might be expected to be transmissible and to identify additional targets for therapeutic interventions. Further elucidation of the factors that contribute to virus spread will require additional experimental animal models of coronavirus transmission.

The SARS-CoV-2 outbreak also highlighted the lack of evidence-based data on the transmission of coronaviruses, or indeed respiratory viruses in in general, and on which non-pharmaceutical countermeasures (for example, social distancing and masks (surgical versus N99/FFP3 masks)) are effective or not. The SARS-CoV-2 outbreak demonstrated that the only effective control options available in the first months of the pandemic were non-pharmaceutical, but our understanding of the efficacy of specific measures is limited.

Coronavirus genome complexity

Why do coronavirus genomes encode so many more proteins than other RNA viruses? Coronavirus genomes are bigger than those of any other RNA virus, apart from those of related members of the Nidovirales order. The genomes are so large that they require genomic proofreading activity to avoid error catastrophe 7 . A large genome size may contribute to enhanced cross-species transmission, but, at present, this notion is speculative. In any case, an important question is to understand the function of the many non-structural proteins involved in virus replication. Development of a cell-free or entirely in vitro replication system would facilitate detailed probing of the role of individual proteins in replication and transmission. Efforts to develop such cell-free systems were initiated 40 years ago, but it is only in the past few years with the advent of cryo-electron microscopy and new biochemical approaches that progress has been made. These efforts are expected to complement studies in intact cells, which use high-resolution microscopy and related techniques to analyse macromolecular interactions and function at the subcellular level.

Related to the previous question, why do coronaviruses encode so many proteins with apparent immunoevasive function? Coronaviruses encode a variable number of accessory proteins, the genes of which are intermingled within the structural protein genes located at the 3′ end of the genome. For example, SARS-CoV-2 encodes at least six such proteins, with several other putative open reading frames in the genome hypothesized to be expressed and have immunoevasive properties 8 . Confusingly, these genes are often deleted in viruses isolated from infected animals, without apparent loss of virulence. This was shown most clearly in the case of MERS-CoV, in which diverse deletions and insertions in accessory genes were detected in some isolates obtained in Africa from camels, the primary host of the virus 9 . These genetic changes may have unpredictable consequences for virus transmissibility or pathogenesis. Deletion of these genes occasionally leads to increased virulence 10 . The variable and sometimes unexpectedly high numbers of these proteins suggest that they have redundant and, perhaps, additional functions. Such redundancy could contribute to cross-species transmission. The genetic instability of MERS-CoV camels in Africa therefore needs to be monitored and evidence for human spillover needs to be continually assessed.

Predictive evolution

Can coronavirus evolution in infected human or other animal hosts be predicted? Coronaviruses readily mutate and recombine as they adapt to a new host. This is well illustrated by the COVID-19 pandemic, in which ancestral strains of SARS-CoV-2 initially mutated to better infect humans, and later evolved to evade the human immune response, generating a series of variants of concern. Several studies have modelled SARS-CoV-2 evolution but so far it has not been possible to predict how the virus will evolve in the future. Such predictive modelling is recognized to be difficult, but would be very useful in the present pandemic as well as in future coronavirus outbreaks or pandemics for vaccine development, for anticipating clinical disease and pathogenesis, and for risk assessment of animal viruses with zoonotic potential.

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Stanley Perlman

HKU-Pasteur Research Pole, The University of Hong Kong (HKU), Hong Kong Special Administrative Region, People’s Republic of China

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Perlman, S., Peiris, M. Coronavirus research: knowledge gaps and research priorities. Nat Rev Microbiol 21 , 125–126 (2023). https://doi.org/10.1038/s41579-022-00837-3

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Research Article

The impact of the COVID-19 pandemic on scientific research in the life sciences

Roles Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Affiliation AXES, IMT School for Advanced Studies Lucca, Lucca, Italy

Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Chair of Systems Design D-MTEC, ETH Zürich, Zurich, Switzerland

• Massimo Riccaboni, 
• Luca Verginer

• Published: February 9, 2022
• https://doi.org/10.1371/journal.pone.0263001
• Reader Comments

The COVID-19 outbreak has posed an unprecedented challenge to humanity and science. On the one side, public and private incentives have been put in place to promptly allocate resources toward research areas strictly related to the COVID-19 emergency. However, research in many fields not directly related to the pandemic has been displaced. In this paper, we assess the impact of COVID-19 on world scientific production in the life sciences and find indications that the usage of medical subject headings (MeSH) has changed following the outbreak. We estimate through a difference-in-differences approach the impact of the start of the COVID-19 pandemic on scientific production using the PubMed database (3.6 Million research papers). We find that COVID-19-related MeSH terms have experienced a 6.5 fold increase in output on average, while publications on unrelated MeSH terms dropped by 10 to 12%. The publication weighted impact has an even more pronounced negative effect (-16% to -19%). Moreover, COVID-19 has displaced clinical trial publications (-24%) and diverted grants from research areas not closely related to COVID-19. Note that since COVID-19 publications may have been fast-tracked, the sudden surge in COVID-19 publications might be driven by editorial policy.

Citation: Riccaboni M, Verginer L (2022) The impact of the COVID-19 pandemic on scientific research in the life sciences. PLoS ONE 17(2): e0263001. https://doi.org/10.1371/journal.pone.0263001

Editor: Florian Naudet, University of Rennes 1, FRANCE

Received: April 28, 2021; Accepted: January 10, 2022; Published: February 9, 2022

Copyright: © 2022 Riccaboni, Verginer. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The processed data, instructions on how to process the raw PubMed dataset as well as all code are available via Zenodo at https://doi.org/10.5281/zenodo.5121216 .

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The COVID-19 pandemic has mobilized the world scientific community in 2020, especially in the life sciences [ 1 , 2 ]. In the first three months after the pandemic, the number of scientific papers about COVID-19 was fivefold the number of articles on H1N1 swine influenza [ 3 ]. Similarly, the number of clinical trials related to COVID-19 prophylaxis and treatments skyrocketed [ 4 ]. Thanks to the rapid mobilization of the world scientific community, COVID-19 vaccines have been developed in record time. Despite this undeniable success, there is a rising concern about the negative consequences of COVID-19 on clinical trial research, with many projects being postponed [ 5 – 7 ]. According to Evaluate Pharma, clinical trials were one of the pandemic’s first casualties, with a record number of 160 studies suspended for reasons related to COVID-19 in April 2020 [ 8 , 9 ] reporting a total of 1,200 trials suspended as of July 2020. As a consequence, clinical researchers have been impaired by reduced access to healthcare research infrastructures. Particularly, the COVID-19 outbreak took a tall on women and early-career scientists [ 10 – 13 ]. On a different ground, Shan and colleagues found that non-COVID-19-related articles decreased as COVID-19-related articles increased in top clinical research journals [ 14 ]. Fraser and coworker found that COVID-19 preprints received more attention and citations than non-COVID-19 preprints [ 1 ]. More recently, Hook and Porter have found some early evidence of ‘covidisation’ of academic research, with research grants and output diverted to COVID-19 research in 2020 [ 15 ]. How much should scientists switch their efforts toward SARS-CoV-2 prevention, treatment, or mitigation? There is a growing consensus that the current level of ‘covidisation’ of research can be wasteful [ 4 , 5 , 16 ].

Against this background, in this paper, we investigate if the COVID-19 pandemic has induced a shift in biomedical publications toward COVID-19-related scientific production. The objective of the study is to show that scientific articles listing covid-related Medical Subject Headings (MeSH) when compared against covid-unrelated MeSH have been partially displaced. Specifically, we look at several indicators of scientific production in the life sciences before and after the start of the COVID-19 pandemic: (1) number of papers published, (2) impact factor weighted number of papers, (3) opens access, (4) number of publications related to clinical trials, (5) number of papers listing grants, (6) number of papers listing grants existing before the pandemic. Through a natural experiment approach, we analyze the impact of the pandemic on scientific production in the life sciences. We consider COVID-19 an unexpected and unprecedented exogenous source of variation with heterogeneous effects across biomedical research fields (i.e., MeSH terms).

Based on the difference in difference results, we document the displacement effect that the pandemic has had on several aspects of scientific publishing. The overall picture that emerges from this analysis is that there has been a profound realignment of priorities and research efforts. This shift has displaced biomedical research in fields not related to COVID-19.

The rest of the paper is structured as follows. First, we describe the data and our measure of relatedness to COVID-19. Next, we illustrate the difference-in-differences specification we rely on to identify the impact of the pandemic on scientific output. In the results section, we present the results of the difference-in-differences and network analyses. We document the sudden shift in publications, grants and trials towards COVID-19-related MeSH terms. Finally, we discuss the findings and highlight several policy implications.

Materials and methods

The present analysis is based primarily on PubMed and the Medical Subject Headings (MeSH) terminology. This data is used to estimate the effect of the start of the COVID 19 pandemic via a difference in difference approach. This section is structured as follows. We first introduce the data and then the econometric methodology. This analysis is not based on a pre-registered protocol.

