research articles 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.

This research received no external funding.

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University Hospital and School of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil

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

School of Nursing, Psychotherapy and Community Health, Dublin City University, Dublin, Ireland

Department of Anesthesiology, Intensive Care and Pain Medicine, University of Münster, Münster, Germany

Thilo Caspar von Groote

Department of Sport and Health Science, Technische Universität München, Munich, Germany

Hebatullah Mohamed Abdulazeem

School of Health Sciences, Faculty of Health and Medicine, The University of Newcastle, Callaghan, Australia

Ishanka Weerasekara

Department of Physiotherapy, Faculty of Allied Health Sciences, University of Peradeniya, Peradeniya, Sri Lanka

Cochrane Croatia, University of Split, School of Medicine, Split, Croatia

Ana Marusic, Irena Zakarija-Grkovic & Tina Poklepovic Pericic

Center for Evidence-Based Medicine and Health Care, Catholic University of Croatia, Ilica 242, 10000, Zagreb, Croatia

Livia Puljak

Cochrane Brazil, Evidence-Based Health Program, Universidade Federal de São Paulo, São Paulo, Brazil

Vinicius Tassoni Civile & Alvaro Nagib Atallah

Yorkville University, Fredericton, New Brunswick, Canada

Santino Filoso

Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, Ontario, Canada

Nicola Luigi Bragazzi

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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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Correspondence to Livia Puljak .

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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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DOI : https://doi.org/10.1186/s12879-021-06214-4

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The COVID-19 pandemic is a rapidly changing situation.  Some of the research included above is preliminary.  Materials listed in this database are selected to provide awareness of quality public health literature and resources. A material’s inclusion does not necessarily represent the views of the U.S. Department of Health and Human Services (HHS), the Public Health Service (PHS), or the Centers for Disease Control and Prevention (CDC), nor does it imply endorsement of the material’s methods or findings.

To access the full text, click on the DOI, PMID, or URL links.  While most publishers are making their COVID-19 content Open Access, some articles are accessible only to those with a CDC user id and password. Find a library near you that may be able to help you get access to articles by clicking the following links: https://www.worldcat.org/libraries OR https://www.usa.gov/libraries .

CDC users can use EndNote’s Find Full Text feature to attach the full text PDFs within their EndNote Library.  CDC users, please email Martha Knuth for an EndNote file of all citations.  Once you have your EndNote file downloaded, to get the full-text of journal articles listed in the search results you can do the following steps:

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The following databases were searched from Dec. 2019-Oct. 9 2020 for articles related to COVID-19: Medline (Ovid and PubMed), PubMed Central, Embase, CAB Abstracts, Global Health, PsycInfo, Cochrane Library, Scopus, Academic Search Complete, Africa Wide Information, CINAHL, ProQuest Central, SciFinder, the Virtual Health Library, and LitCovid.  Selected grey literature sources were searched as well, including the WHO COVID-19 website, CDC COVID-19 website, Eurosurveillance, China CDC Weekly, Homeland Security Digital Library, ClinicalTrials.gov, bioRxiv (preprints), medRxiv (preprints), chemRxiv (preprints), and SSRN (preprints).

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Materials listed in these guides are selected to provide awareness of quality public health literature and resources. A material’s inclusion does not necessarily represent the views of the U.S. Department of Health and Human Services (HHS), the Public Health Service (PHS), or the Centers for Disease Control and Prevention (CDC), nor does it imply endorsement of the material’s methods or findings. HHS, PHS, and CDC assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by HHS, PHS, and CDC. Opinion, findings, and conclusions expressed by the original authors of items included in these materials, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of HHS, PHS, or CDC. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by HHS, PHS, or CDC.

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• Over 760 million cases and 6.9 million deaths have been recorded worldwide since December 2019, but the actual number is thought to be higher.
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COVID-19 is the disease caused by the SARS-CoV-2 coronavirus. It usually spreads between people in close contact.

COVID-19 vaccines provide strong protection against severe illness and death. Although a person can still get COVID-19 after vaccination, they are more likely to have mild or no symptoms.