Selection of biomedical publications.

We rely on PubMed, a repository with more than 34 million biomedical citations, for the analysis. Specifically, we analyze the daily updated files up to 31/06/2021, extracting all publications of type ‘Journal Article’. For the principal analysis, we consider 3,638,584 papers published from January 2019 to December 2020. We also analyze 11,122,017 papers published from 2010 onwards to identify the earliest usage of a grant and infer if it was new in 2020. We use the SCImago journal ranking statistics to compute the impact factor weighted number (IFWN) of papers in a given field of research. To assign the publication date, we use the ‘electronically published’ dates and, if missing, the ‘print published’ dates.

Medical subject headings.

We rely on the Medical Subject Headings (MeSH) terminology to approximate narrowly defined biomedical research fields. This terminology is a curated medical vocabulary, which is manually added to papers in the PubMed corpus. The fact that MeSH terms are manually annotated makes this terminology ideal for classification purposes. However, there is a delay between publication and annotation, on the order of several months. To address this delay and have the most recent classification, we search for all 28 425 MeSH terms using PubMed’s ESearch utility and classify paper by the results. The specific API endpoint is https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi , the relevant scripts are available with the code. For example, we assign the term ‘Ageusia’ (MeSH ID D000370) to all papers listed in the results of the ESearch API. We apply this method to the whole period (January 2019—December 2020) and obtain a mapping from papers to the MeSH terms. For every MeSH term, we keep track of the year they have been established. For instance, COVID-19 terms were established in 2020 (see Table 1 ): in January 2020, the WHO recommended 2019-nCoV and 2019-nCoV acute respiratory disease as provisional names for the virus and disease. The WHO issued the official terms COVID-19 and SARS-CoV-2 at the beginning of February 2020. By manually annotating publications, all publications referring to COVID-19 and SARS-CoV-2 since January 2020 have been labelled with the related MeSH terms. Other MeSH terms related to COVID-19, such as coronavirus, for instance, have been established years before the pandemic (see Table 2 ). We proxy MeSH term usage via search terms using the PubMed EUtilities API; this means that we are not using the hand-labelled MeSH terms but rather the PubMed search results. This means that the accuracy of the MeSH term we assign to a given paper is not perfect. In practice, this means that we have assigned more MeSH terms to a given term than a human annotator would have.

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https://doi.org/10.1371/journal.pone.0263001.t001

The list contains only terms with at least 100 publications in 2020.

https://doi.org/10.1371/journal.pone.0263001.t002

Clinical trials and publication types.

We classify publications using PubMed’s ‘PublicationType’ field in the XML baseline files (There are 187 publication types, see https://www.nlm.nih.gov/mesh/pubtypes.html ). We consider a publication to be related to a clinical trial if it lists any of the following descriptors:

• D016430: Clinical Trial
• D017426: Clinical Trial, Phase I
• D017427: Clinical Trial, Phase II
• D017428: Clinical Trial, Phase III
• D017429: Clinical Trial, Phase IV
• D018848: Controlled Clinical Trial
• D065007: Pragmatic Clinical Trial
• D000076362: Adaptive Clinical Trial
• D000077522: Clinical Trial, Veterinary

In our analysis of the impact of COVID-19 on publications related to clinical trials, we only consider MeSH terms that are associated at least once with a clinical trial publication over the two years. We apply this restriction to filter out MeSH terms that are very unlikely to be relevant for clinical trial types of research.

Open access.

We proxy the availability of a journal article to the public, i.e., open access, if it is available from PubMed Central. PubMed Central archives full-text journal articles and provides free access to the public. Note that the copyright license may vary across participating publishers. However, the text of the paper is for all effects and purposes freely available without requiring subscriptions or special affiliation.

We infer if a publication has been funded by checking if it lists any grants. We classify grants as either ‘old’, i.e. existed before 2019, or ‘new’, i.e. first observed afterwards. To do so, we collect all grant IDs for 11,122,017 papers from 2010 on-wards and record their first appearance. This procedure is an indirect inference of the year the grant has been granted. The basic assumption is that if a grant number has not been listed in any publication since 2010, it is very likely a new grant. Specifically, an old grant is a grant listed since 2019 observed at least once from 2010 to 2018.

Note that this procedure is only approximate and has a few shortcomings. Mistyped grant numbers (e.g. ‘1234-M JPN’ and ‘1234-M-JPN’) could appear as new grants, even though they existed before, or new grants might be classified as old grants if they have a common ID (e.g. ‘Grant 1’). Unfortunately, there is no central repository of grant numbers and the associated metadata; however, there are plans to assign DOI numbers to grants to alleviate this problem (See https://gitlab.com/crossref/open_funder_registry for the project).

Impact factor weighted publication numbers (IFWN).

In our analysis, we consider two measures of scientific output. First, we simply count the number of publications by MeSH term. However, since journals vary considerably in terms of impact factor, we also weigh the number of publications by the impact factor of the venue (e.g., journal) where it was published. Specifically, we use the SCImago journal ranking statistics to weigh a paper by the impact factor of the journal it appears in. We use the ‘citation per document in the past two years’ for 45,230 ISSNs. Note that a journal may and often has more than one ISSN, i.e., one for the printed edition and one for the online edition. SCImago applies the same score for a venue across linked ISSNs.

For the impact factor weighted number (IFWN) of publication per MeSH terms, this means that all publications are replaced by the impact score of the journal they appear in and summed up.

COVID-19-relatedness.

To measure how closely related to COVID-19 is a MeSH term, we introduce an index of relatedness to COVID-19. First, we identify the focal COVID-19 terms, which appeared in the literature in 2020 (see Table 1 ). Next, for all other pre-existing MeSH terms, we measure how closely related to COVID-19 they end up being.

Our aim is to show that MeSH terms that existed before and are related have experienced a sudden increase in the number of (impact factor weighted) papers.

Intuitively we can read this measure as: what is the probability in 2020 that a COVID-19 MeSH term is present given that we chose a paper with MeSH term i ? For example, given that in 2020 we choose a paper dealing with “Ageusia” (i.e., Complete or severe loss of the subjective sense of taste), there is a 96% probability that this paper also lists COVID-19, see Table 1 .

Note that a paper listing a related MeSH term does not imply that that paper is doing COVID-19 research, but it implies that one of the MeSH terms listed is often used in COVID-19 research.

In sum, in our analysis, we use the following variables:

• Papers: Number of papers by MeSH term;
• Impact: Impact factor weighted number of papers by MeSH term;
• PMC: Papers listed in PubMed central by MeSH term, as a measure of Open Access publications;
• Trials: number of publications of type “Clinical Trial” by MeSH term;
• Grants: number of papers with at least one grant by MeSH term;
• Old Grants: number of papers listing a grant that has been observed between 2010 and 2018, by MeSH term;

Difference-in-differences

The difference-in-differences (DiD) method is an econometric technique to imitate an experimental research design from observation data, sometimes referred to as a quasi-experimental setup. In a randomized controlled trial, subjects are randomly assigned either to the treated or the control group. Analogously, in this natural experiment, we assume that medical subject headings (MeSH) have been randomly assigned to be either treated (related) or not treated (unrelated) by the pandemic crisis.

Before the COVID, for a future health crisis, the set of potentially impacted medical knowledge was not predictable since it depended on the specifics of the emergency. For instance, ageusia (loss of taste), a medical concept existing since 1991, became known to be a specific symptom of COVID-19 only after the pandemic.

Specifically, we exploit the COVID-19 as an unpredictable and exogenous shock that has deeply affected the publication priorities for biomedical scientific production, as compared to the situation before the pandemic. In this setting, COVID-19 is the treatment, and the identification of this new human coronavirus is the event. We claim that treated MeSH terms, i.e., MeSH terms related to COVID-19, have experienced a sudden increase in terms of scientific production and attention. In contrast, research on untreated MeSH terms, i.e., MeSH terms not related to COVID-19, has been displaced by COVID-19. Our analysis compares the scientific output of COVID-19 related and unrelated MeSH terms before and after January 2020.

In our case, some of the terms turn out to be related to COVID-19 in 2020, whereas most of the MeSH terms are not closely related to COVID-19.

Thus β 1 identifies the overall effect on the control group after the event, β 2 the difference across treated and control groups before the event (i.e. the first difference in DiD) and finally the effect on the treated group after the event, net of the first difference, β 3 . This last parameter identifies the treatment effect on the treated group netting out the pre-treatment difference.

For the DiD to have a causal interpretation, it must be noted that pre-event, the trends of the two groups should be parallel, i.e., the common trend assumption (CTA) must be satisfied. We will show that the CTA holds in the results section.

To specify the DiD model, we need to define a period before and after the event and assign a treatment status or level of exposure to each term.

Before and after.