Anyone can get sick with COVID-19 and become seriously ill or die, but most people will recover without treatment.

People over age 60 and those with existing medical conditions have a higher risk of getting seriously ill. These conditions include high blood pressure, diabetes, obesity, immunosuppression including HIV, cancer and pregnancy. Unvaccinated people also have a higher risk of severe symptoms. 

People may experience different symptoms from COVID-19. Symptoms usually begin 5–6 days after exposure and last 1–14 days.

The most common symptoms are:

• fever 
• sore throat.

Less common symptoms are:

• muscle aches and heavy arms or legs
• severe fatigue or tiredness
• runny or blocked nose, or sneezing
• new and persistent cough
• tight chest or chest pain
• shortness of breath
• hoarse voice
• numbness or tingling
• appetite loss, nausea, vomiting, abdominal pain or diarrhoea
• loss or change of sense of taste or smell
• difficulty sleeping.

People with the following symptoms should seek immediate medical attention:

• difficulty breathing, especially at rest, or unable to speak in sentences
• drowsiness or loss of consciousness
• persistent pain or pressure in the chest
• skin being cold or clammy, or turning pale or a bluish colour
• loss of speech or movement.

People who have pre-existing health problems are at higher risk when they have COVID-19; they should seek medical help early if worried about their condition. These include people taking immunosuppressive medication; those with chronic heart, lung, liver or rheumatological problems; those with HIV, diabetes, cancer. obesity or dementia.

People with severe disease and those needing hospital treatment should receive treatment as soon as possible. The consequences of severe COVID-19 include death, respiratory failure, sepsis, thromboembolism (blood clots), and multiorgan failure, including injury of the heart, liver or kidneys.

In rare situations, children can develop a severe inflammatory syndrome a few weeks after infection. 

Some people who have had COVID-19, whether they have needed hospitalization or not, continue to experience symptoms. These long-term effects are called long COVID (or post COVID-19 condition). The most common symptoms associated with long COVID include fatigue, breathlessness and cognitive dysfunction (for example, confusion, forgetfulness, or a lack of mental focus or clarity). Long COVID can affect a person’s ability to perform daily activities such as work or household chores.  

Most people will recover without needing treatment in a hospital.

For those who need it, doctors will suggest treatments for COVID-19 based on the severity of the disease and the risk of it getting worse. They will consider the person’s age and if they have other health problems.

More on treatment

People should get vaccinated as soon as it’s their turn. They should follow local guidance on vaccination and ways to protect themselves against COVID-19.

COVID-19 vaccines provide strong protection against serious illness, hospitalization and death.

To prevent the spread of COVID-19:

• avoid crowds and keep a safe distance from others, even if they don’t appear to be sick;
• wear a properly fitted mask if you feel sick, have been close to people who are sick, if you are at high-risk, or in crowded or poorly ventilated areas;
• clean your hands frequently with alcohol-based hand rub or soap and water;
• cover your mouth and nose with a bent elbow or tissue when you cough or sneeze;
• dispose of used tissues right away and clean your hands; and 
• if you develop symptoms or test positive for COVID-19, self-isolate until you recover.

Vaccination against COVID-19 is based on priority groups such as people aged 60 years and over, and those with underlying medical problems such as high blood pressure, diabetes, chronic health problems, immunosuppression (including HIV), obesity, cancer, pregnant persons, and unvaccinated people. In March 2023, WHO updated its recommendations on primary series vaccination (two doses of any vaccine) as well as the need for booster doses. These recommendations are time-limited and can change at any time depending on how the SARS-CoV-2 virus is circulating in your area or country. It is important to stay up to date with local guidelines and recommendations provided by your local health authority.

Since its introduction, COVID-19 vaccines have saved millions of lives across the world by providing protection against severe disease, hospitalization, and death. Even though vaccines protect against severe disease and death, it is still possible to spread SARS-CoV-2 to others after being vaccinated.