The pre-treatment period is defined as January 2019 to December 2019. The post-treatment period is defined as the months from January 2020 to December 2020. We argue that the state of biomedical research was similar in those two years, apart from the effect of the pandemic.

Treatment status and exposure.

The treatment is determined by the COVID-19 relatedness index σ i introduced earlier. Specifically, this number indicates the likelihood that COVID-19 will be a listed MeSH term, given that we observe the focal MeSH term i . To show that the effect becomes even stronger the closer related the subject is, and for ease of interpretation, we also discretize the relatedness value into three levels of treatment. Namely, we group MeSH terms with a σ between, 0% to 20%, 20% to 80% and 80% to 100%. The choice of alternative grouping strategies does not significantly affect our results. Results for alternative thresholds of relatedness can be computed using the available source code. We complement the dichotomized analysis by using the treatment intensity (relatedness measure σ ) to show that the result persists.

Panel regression.

In this work, we estimate a random effects panel regression where the units of analysis are 28 318 biomedical research fields (i.e. MeSH terms) observed over time before and after the COVID-19 pandemic. The time resolution is at the monthly level, meaning that for each MeSH term, we have 24 observations from January 2019 to December 2020.

The outcome variable Y it identifies the outcome at time t (i.e., month), for MeSH term i . As before, P t identifies the period with P t = 0 if the month is before January 2020 and P t = 1 if it is on or after this date. In (3) , the treatment level is measure by the relatedness to COVID-19 ( σ i ), where again the γ 1 identifies pre-trend (constant) differences and δ 1 the overall effect.

In total, we estimate six coefficients. As before, the δ l coefficient identifies the DiD effect.

Verifying the Common Trend Assumption (CTA).

We show that the CTA holds for this model by comparing the pre-event trends of the control group to the treated groups (COVID-19 related MeSH terms). Namely, we show that the pre-event trends of the control group are the same as the pre-event trends of the treated group.

Co-occurrence analysis

To investigate if the pandemic has caused a reconfiguration of research priorities, we look at the MeSH term co-occurrence network. Precisely, we extract the co-occurrence network of all 28,318 MeSH terms as they appear in the 3.3 million papers. We considered the co-occurrence networks of 2018, 2019 and 2020. Each node represents a MeSH term in these networks, and a link between them indicates that they have been observed at least once together. The weight of the edge between the MeSH terms is given by the number of times those terms have been jointly observed in the same publications.

Medical language is hugely complicated, and this simple representation does not capture the intricacies, subtle nuances and, in fact, meaning of the terms. Therefore, we do not claim that we can identify how the actual usage of MeSH terms has changed from this object, but rather that it has. Nevertheless, the co-occurrence graph captures rudimentary relations between concepts. We argue that absent a shock to the system, their basic usage patterns, change in importance (within the network) would essentially be the same from year to year. However, if we find that the importance of terms changes more than expected in 2020, it stands to reason that there have been some significant changes.

To show that that MeSH usage has been affected, we compute for each term in the years 2018, 2019 and 2020 their PageRank centrality [ 17 ]. The PageRank centrality tells us how likely a random walker traversing a network would be found at a given node if she follows the weights of the empirical edges (i.e., co-usage probability). Specifically, for the case of the MeSH co-occurrence network, this number represents how often an annotator at the National Library of Medicine would assign that MeSH term following the observed general usage patterns. It is a simplistic measure to capture the complexities of biomedical research. Nevertheless, it captures far-reaching interdependence across MeSH terms as the measure uses the whole network to determine the centrality of every MeSH term. A sudden change in the rankings and thus the position of MeSH terms in this network suggests that a given research subject has risen as it is used more often with other important MeSH terms (or vice versa).

We then compare the growth for each MeSH i term in g i (2019), i.e. before the the COVID-19 pandemic, with the growth after the event ( g i (2020)).

Publication growth

Changes in output and COVID-19 relatedness

Before we show the regression results, we provide descriptive evidence that publications from 2019 to 2020 have drastically increased. By showing that this growth correlates strongly with a MeSH term’s COVID-19 relatedness ( σ ), we demonstrate that (1) σ captures an essential aspect of the growth dynamics and (2) highlight the meteoric rise of highly related terms.

We look at the year over year growth in the number of the impact weighted number of publications per MeSH term from 2018 to 2019 and 2019 to 2020 as defined in the methods section.

Fig 1 shows the yearly growth of the impact weighted number of publications per MeSH term. By comparing the growth of the number of publications from the years 2018, 2019 and 2020, we find that the impact factor weighted number of publications has increased by up to a factor of 100 compared to the previous year for Betacoronavirus, one of the most closely related to COVID-19 MeSH term.

Each dot represents, a MeSH term. The y axis (growth) is in symmetric log scale. The x axis shows the COVID-19 relatedness, σ . Note that the position of the dots on the x-axis is the same in the two plots. Below: MeSH term importance gain (PageRank) and their COVID-19 relatedness.

https://doi.org/10.1371/journal.pone.0263001.g001

Fig 1 , first row, reveals how strongly correlated the growth in the IFWN of publication is to the term’s COVID-19 relatedness. For instance, we see that the term ‘Betacoronavirus’ skyrocketed from 2019 to 2020, which is expected given that SARS-CoV-2 is a species of the genus. Conversely, the term ‘Alphacoronavirus’ has not experienced any growth given that it is twin a genus of the Coronaviridae family, but SARS-CoV-2 is not one of its species. Note also the fast growth in the number of publications dealing with ‘Quarantine’. Moreover, MeSH terms that grew significantly from 2018 to 2019 and were not closely related to COVID-19, like ‘Vaping’, slowed down in 2020. From the graph, the picture emerges that publication growth is correlated with COVID-19 relatedness σ and that the growth for less related terms slowed down.

To show that the usage pattern of MeSH terms has changed following the pandemic, we compute the PageRank centrality using graph-tool [ 18 ] as discussed in the Methods section.

Fig 1 , second row, shows the change in the PageRank centrality of the MeSH terms after the pandemic (2019 to 2020, right plot) and before (2018 to 2019, left plot). If there were no change in the general usage pattern, we would expect the variance in PageRank changes to be narrow across the two periods, see (left plot). However, PageRank scores changed significantly more from 2019 to 2020 than from 2018 to 2019, suggesting that there has been a reconfiguration of the network.

To further support this argument, we carry out a DiD regression analysis.

Common trends assumption

As discussed in the Methods section, we need to show that the CTA assumption holds for the DiD to be defined appropriately. We do this by estimating for each month the number of publications and comparing it across treatment groups. This exercise also serves the purpose of a placebo test. By assuming that each month could have potentially been the event’s timing (i.e., the outbreak), we show that January 2020 is the most likely timing of the event. The regression table, as noted earlier, contains over 70 estimated coefficients, hence for ease of reading, we will only show the predicted outcome per month by group (see Fig 2 ). The full regression table with all coefficients is available in the S1 Table .

The y axis is in log scale. The dashed vertical line identifies January 2020. The dashed horizontal line shows the publications in January 2019 for the 0–20% group before the event. This line highlights that the drop happens after the event. The bands around the lines indicate the 95% confidence interval of the predicted values. The results are the output of the Stata margins command.

https://doi.org/10.1371/journal.pone.0263001.g002

Fig 2 shows the predicted number per outcome variable obtained from the panel regression model. These predictions correspond to the predicted value per relatedness group using the regression parameters estimated via the linear panel regression. The bands around the curves are the 95% confidence intervals.

All outcome measures depict a similar trend per month. Before the event (i.e., January 2020), there is a common trend across all groups. In contrast, after the event, we observe a sudden rise for the outcomes of the COVID-19 related treated groups (green and red lines) and a decline in the outcomes for the unrelated group (blue line). Therefore, we can conclude that the CTA assumption holds.

Regression results

Table 3 shows the DiD regression results (see Eq (3) ) for the selected outcome measures: number of publications (Papers), impact factor weighted number of publications (Impact), open access (OA) publications, clinical trial related publications, and publications with existing grants.

https://doi.org/10.1371/journal.pone.0263001.t003

Table 3 shows results for the discrete treatment level version of the DiD model (see Eq (4) ).

Note that the outcome variable is in natural log scale; hence to get the effect of the independent variable, we need to exponentiate the coefficient. For values close to 0, the effect is well approximated by the percentage change of that magnitude.

In both specifications we see that the least related group, drops in the number of publications between 10% and 13%, respectively (first row of Tables 3 and 4 , exp(−0.102) ≈ 0.87). In line with our expectations, the increase in the number of papers published by MeSH term is positively affected by the relatedness to COVID-19. In the discrete model (row 2), we note that the number of documents with MeSH terms with a COVID-19 relatedness between 20 and 80% grows by 18% and highly related terms by a factor of approximately 6.6 (exp(1.88)). The same general pattern can be observed for the impact weighted publication number, i.e., Model (2). Note, however, that the drop in the impact factor weighted output is more significant, reaching -19% for COVID-19 unrelated publications, and related publications growing by a factor of 8.7. This difference suggests that there might be a bias to publish papers on COVID-19 related subjects in high impact factor journals.

https://doi.org/10.1371/journal.pone.0263001.t004

By looking at the number of open access publications (PMC), we note that the least related group has not been affected negatively by the pandemic. However, the number of COVID-19 related publications has drastically increased for the most COVID-19 related group by a factor of 6.2. Note that the substantial increase in the number of papers available through open access is in large part due to journal and editorial policies to make preferentially COVID research immediately available to the public.

Regarding the number of clinical trial publications, we note that the least related group has been affected negatively, with the number of publications on clinical trials dropping by a staggering 24%. At the same time, publications on clinical trials for COVID-19-related MeSH have increased by a factor of 2.1. Note, however, that the effect on clinical trials is not significant in the continuous regression. The discrepancy across Tables 3 and 4 highlights that, especially for trials, the effect is not linear, where only the publications on clinical trials closely related to COVID-19 experiencing a boost.

It has been reported [ 19 ] that while the number of clinical trials registered to treat or prevent COVID-19 has surged with 179 new registrations in the second week of April 2020 alone. Only a few of these have led to publishable results in the 12 months since [ 20 ]. On the other hand, we find that clinical trial publications, considering related MeSH (but not COVID-19 directly), have had significant growth from the beginning of the pandemic. These results are not contradictory. Indeed counting the number of clinical trial publications listing the exact COVID-19 MeSH term (D000086382), we find 212 publications. While this might seem like a small number, consider that in 2020 only 8,485 publications were classified as clinical trials; thus, targeted trials still made up 2.5% of all clinical trials in 2020 . So while one might doubt the effectiveness of these research efforts, it is still the case that by sheer number, they represent a significant proportion of all publications on clinical trials in 2020. Moreover, COVID-19 specific Clinical trial publications in 2020, being a delayed signal of the actual trials, are a lower bound estimate on the true number of such clinical trials being conducted. This is because COVID-19 studies could only have commenced in 2020, whereas other studies had a head start. Thus our reported estimates are conservative, meaning that the true effect on actual clinical trials is likely larger, not smaller.

Research funding, as proxied by the number of publications with grants, follows a similar pattern, but notably, COVID-19-related MeSH terms list the same proportion of grants established before 2019 as other unrelated MeSH terms, suggesting that grants which were not designated for COVID-19 research have been used to support COVID-19 related research. Overall, the number of publications listing a grant has dropped. Note that this should be because the number of publications overall in the unrelated group has dropped. However, we note that the drop in publications is 10% while the decline in publications with at least one grant is 15%. This difference suggests that publications listing grants, which should have more funding, are disproportionately COVID-19 related papers. To further investigate this aspect, we look at whether the grant was old (pre-2019) or appeared for the first time in or after 2019. It stands to reason that an old grant (pre-2019) would not have been granted for a project dealing with the pandemic. Hence we would expect that COVID-19 related MeSH terms to have a lower proportion of old grants than the unrelated group. In models (6) in Table 4 we show that the number of old grants for the unrelated group drops by 13%. At the same time, the number of papers listing old grants (i.e., pre-2019) among the most related group increased by a factor of 3.1. Overall, these results suggest that COVID-19 related research has been funded largely by pre-existing grants, even though a specific mandate tied to the grants for this use is unlikely.

The scientific community has swiftly reallocated research efforts to cope with the COVID-19 pandemic, mobilizing knowledge across disciplines to find innovative solutions in record time. We document this both in terms of changing trends in the biomedical scientific output and the usage of MeSH terms by the scientific community. The flip side of this sudden and energetic prioritization of effort to fight COVID-19 has been a sudden contraction of scientific production in other relevant research areas. All in all, we find strong support to the hypotheses that the COVID-19 crisis has induced a sudden increase of research output in COVID-19 related areas of biomedical research. Conversely, research in areas not related to COVID-19 has experienced a significant drop in overall publishing rates and funding.

Our paper contributes to the literature on the impact of COVID-19 on scientific research: we corroborate previous findings about the surge of COVID-19 related publications [ 1 – 3 ], partially displacing research in COVID-19 unrelated fields of research [ 4 , 14 ], particularly research related to clinical trials [ 5 – 7 ]. The drop in trial research might have severe consequences for patients affected by life-threatening diseases since it will delay access to new and better treatments. We also confirm the impact of COVID-19 on open access publication output [ 1 ]; also, this is milder than traditional outlets. On top of this, we provide more robust evidence on the impact weighted effect of COVID-19 and grant financed research, highlighting the strong displacement effect of COVID-19 on the allocation of financial resources [ 15 ]. We document a substantial change in the usage patterns of MeSH terms, suggesting that there has been a reconfiguration in the way research terms are being combined. MeSH terms highly related to COVID-19 were peripheral in the MeSH usage networks before the pandemic but have become central since 2020. We conclude that the usage patterns have changed, with COVID-19 related MeSH terms occupying a much more prominent role in 2020 than they did in the previous years.

We also contribute to the literature by estimating the effect of COVID-19 on biomedical research in a natural experiment framework, isolating the specific effects of the COVID-19 pandemic on the biomedical scientific landscape. This is crucial to identify areas of public intervention to sustain areas of biomedical research which have been neglected during the COVID-19 crisis. Moreover, the exploratory analysis on the changes in usage patterns of MeSH terms, points to an increase in the importance of covid-related topics in the broader biomedical research landscape.

Our results provide compelling evidence that research related to COVID-19 has indeed displaced scientific production in other biomedical fields of research not related to COVID-19, with a significant drop in (impact weighted) scientific output related to non-COVID-19 and a marked reduction of financial support for publications not related to COVID-19 [ 4 , 5 , 16 ]. The displacement effect is persistent to the end of 2020. As vaccination progresses, we highlight the urgent need for science policy to re-balance support for research activity that was put on pause because of the COVID-19 pandemic.

We find that COVID-19 dramatically impacted clinical research. Reactivation of clinical trials activities that have been postponed or suspended for reasons related to COVID-19 is a priority that should be considered in the national vaccination plans. Moreover, since grants have been diverted and financial incentives have been targeted to sustain COVID-19 research leading to an excessive entry in COVID-19-related clinical trials and the ‘covidisation’ of research, there is a need to reorient incentives to basic research and otherwise neglected or temporally abandoned areas of biomedical research. Without dedicated support in the recovery plans for neglected research of the COVID-19 era, there is a risk that more medical needs will be unmet in the future, possibly exacerbating the shortage of scientific research for orphan and neglected diseases, which do not belong to COVID-19-related research areas.

Limitations

Our empirical approach has some limits. First, we proxy MeSH term usage via search terms using the PubMed EUtilities API. This means that the accuracy of the MeSH term we assign to a given paper is not fully validated. More time is needed for the completion of manually annotated MeSH terms. Second, the timing of publication is not the moment the research has been carried out. There is a lead time between inception, analysis, write-up, review, revision, and final publication. This delay varies across disciplines. Nevertheless, given that the surge in publications happens around the alleged event date, January 2020, we are confident that the publication date is a reasonable yet imperfect estimate of the timing of the research. Third, several journals have publicly declared to fast-track COVID-19 research. This discrepancy in the speed of publication of COVID-19 related research and other research could affect our results. Specifically, a surge or displacement could be overestimated due to a lag in the publication of COVID-19 unrelated research. We alleviate this bias by estimating the effect considering a considerable time after the event (January 2020 to December 2020). Forth, on the one hand, clinical Trials may lead to multiple publications. Therefore we might overestimate the impact of COVID-19 on the number of clinical trials. On the other hand, COVID-19 publications on clinical trials lag behind, so the number of papers related COVID-19 trials is likely underestimated. Therefore, we note that the focus of this paper is scientific publications on clinical trials rather than on actual clinical trials. Fifth, regarding grants, unfortunately, there is no unique centralized repository mapping grant numbers to years, so we have to proxy old grants with grants that appeared in publications from 2010 to 2018. Besides, grant numbers are free-form entries, meaning that PubMed has no validation step to disambiguate or verify that the grant number has been entered correctly. This has the effect of classifying a grant as new even though it has appeared under a different name. We mitigate this problem by using a long period to collect grant numbers and catch many spellings of the same grant, thereby reducing the likelihood of miss-identifying a grant as new when it existed before. Still, unless unique identifiers are widely used, there is no way to verify this.

So far, there is no conclusive evidence on whether entry into COVID-19 has been excessive. However, there is a growing consensus that COVID-19 has displaced, at least temporally, scientific research in COVID-19 unrelated biomedical research areas. Even though it is certainly expected that more attention will be devoted to the emergency during a pandemic, the displacement of biomedical research in other fields is concerning. Future research is needed to investigate the long-run structural consequences of the COVID-19 crisis on biomedical research.

Supporting information

S1 table. common trend assumption (cta) regression table..