WHO response

The World Health Organization is the global coordinating agency for the response to the COVID-19 pandemic. The Organization works with Member States and partners on all aspects of the pandemic response, including facilitating research, developing guidance, coordinating vaccine development and distribution, and monitoring daily case numbers and trends around the world.

Since April 2020, the Access to COVID-19 Tools (ACT) Accelerator, launched by WHO and partners, has supported the fastest, most coordinated, and successful global effort in history to develop tools to fight a disease. COVAX, the vaccines pillar of the ACT-Accelerator is a ground-breaking global collaboration to accelerate the development, production, and equitable access to COVID-19 tests, treatments, and vaccines.

WHO provides global coordination and member state support on vaccine safety monitoring. It developed the target product profiles for COVID-19 vaccines and provides R&D technical coordination.

WHO also leads work to improve global capacity and access to oxygen production, distribution and supply to patients.

Although WHO announced the end of the emergency phase of COVID-19 in May 2023, the Organization continues to coordinate the global response.

All information on COVID-19

WHO's work on coronavirus disease

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• 05 May 2021

COVID research: a year of scientific milestones

For just over a year of the COVID-19 pandemic, Nature highlighted key papers and preprints to help readers keep up with the flood of coronavirus research. Those highlights are below. For continued coverage of important COVID-19 developments, go to Nature’s news section .

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Volume 30, Number 7—July 2024

Prevalence of and Risk Factors for Post–COVID-19 Condition during Omicron BA.5–Dominant Wave, Japan

Suggested citation for this article

The increased risk for post–COVID-19 condition after the Omicron-dominant wave remains unclear. This population-based study included 25,911 persons in Japan 20–69 years of age with confirmed SARS-CoV-2 infection enrolled in the established registry system during July–August 2022 and 25,911 age- and sex-matched noninfected controls who used a self-reported questionnaire in January–February 2023. We compared prevalence and age- and sex-adjusted odds ratios of persistent post–COVID-19 symptoms (lasting ≥2 months). We evaluated factors associated with post–COVID-19 condition by comparing cases with and without post–COVID-19 condition. We analyzed 14,710 (8,392 cases and 6,318 controls) of 18,183 respondents. Post–COVID-19 condition proportion among cases was 11.8%, higher by 6.3% than 5.5% persistent symptoms among controls. Female sex, underlying medical conditions, mild to moderate acute COVID-19, and vaccination were associated with post–COVID-19 condition. Approximately 12% had post–COVID-19 condition during the Omicron-dominant wave, indicating the need for longer follow-up.

COVID-19 has caused a significant global disease burden since it was first identified in December 2019; as of May 2024, > 750 million cases had been confirmed, and ≈7.5 million deaths had occurred worldwide ( 1 ). In addition to acute illnesses, the prolonged or recurrent symptoms occurring after an initial infection SARS-CoV-2, referred to as post–COVID-19 condition ( 2 ), have also raised concerns.

More than 65 million persons worldwide have post–COVID-19 conditions ( 3 ). On the basis of estimates of those infected during March 2020–November 2021, a total of 10%–30% of nonhospitalized case-patients and 50%–70% of hospitalized case-patients have had post–COVID-19 condition. Frequently reported symptoms included fatigue, dyspnea, neurocognitive impairment, and loss of smell in patients infected during January 2020–August 2021 ( 4 – 8 ). The risk of developing post–COVID-19 condition was higher in female patients, those with severe acute COVID-19, or those with a greater number of acute symptoms ( 4 , 7 , 9 , 10 ). We noted those results in patients infected with variants before the Omicron variant emerged.