Full regression table with all controls and interactions.

https://doi.org/10.1371/journal.pone.0263001.s001

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• 17. Page L, Brin S, Motwani R, Winograd T. The PageRank citation ranking: Bringing order to the web. Stanford InfoLab; 1999.

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• Volume 14, Issue 9
• What is known about nurse retention in peri-COVID-19 and post-COVID-19 work environments: protocol for a scoping review of factors, strategies and interventions
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• http://orcid.org/0000-0003-1737-8678 Laura Buckley 1 ,
• http://orcid.org/0000-0001-7515-6657 Linda McGillis Hall 1 ,
• http://orcid.org/0000-0002-5535-6624 Sheri Price 2 ,
• http://orcid.org/0009-0005-3183-5398 Sanja Visekruna 3 ,
• Candice McTavish 1
• 1 Lawrence Bloomberg Faculty of Nursing , University of Toronto , Toronto , Ontario , Canada
• 2 Faculty of Health Sciences, School of Nursing , Dalhousie University , Halifax , Nova Scotia , Canada
• 3 Faculty of Health Sciences, School of Nursing , McMaster University , Hamilton , Ontario , Canada
• Correspondence to Dr Laura Buckley; laura.buckley{at}mail.utoronto.ca

Introduction The pandemic has highlighted a worsening of nurses’ working conditions and a global nursing shortage. Little is known about the factors, strategies and interventions that improve nurse retention in the peri-COVID and post-COVID time period. An improved understanding of approaches implemented to support and retain nurses will provide a blueprint for sustaining the nursing workforce. The objectives of this scoping review are to investigate and describe the following: (a) factors associated with nurse retention; (b) strategies suggested to support nurse retention and (c) interventions trialled to support nurse retention, during and after the COVID-19 pandemic.

Methods and analysis Medline, Embase, CINAHL and Scopus will be searched. The included studies will be qualitative, quantitative, mixed methods and grey literature studies of nurses including factors, strategies and/or interventions to support nurse retention in the peri-COVID and post-COVID time period (2019 to present) that are in English or can be translated into English. The excluded studies will be those that focus on nurse managers, educators, students or those in advanced practice roles and studies where the population cannot be segmented to identify which data came from nurses. Systematic, scoping reviews and meta-syntheses will be excluded, but their reference lists will be hand-screened for suitable studies. Data will be evaluated for quality and synthesised qualitatively to map the current evidence available. The relevant studies will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews.

Ethics and dissemination Approval for the broader research study, including this scoping review, has been obtained from the university health sciences research board (protocol #00042510). All data for this scoping review will be collected from published literature, and findings will be published in a peer-reviewed journal and presented at relevant conferences.

Trial registration number The protocol was registered on Open Science Framework (4 April 2024) https://doi.org/10.17605/OSF.IO/XWH45 .

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• Human resource management
• Health Workforce

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2024-087948

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STRENGTHS AND LIMITATIONS OF THIS STUDY

This scoping review addresses multiple facets of nurse retention including factors associated with retention, suggested strategies employed to improve retention, and interventions trialled, offering a fulsome understanding of the subject.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines will be employed to provide a structured and transparent approach to the review process, enhancing its reliability and reproducibility.

By searching multiple databases, the scoping review aims to capture a wide range of relevant literature, minimising the risk of missing key studies.

Studies with statistically significant results or positive outcomes related to nurse retention may be more likely to be published, potentially skewing the overall findings.

Given the short timeframe between the start of the pandemic and now, there may be limited studies for inclusion, particularly interventional studies.

Introduction

Prepandemic, research identified high levels of burnout, exhaustion and workplace well-being concerns in nurses globally. 1–4 Nurse turnover has been a persistent issue over the previous decades. 5 6 Nurse turnover is not only costly but has detrimental impacts on both patients and the nurses themselves. 5–9

The pandemic only worsened the global nursing shortage causing policy-makers and healthcare organisations to implement workplace changes and new models of care due to inadequate nurse staffing and further emphasising the importance of retaining nurses in the field. 10 With these changes, the pandemic also brought new and enhanced factors that influenced turnover intention among nurses including fear of infection, even higher patient ratios, and stressful work environments. 11–14

Previously identified strategies and interventions to address nurse turnover included enhanced salary and benefits, flexible scheduling, positive work environments and professional education opportunities. 15 However, little is known about the factors, strategies and interventions that improve nurse retention in this peri-COVID and post-COVID timeframe. It has yet to be shown if previous practices are relevant and sufficient to combat ongoing nurse turnover in this new context. Due to the changed landscape of the healthcare system emerging from the pandemic, gaining an improved understanding of strategies implemented to support and retain nurses will provide a blueprint for strengthening and sustaining the nursing workforce. A preliminary search of Medline and the Scopus Database of Systematic Reviews, Open Science Framework and PROSPERO was conducted, and no current or ongoing systematic reviews or scoping reviews on the topic were identified. The objective of this scoping review is to assess and organise the extent of the literature on nurse retention in the peri-COVID and post-COVID time. This scoping review will serve as an organised collation of relevant factors, strategies and interventions to support nurse retention that could be used and referenced by healthcare leaders, organisations and policy-makers.

Review question

What is known about nurse retention in peri-COVID-19 and post-COVID-19 work environments?

Study objectives

The objectives of this scoping review are to investigate and describe the following: (a) factors associated with nurse retention; (b) strategies suggested to support nurse retention and (c) interventions trialled to support nurse retention, during and after the COVID-19 pandemic. These objectives will be achieved by systematically mapping the included literature into the three categories of nurse retention factors, strategies and interventions (see online supplemental appendix A for extraction tools). Following this, the included studies will be thematically organised within those categories and presented narratively.

Supplemental material

Methods and analysis.

The scoping review methodology outlined by Arksey and O’Malley 16 and advanced by Levac et al 17 will be employed for this study. Arksey and O’Malley 16 propose a six-step framework for conducting scoping review studies, including the following: (1) identifying the research question; (2) identifying relevant literature; (3) study selection; (4) charting the data; (5) collating, summarising and reporting the articles and (6) consulting and translating knowledge. 16 17 The proposed scoping review results will be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines . 18

Types of sources

This scoping review will consider both experimental and quasi-experimental study designs including randomised controlled trials, non-randomised controlled trials, preobservational and postobservational studies and interrupted time-series studies. In addition, analytical observational studies including prospective and retrospective cohort studies, case-control studies and analytical cross-sectional studies will be considered for inclusion. This review will also take into account descriptive observational study designs including case series, individual case reports and descriptive cross-sectional studies for inclusion. Qualitative studies will also be considered that use, but are not limited to, designs such as phenomenology, grounded theory, ethnography, qualitative description, action research and feminist research. Systematic or scoping reviews and meta-syntheses will be excluded, but their reference lists will be reviewed by hand. Relevant titles and authors within those reference lists will be searched and screened against inclusion/exclusion criteria for potentially relevant studies.

Eligibility criteria

Eligible studies for inclusion in this scoping review will include nurses as their participants (registered nurses (RN), licenced practical nurses (LPN), registered practical nurses (RPN)); they will discuss factors, strategies or interventions related to nurse retention, and they should occur during or post-COVID-19 pandemic (2019–present). The definition of the concept of retention/turnover will be kept broad to include studies that look at a job, unit, organisation, specialty and professional turnover. Eligible articles must be in English or translatable into English. Studies will be excluded if the included nurses cannot be segmented out in the results and if they focus on nursing students nurse leaders, nurse managers or advanced practice nurses (eg, clinical nurse specialists, nurses practitioners) as their duties and responsibilities differ from those of the regular nursing population which may impact their experience of retention. Systematic or scoping reviews and meta-syntheses will be excluded, but their reference lists will be hand-screened for suitable studies. Eligibility criteria are displayed in table 1 .

• View inline

Search strategy

The search strategy will aim to locate both published and unpublished studies. An initial limited search of Medline was undertaken to identify articles on the topic and guide the search strategy development. The text words contained in the titles and abstracts of relevant articles and the index terms used to describe the articles were used to develop a full search strategy for Embase, CINAHL and Scopus. See online supplemental appendix B for an example of the Medline (Ovid) search strategy. The search strategy, including all identified keywords and index terms, will be adapted for each included database and/or information source. A health sciences librarian at the university was consulted throughout the development of the search strategy. The reference list of all included sources of evidence will be screened for additional studies.

Study/source of evidence selection

Following the search, all identified citations will be collated and uploaded into Covidence (Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia), and duplicates removed. 19 Following a pilot test, titles and abstracts will then be screened by two or more independent reviewers for assessment against the inclusion criteria for the review. Potentially, relevant sources will be retrieved in full and their citation details imported into Covidence (Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia). The full text of selected citations will be assessed in detail against the inclusion criteria by two or more independent reviewers. Reasons for exclusion of sources of evidence at full text that do not meet the inclusion criteria will be recorded and reported in the scoping review. Any disagreements that arise between the reviewers at each stage of the selection process will be resolved through discussion or with an additional reviewer/s. The results of the search and the study inclusion process will be reported in full as outlined in the PRISMA-ScR and the final scoping review as well as presented in a PRISMA-ScR flow diagram. 18

Data extraction

Data will be extracted from papers included in the scoping review by two or more independent reviewers using a data extraction tool developed by the reviewers in Microsoft Excel. The following data items will be extracted: title, journal, authors, year of publication, country of publication, study setting, study population (n=), factors that mitigate intent to leave (or other retention measure), strategies identified to address nurse retention, description of interventions used to address nurse retention, tool used to measure retention/turnover intention, retention prevalence and/or scores.

The draft extraction form (see online supplemental appendix A ) will be modified and revised as necessary during the process of extracting data from each included evidence source. Modifications will be detailed in the scoping review. Any disagreements that arise between the reviewers will be resolved through discussion, or with an additional reviewer/s. If appropriate, the authors of papers will be contacted to request missing or additional data, where required.

Critical appraisal of individual sources of evidence: it is expected that there may be a broad range of quality in studies evaluating factors, strategies and interventions for improving nurse retention. Applicable qualitative, quantitative and mixed methods studies will be evaluated using the Mixed Methods Appraisal Tool (MMAT) V.2018. 20 The MMAT allows for the separate methodological evaluation of qualitative research, randomised controlled trials, non-randomised studies, quantitative descriptive studies and mixed methods studies within one appraisal tool. 20

Data analysis and presentation

Data will be synthesised qualitatively to map the current evidence available to address the study’s aims of investigating and describing factors, strategies and interventions that improve nurse retention. Correlational factors presented strategies and tested interventions will be presented in table form and described in narrative form. We anticipate that various turnover and retention measurement approaches will be employed across different studies, which may impede direction comparisons of interventions. Despite these variations, we will strive to accurately represent the outcomes by synthesising the data using standardised metrics where possible and by qualitatively assessing the impact of each intervention within its respective context.

Anticipated review outcomes

In this scoping review, we anticipate identifying a range of outcomes from the included studies that relate to nurse retention during and after the COVID-19 pandemic. These outcomes will be categorised and synthesised according to the following objectives:

Factors associated with nurse retention

Workplace environment: elements such as organisational culture, leadership support, workload and work-life balance.

Psychosocial factors: stress, burnout, job satisfaction, mental health impacts and coping mechanisms.

Demographic factors: age, gender, years of experience and geographical location.

Work outcomes: patient safety, morbidity and mortality.

Strategies suggested to support nurse retention

Subnational and national strategies: policy changes, governmental support and government-driven incentives.

Organisational strategies: policy changes, financial incentives, flexible work arrangements and professional development opportunities.

Individual strategies: resilience training, task rotation, mental health support, mentorship programmes and peer support networks.

Interventions trialled to support nurse retention

Programmatic interventions: implementation of wellness programmes, mentoring and leadership training.

Technological interventions: use of digital tools and telehealth to reduce workload and support patient care.

Policy interventions: changes in staffing policies, staffing ratios, shift patterns and emergency response protocols.

The outcomes identified from the included studies will be synthesised qualitatively. We will map these outcomes against the study objectives to understand the current evidence and gaps in knowledge. The synthesis will focus on common themes, diversity of findings and gaps in the evidence.

Ethics and dissemination

Approval for the broader research study, including this scoping review, has been obtained from the university health sciences research board (protocol #00042510). This study poses no ethical concerns as it involves secondary data analysis and does not involve human subjects or sensitive information. Findings will be disseminated through publication in a peer-reviewed journal and presentation at relevant conferences. Full data from this scoping review will be publicly accessible on request for transparency, accessibility and utilisation to promote further research and knowledge advancement in the field.

Ethics statements

Patient consent for publication.

Not applicable.

Acknowledgments

The study team is acknowledging and thanks Health Sciences Librarian, Mikaela Gray, for her expertise in the creation of this search strategy.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1

Contributors LB, LMH, CM, SP and SV all contributed to the background research to prompt the proposed study, along with the development of the study objectives, search strategies and analysis plan. LB is the guarantor.

Funding Canadian Institutes of Health Research Operating Grant Program (WI2 179956).

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, conducting or reporting or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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Creating A Research Space or CARS

Introduction, what is the cars model, why is this important.

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• Move 1: Establishing a Territory
• Move 2: Establishing a Niche
• Move 3: Occupying the Niche
• Tips for Using the CARS Model

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This guide presents a detailed explanation of the CARS model, a framework that can help you organize your academic writing. It is useful for students and researchers writing introductions for all types of papers, including theses, dissertations, and grant proposals.

The CARS model simplifies writing introductions or proposals by helping you:

• Explain why your research is important
• Show how your work fits with existing research
• Describe the purpose of your paper or proposal

The following sections of this guide will explain each part of the CARS model, accompanied by examples to help you apply it to your writing. This model has proven valuable for many researchers and students, helping them produce clear, strong introductions that adhere to academic standards and emphasize the significance of their work. We hope it will help you, too. 

CARS stands for "Creating a Research Space." It's a framework developed by linguist John Swales that helps you introduce your research in a way that captures your readers' attention and clearly shows your work's place in academic conversation. Think of it as a roadmap for your introduction, guiding you through three essential moves:

• Establishing a Territory
• Establishing a Niche
• Occupying the Niche

Each of these moves has specific steps, which we'll explore in detail. By the end of this guide, you'll have a clear understanding of how to apply the CARS model to your own writing, helping you craft introductions that are both engaging and academically sound.

It's also important to understand what the CARS model is not. Unlike formatting guides or grammar rules, CARS focuses on organizing your introduction's content. It doesn't teach basic writing skills or provide downloadable templates. Instead, it helps you articulate why your research matters, how it fits within existing work, and what you accomplished or hope to accomplish. By following this model, you'll create a compelling narrative for your research, setting the stage for the detailed work that follows.

 A well-crafted introduction is essential because:

• It frames your research by providing context and relevance, helping readers understand why your work matters. 
• It forms the foundation for your study, setting clear expectations for what follows. 
• It enhances the quality and reception of your writing by presenting your ideas in a structured, logical manner. 
• It improves your work's overall coherence and impact by establishing a clear direction from the outset.  

Yet many people find crafting effective introductions to be the most difficult part of academic writing.  

Understanding and using the CARS model is a proven method for crafting effective introductions. It ensures that all the essential elements listed above are effectively communicated.

Moreover, a strong introduction encourages other researchers who find your paper to continue reading your work. This increased engagement can lead to several benefits: 

• Higher likelihood of your full study being read and understood
• Increased potential for your work to be cited by other researchers
• Greater visibility of your research within the academic community
• Potential for broader impact in your field of study

What this means is that by writing a compelling introduction to your paper, you're not just improving that one paper—you're potentially enhancing your contribution to the advancement of knowledge in your field and boosting your academic profile.

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A Review of Coronavirus Disease-2019 (COVID-19)

Tanu singhal.

Department of Pediatrics and Infectious Disease, Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute, Mumbai, India

There is a new public health crises threatening the world with the emergence and spread of 2019 novel coronavirus (2019-nCoV) or the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus originated in bats and was transmitted to humans through yet unknown intermediary animals in Wuhan, Hubei province, China in December 2019. There have been around 96,000 reported cases of coronavirus disease 2019 (COVID-2019) and 3300 reported deaths to date (05/03/2020). The disease is transmitted by inhalation or contact with infected droplets and the incubation period ranges from 2 to 14 d. The symptoms are usually fever, cough, sore throat, breathlessness, fatigue, malaise among others. The disease is mild in most people; in some (usually the elderly and those with comorbidities), it may progress to pneumonia, acute respiratory distress syndrome (ARDS) and multi organ dysfunction. Many people are asymptomatic. The case fatality rate is estimated to range from 2 to 3%. Diagnosis is by demonstration of the virus in respiratory secretions by special molecular tests. Common laboratory findings include normal/ low white cell counts with elevated C-reactive protein (CRP). The computerized tomographic chest scan is usually abnormal even in those with no symptoms or mild disease. Treatment is essentially supportive; role of antiviral agents is yet to be established. Prevention entails home isolation of suspected cases and those with mild illnesses and strict infection control measures at hospitals that include contact and droplet precautions. The virus spreads faster than its two ancestors the SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), but has lower fatality. The global impact of this new epidemic is yet uncertain.

Introduction

The 2019 novel coronavirus (2019-nCoV) or the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) as it is now called, is rapidly spreading from its origin in Wuhan City of Hubei Province of China to the rest of the world [ 1 ]. Till 05/03/2020 around 96,000 cases of coronavirus disease 2019 (COVID-19) and 3300 deaths have been reported [ 2 ]. India has reported 29 cases till date. Fortunately so far, children have been infrequently affected with no deaths. But the future course of this virus is unknown. This article gives a bird’s eye view about this new virus. Since knowledge about this virus is rapidly evolving, readers are urged to update themselves regularly.