The Omicron variant was identified in November 2021; the BA.5 lineage of that variant was detected in April 2022 and has since spread worldwide. The Omicron variant tends to cause less severe acute symptoms ( 11 ) and has a similar or lower risk for post–COVID-19 condition than the previous variants ( 12 – 16 ). However, most previous studies concerning post–COVID-19 condition in relation to the Omicron variant, except those that used electronic health record data ( 17 ), were hospital-based ( 13 – 15 , 18 – 21 ) or population-based without a control group ( 12 , 16 , 22 , 23 ). Longer sequelae and risks for post–COVID-19 condition in persons infected with the Omicron variant compared with noninfected populations remain unknown. As the number of COVID-19 cases has increased, with greater infectivity of the Omicron variant ( 24 ) in addition reductions in nonpharmaceutical interventions (e.g., lockdowns, social distancing, mask requirements), it is crucial to investigate the potential long-term consequences of infection with the Omicron variant. We conducted a population-based study of symptoms after acute COVID-19 using a self-reported questionnaire in a large city in Japan. Our objective was to examine the increased risk for persistent symptoms after SARS-CoV-2 infection compared with a noninfected population, focusing specifically on the Omicron variant (especially the BA.5 lineage). We also investigated the factors associated with post–COVID-19 condition.

Study Design and Participants

We conducted a population-based study of community-dwelling adults 20–69 years of age who had confirmed SARS-CoV-2 infection during July–August 2022. We extracted data from the Japan Health Center Real-time Information-sharing System on COVID-19 (HER-SYS), the established registry system, and age- and sex-matched controls using a self-reported web-based questionnaire in Shinagawa City, a metropolitan area located in the Tokyo area of Japan. The population of Shinagawa City is ≈400,000 and its population density is 17,700 persons/km 2 .

Japan experienced the 7th wave of COVID-19 in July 2022, caused by the Omicron subvariant BA.5 lineage. The prevalence of the BA.5 lineage increased from 67% in epidemiologic week 27 (July 7–10, 2022) to 92% in epidemiologic week 30 (July 25–31, 2022), becoming dominant ( 25 ). When COVID-19 was diagnosed by a positive reverse transcription PCR or a lateral flow antigen test for SARS-CoV-2 or a clinical diagnosis (for symptomatic close contacts), the attending physician was required to document every case in HER-SYS until September 26, 2022. Patients needed to see a physician to undergo a test for SARS-CoV-2 until the Ministry of Health, Labour, and Welfare approved over-the-counter antigen test kits on August 24, 2022. However, most patients visited a physician even after the over-the-counter antigen test kits became available rather than testing themselves at home. Therefore, most of the infected persons were registered in HER-SYS during the study period.

Figure 1 . Flowchart of participant selection in study of prevalence and risk factors for post–COVID-19 conditions during Omicron BA.5–dominant wave, Japan. Of 29,276 residents 20–69 years of age identified in the municipal...

We selected participants registered in the HER-SYS database who were 20–69 years of age and infected with SARS-CoV-2 during July 1–August 31, 2022. We excluded 3,365 of the 29,276 identified infected residents who had died or moved out of the area and selected the remaining 25,911 infected persons as study participants (infected group). We matched data from HER-SYS and the Basic Resident Registration system (the municipal residence record of the name, birthdate, sex, and address of all residents living in a municipality) to identify noninfected residents who had never been registered in the HER-SYS database during the participant selection. We selected 25,911 age- and sex-matched noninfected persons (noninfected group) from the matched dataset ( Figure 1 ). The ethics committee of the National Center for Global Health and Medicine approved this study (NCGM-S-004571).

We sent research information and invitations to the online questionnaire to the selected participants (25,911 each in the infected and noninfected group) by mail on January 11–13, 2023, approximately 6 months after infection for those who had COVID-19 (cases). Respondents were required to provide consent to participate in the study before accessing the website; those who agreed answered the questionnaire by February 13. At the beginning of the questionnaire, we asked participants if they had a diagnosis of COVID-19. If they answered “yes,” they were directed to the questions for infected persons, which inquired about the number and date of infection episodes. If they answered “no,” “I don’t know,” or “I prefer not to answer,” they were directed to the questions for noninfected persons ( Appendix ). We included persons whose answers on infection status were consistent with HER-SYS data and whose first infection was within the study period.