Coronaviruses are enveloped positive sense RNA viruses ranging from 60 nm to 140 nm in diameter with spike like projections on its surface giving it a crown like appearance under the electron microscope; hence the name coronavirus [ 3 ]. Four corona viruses namely HKU1, NL63, 229E and OC43 have been in circulation in humans, and generally cause mild respiratory disease.

There have been two events in the past two decades wherein crossover of animal betacorona viruses to humans has resulted in severe disease. The first such instance was in 2002–2003 when a new coronavirus of the β genera and with origin in bats crossed over to humans via the intermediary host of palm civet cats in the Guangdong province of China. This virus, designated as severe acute respiratory syndrome coronavirus affected 8422 people mostly in China and Hong Kong and caused 916 deaths (mortality rate 11%) before being contained [ 4 ]. Almost a decade later in 2012, the Middle East respiratory syndrome coronavirus (MERS-CoV), also of bat origin, emerged in Saudi Arabia with dromedary camels as the intermediate host and affected 2494 people and caused 858 deaths (fatality rate 34%) [ 5 ].

Origin and Spread of COVID-19 [ 1 , 2 , 6 ]

In December 2019, adults in Wuhan, capital city of Hubei province and a major transportation hub of China started presenting to local hospitals with severe pneumonia of unknown cause. Many of the initial cases had a common exposure to the Huanan wholesale seafood market that also traded live animals. The surveillance system (put into place after the SARS outbreak) was activated and respiratory samples of patients were sent to reference labs for etiologic investigations. On December 31st 2019, China notified the outbreak to the World Health Organization and on 1st January the Huanan sea food market was closed. On 7th January the virus was identified as a coronavirus that had >95% homology with the bat coronavirus and > 70% similarity with the SARS- CoV. Environmental samples from the Huanan sea food market also tested positive, signifying that the virus originated from there [ 7 ]. The number of cases started increasing exponentially, some of which did not have exposure to the live animal market, suggestive of the fact that human-to-human transmission was occurring [ 8 ]. The first fatal case was reported on 11th Jan 2020. The massive migration of Chinese during the Chinese New Year fuelled the epidemic. Cases in other provinces of China, other countries (Thailand, Japan and South Korea in quick succession) were reported in people who were returning from Wuhan. Transmission to healthcare workers caring for patients was described on 20th Jan, 2020. By 23rd January, the 11 million population of Wuhan was placed under lock down with restrictions of entry and exit from the region. Soon this lock down was extended to other cities of Hubei province. Cases of COVID-19 in countries outside China were reported in those with no history of travel to China suggesting that local human-to-human transmission was occurring in these countries [ 9 ]. Airports in different countries including India put in screening mechanisms to detect symptomatic people returning from China and placed them in isolation and testing them for COVID-19. Soon it was apparent that the infection could be transmitted from asymptomatic people and also before onset of symptoms. Therefore, countries including India who evacuated their citizens from Wuhan through special flights or had travellers returning from China, placed all people symptomatic or otherwise in isolation for 14 d and tested them for the virus.

Cases continued to increase exponentially and modelling studies reported an epidemic doubling time of 1.8 d [ 10 ]. In fact on the 12th of February, China changed its definition of confirmed cases to include patients with negative/ pending molecular tests but with clinical, radiologic and epidemiologic features of COVID-19 leading to an increase in cases by 15,000 in a single day [ 6 ]. As of 05/03/2020 96,000 cases worldwide (80,000 in China) and 87 other countries and 1 international conveyance (696, in the cruise ship Diamond Princess parked off the coast of Japan) have been reported [ 2 ]. It is important to note that while the number of new cases has reduced in China lately, they have increased exponentially in other countries including South Korea, Italy and Iran. Of those infected, 20% are in critical condition, 25% have recovered, and 3310 (3013 in China and 297 in other countries) have died [ 2 ]. India, which had reported only 3 cases till 2/3/2020, has also seen a sudden spurt in cases. By 5/3/2020, 29 cases had been reported; mostly in Delhi, Jaipur and Agra in Italian tourists and their contacts. One case was reported in an Indian who traveled back from Vienna and exposed a large number of school children in a birthday party at a city hotel. Many of the contacts of these cases have been quarantined.

These numbers are possibly an underestimate of the infected and dead due to limitations of surveillance and testing. Though the SARS-CoV-2 originated from bats, the intermediary animal through which it crossed over to humans is uncertain. Pangolins and snakes are the current suspects.

Epidemiology and Pathogenesis [ 10 , 11 ]

All ages are susceptible. Infection is transmitted through large droplets generated during coughing and sneezing by symptomatic patients but can also occur from asymptomatic people and before onset of symptoms [ 9 ]. Studies have shown higher viral loads in the nasal cavity as compared to the throat with no difference in viral burden between symptomatic and asymptomatic people [ 12 ]. Patients can be infectious for as long as the symptoms last and even on clinical recovery. Some people may act as super spreaders; a UK citizen who attended a conference in Singapore infected 11 other people while staying in a resort in the French Alps and upon return to the UK [ 6 ]. These infected droplets can spread 1–2 m and deposit on surfaces. The virus can remain viable on surfaces for days in favourable atmospheric conditions but are destroyed in less than a minute by common disinfectants like sodium hypochlorite, hydrogen peroxide etc. [ 13 ]. Infection is acquired either by inhalation of these droplets or touching surfaces contaminated by them and then touching the nose, mouth and eyes. The virus is also present in the stool and contamination of the water supply and subsequent transmission via aerosolization/feco oral route is also hypothesized [ 6 ]. As per current information, transplacental transmission from pregnant women to their fetus has not been described [ 14 ]. However, neonatal disease due to post natal transmission is described [ 14 ]. The incubation period varies from 2 to 14 d [median 5 d]. Studies have identified angiotensin receptor 2 (ACE 2 ) as the receptor through which the virus enters the respiratory mucosa [ 11 ].

The basic case reproduction rate (BCR) is estimated to range from 2 to 6.47 in various modelling studies [ 11 ]. In comparison, the BCR of SARS was 2 and 1.3 for pandemic flu H1N1 2009 [ 2 ].

Clinical Features [ 8 , 15 – 18 ]

The clinical features of COVID-19 are varied, ranging from asymptomatic state to acute respiratory distress syndrome and multi organ dysfunction. The common clinical features include fever (not in all), cough, sore throat, headache, fatigue, headache, myalgia and breathlessness. Conjunctivitis has also been described. Thus, they are indistinguishable from other respiratory infections. In a subset of patients, by the end of the first week the disease can progress to pneumonia, respiratory failure and death. This progression is associated with extreme rise in inflammatory cytokines including IL2, IL7, IL10, GCSF, IP10, MCP1, MIP1A, and TNFα [ 15 ]. The median time from onset of symptoms to dyspnea was 5 d, hospitalization 7 d and acute respiratory distress syndrome (ARDS) 8 d. The need for intensive care admission was in 25–30% of affected patients in published series. Complications witnessed included acute lung injury, ARDS, shock and acute kidney injury. Recovery started in the 2nd or 3rd wk. The median duration of hospital stay in those who recovered was 10 d. Adverse outcomes and death are more common in the elderly and those with underlying co-morbidities (50–75% of fatal cases). Fatality rate in hospitalized adult patients ranged from 4 to 11%. The overall case fatality rate is estimated to range between 2 and 3% [ 2 ].

Interestingly, disease in patients outside Hubei province has been reported to be milder than those from Wuhan [ 17 ]. Similarly, the severity and case fatality rate in patients outside China has been reported to be milder [ 6 ]. This may either be due to selection bias wherein the cases reporting from Wuhan included only the severe cases or due to predisposition of the Asian population to the virus due to higher expression of ACE 2 receptors on the respiratory mucosa [ 11 ].

Disease in neonates, infants and children has been also reported to be significantly milder than their adult counterparts. In a series of 34 children admitted to a hospital in Shenzhen, China between January 19th and February 7th, there were 14 males and 20 females. The median age was 8 y 11 mo and in 28 children the infection was linked to a family member and 26 children had history of travel/residence to Hubei province in China. All the patients were either asymptomatic (9%) or had mild disease. No severe or critical cases were seen. The most common symptoms were fever (50%) and cough (38%). All patients recovered with symptomatic therapy and there were no deaths. One case of severe pneumonia and multiorgan dysfunction in a child has also been reported [ 19 ]. Similarly the neonatal cases that have been reported have been mild [ 20 ].

Diagnosis [ 21 ]

A suspect case is defined as one with fever, sore throat and cough who has history of travel to China or other areas of persistent local transmission or contact with patients with similar travel history or those with confirmed COVID-19 infection. However cases may be asymptomatic or even without fever. A confirmed case is a suspect case with a positive molecular test.

Specific diagnosis is by specific molecular tests on respiratory samples (throat swab/ nasopharyngeal swab/ sputum/ endotracheal aspirates and bronchoalveolar lavage). Virus may also be detected in the stool and in severe cases, the blood. It must be remembered that the multiplex PCR panels currently available do not include the COVID-19. Commercial tests are also not available at present. In a suspect case in India, the appropriate sample has to be sent to designated reference labs in India or the National Institute of Virology in Pune. As the epidemic progresses, commercial tests will become available.

Other laboratory investigations are usually non specific. The white cell count is usually normal or low. There may be lymphopenia; a lymphocyte count <1000 has been associated with severe disease. The platelet count is usually normal or mildly low. The CRP and ESR are generally elevated but procalcitonin levels are usually normal. A high procalcitonin level may indicate a bacterial co-infection. The ALT/AST, prothrombin time, creatinine, D-dimer, CPK and LDH may be elevated and high levels are associated with severe disease.

The chest X-ray (CXR) usually shows bilateral infiltrates but may be normal in early disease. The CT is more sensitive and specific. CT imaging generally shows infiltrates, ground glass opacities and sub segmental consolidation. It is also abnormal in asymptomatic patients/ patients with no clinical evidence of lower respiratory tract involvement. In fact, abnormal CT scans have been used to diagnose COVID-19 in suspect cases with negative molecular diagnosis; many of these patients had positive molecular tests on repeat testing [ 22 ].

Differential Diagnosis [ 21 ]

The differential diagnosis includes all types of respiratory viral infections [influenza, parainfluenza, respiratory syncytial virus (RSV), adenovirus, human metapneumovirus, non COVID-19 coronavirus], atypical organisms (mycoplasma, chlamydia) and bacterial infections. It is not possible to differentiate COVID-19 from these infections clinically or through routine lab tests. Therefore travel history becomes important. However, as the epidemic spreads, the travel history will become irrelevant.

Treatment [ 21 , 23 ]

Treatment is essentially supportive and symptomatic.

The first step is to ensure adequate isolation (discussed later) to prevent transmission to other contacts, patients and healthcare workers. Mild illness should be managed at home with counseling about danger signs. The usual principles are maintaining hydration and nutrition and controlling fever and cough. Routine use of antibiotics and antivirals such as oseltamivir should be avoided in confirmed cases. In hypoxic patients, provision of oxygen through nasal prongs, face mask, high flow nasal cannula (HFNC) or non-invasive ventilation is indicated. Mechanical ventilation and even extra corporeal membrane oxygen support may be needed. Renal replacement therapy may be needed in some. Antibiotics and antifungals are required if co-infections are suspected or proven. The role of corticosteroids is unproven; while current international consensus and WHO advocate against their use, Chinese guidelines do recommend short term therapy with low-to-moderate dose corticosteroids in COVID-19 ARDS [ 24 , 25 ]. Detailed guidelines for critical care management for COVID-19 have been published by the WHO [ 26 ]. There is, as of now, no approved treatment for COVID-19. Antiviral drugs such as ribavirin, lopinavir-ritonavir have been used based on the experience with SARS and MERS. In a historical control study in patients with SARS, patients treated with lopinavir-ritonavir with ribavirin had better outcomes as compared to those given ribavirin alone [ 15 ].

In the case series of 99 hospitalized patients with COVID-19 infection from Wuhan, oxygen was given to 76%, non-invasive ventilation in 13%, mechanical ventilation in 4%, extracorporeal membrane oxygenation (ECMO) in 3%, continuous renal replacement therapy (CRRT) in 9%, antibiotics in 71%, antifungals in 15%, glucocorticoids in 19% and intravenous immunoglobulin therapy in 27% [ 15 ]. Antiviral therapy consisting of oseltamivir, ganciclovir and lopinavir-ritonavir was given to 75% of the patients. The duration of non-invasive ventilation was 4–22 d [median 9 d] and mechanical ventilation for 3–20 d [median 17 d]. In the case series of children discussed earlier, all children recovered with basic treatment and did not need intensive care [ 17 ].

There is anecdotal experience with use of remdeswir, a broad spectrum anti RNA drug developed for Ebola in management of COVID-19 [ 27 ]. More evidence is needed before these drugs are recommended. Other drugs proposed for therapy are arbidol (an antiviral drug available in Russia and China), intravenous immunoglobulin, interferons, chloroquine and plasma of patients recovered from COVID-19 [ 21 , 28 , 29 ]. Additionally, recommendations about using traditional Chinese herbs find place in the Chinese guidelines [ 21 ].

Prevention [ 21 , 30 ]

Since at this time there are no approved treatments for this infection, prevention is crucial. Several properties of this virus make prevention difficult namely, non-specific features of the disease, the infectivity even before onset of symptoms in the incubation period, transmission from asymptomatic people, long incubation period, tropism for mucosal surfaces such as the conjunctiva, prolonged duration of the illness and transmission even after clinical recovery.

Isolation of confirmed or suspected cases with mild illness at home is recommended. The ventilation at home should be good with sunlight to allow for destruction of virus. Patients should be asked to wear a simple surgical mask and practice cough hygiene. Caregivers should be asked to wear a surgical mask when in the same room as patient and use hand hygiene every 15–20 min.

The greatest risk in COVID-19 is transmission to healthcare workers. In the SARS outbreak of 2002, 21% of those affected were healthcare workers [ 31 ]. Till date, almost 1500 healthcare workers in China have been infected with 6 deaths. The doctor who first warned about the virus has died too. It is important to protect healthcare workers to ensure continuity of care and to prevent transmission of infection to other patients. While COVID-19 transmits as a droplet pathogen and is placed in Category B of infectious agents (highly pathogenic H5N1 and SARS), by the China National Health Commission, infection control measures recommended are those for category A agents (cholera, plague). Patients should be placed in separate rooms or cohorted together. Negative pressure rooms are not generally needed. The rooms and surfaces and equipment should undergo regular decontamination preferably with sodium hypochlorite. Healthcare workers should be provided with fit tested N95 respirators and protective suits and goggles. Airborne transmission precautions should be taken during aerosol generating procedures such as intubation, suction and tracheostomies. All contacts including healthcare workers should be monitored for development of symptoms of COVID-19. Patients can be discharged from isolation once they are afebrile for atleast 3 d and have two consecutive negative molecular tests at 1 d sampling interval. This recommendation is different from pandemic flu where patients were asked to resume work/school once afebrile for 24 h or by day 7 of illness. Negative molecular tests were not a prerequisite for discharge.

At the community level, people should be asked to avoid crowded areas and postpone non-essential travel to places with ongoing transmission. They should be asked to practice cough hygiene by coughing in sleeve/ tissue rather than hands and practice hand hygiene frequently every 15–20 min. Patients with respiratory symptoms should be asked to use surgical masks. The use of mask by healthy people in public places has not shown to protect against respiratory viral infections and is currently not recommended by WHO. However, in China, the public has been asked to wear masks in public and especially in crowded places and large scale gatherings are prohibited (entertainment parks etc). China is also considering introducing legislation to prohibit selling and trading of wild animals [ 32 ].

The international response has been dramatic. Initially, there were massive travel restrictions to China and people returning from China/ evacuated from China are being evaluated for clinical symptoms, isolated and tested for COVID-19 for 2 wks even if asymptomatic. However, now with rapid world wide spread of the virus these travel restrictions have extended to other countries. Whether these efforts will lead to slowing of viral spread is not known.

A candidate vaccine is under development.

Practice Points from an Indian Perspective

At the time of writing this article, the risk of coronavirus in India is extremely low. But that may change in the next few weeks. Hence the following is recommended:

• Healthcare providers should take travel history of all patients with respiratory symptoms, and any international travel in the past 2 wks as well as contact with sick people who have travelled internationally.
• They should set up a system of triage of patients with respiratory illness in the outpatient department and give them a simple surgical mask to wear. They should use surgical masks themselves while examining such patients and practice hand hygiene frequently.
• Suspected cases should be referred to government designated centres for isolation and testing (in Mumbai, at this time, it is Kasturba hospital). Commercial kits for testing are not yet available in India.
• Patients admitted with severe pneumonia and acute respiratory distress syndrome should be evaluated for travel history and placed under contact and droplet isolation. Regular decontamination of surfaces should be done. They should be tested for etiology using multiplex PCR panels if logistics permit and if no pathogen is identified, refer the samples for testing for SARS-CoV-2.
• All clinicians should keep themselves updated about recent developments including global spread of the disease.
• Non-essential international travel should be avoided at this time.
• People should stop spreading myths and false information about the disease and try to allay panic and anxiety of the public.

Conclusions

This new virus outbreak has challenged the economic, medical and public health infrastructure of China and to some extent, of other countries especially, its neighbours. Time alone will tell how the virus will impact our lives here in India. More so, future outbreaks of viruses and pathogens of zoonotic origin are likely to continue. Therefore, apart from curbing this outbreak, efforts should be made to devise comprehensive measures to prevent future outbreaks of zoonotic origin.

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