Post–COVID-19 Condition (Cases) and Persistent Symptoms (Controls)

We asked the participants about the presence of 26 symptoms that emerged during or after the first SARS-CoV-2 infection for cases and in July 2022 for controls. The symptoms were selected from the International Severe Acute Respiratory and Emerging Infection Consortium COVID-19 questionnaire. Symptoms were fever, cough, fatigue, sore throat, chest pain, anorexia, brain fog, difficulty concentrating, anosmia, ageusia, shortness of breath, hair loss, muscle weakness, palpitations, sleep disorder, rhinorrhea, headache, joint pain and swelling, muscle aches, nausea/vomiting, abdominal pain, skin rash, eye-related symptoms, dizziness, erectile dysfunction (male only), and menstrual change (female only) ( 26 ). If a symptom was present, we asked about its timing and duration: whether they had the symptom at illness onset or 3 months after infection (infected group only), whether they had it at the time of the survey, and whether the symptom persisted for ≥2 months. For those who affirmed they had any symptoms, we asked the extent to which the symptoms hindered daily life at the time of response using an 11-point scale from 0 (no effect) to 10 (extreme hindrance) and categorized those responses into 4 levels: 0, no effect; 1–3, mild hindrance; 4–6, moderate hindrance; and 7–10, serious hindrance.

For cases, we defined post–COVID-19 condition according to the World Health Organization (WHO) definition ( 27 ): a symptom that persisted for > 2 months after the acute phase. For brain fog, difficulty concentrating, hair loss, and muscle weakness, we defined post–COVID-19 condition as symptoms having lasted > 2 months during the observation period regardless of the timing because those symptoms develop in the subacute phase ( 17 , 28 ). For controls, we defined persistent symptoms as symptoms lasting > 2 months experienced between July 2022 and the date of the survey.

We asked infected persons about the severity of acute COVID-19 and categorized them into 4 groups according to the WHO clinical severity scale: asymptomatic, mild (symptomatic but not admitted to the hospital), moderate (admitted to the hospital, required supplemental oxygen, or both), and severe (received mechanical ventilation or intensive care admission) ( 29 ). We counted the number of infections because some participants had been infected > 1 time during the observation period. We also asked participants about their demographics (i.e., age at the answering date, sex, height, and weight), underlying medical conditions before the infection (or before July 2022 in the noninfected group), lifestyle, and socioeconomic status (e.g., household income and educational level). We calculated equivalized household income by dividing household income by the square root of the household size. For vaccination status, we extracted the vaccination date, vaccination type, and number of vaccinations from the municipality’s Vaccination Record System. We substituted the questionnaire responses for missing values for 1,589 (10%) respondents (e.g., those who had moved from the original municipality).

Statistical Analysis

We determined the participants’ characteristics according to their infection status and compared them using the t -test for continuous variables and χ 2 test for categorical variables. We calculated the proportions of overall and each post–COVID-19 condition (cases) and persistent symptoms (controls). Using multivariable logistic regression analysis, we calculated the age- and sex-adjusted odds ratios of each symptom in the cases compared with the persistent symptoms in the controls as a reference. We also investigated the risk factors associated with post–COVID-19 condition among cases using multivariate logistic regression models. Model 1 comprised age group and sex; model 2, underlying medical conditions, body mass index, severity, and vaccination status before infection; and model 3, household income and educational level. We conducted multiple imputations using chained equations to account for missing data in model 3; the proportion of missing values in household income was 13.1%. We included all explanatory and outcome variables in the imputation model to create 50 imputed datasets. We also calculated the proportion of influence of post–COVID-19 condition on daily life. We defined statistical significance as a 2-sided p value <0.05. We used Stata version 17 MP software (StataCorp LLC, https://www.stata.com ) for all analyses.

A total of 51,822 persons were invited to participate in the study, of whom 18,183 responded to the questionnaire (response rate 35.1%). The response rate was higher in the infected group than in the noninfected group (37.3% vs. 32.9%, difference of 4.4% [95% CI 3.0%–5.8%]). The response rate was higher among female than male persons in all age groups of both infected and noninfected groups. Among male invitees, the difference in response rates between the infected and noninfected groups was large for age groups in their 50s (12.8% [95% CI 8.1%–17.5%]) and 60s (8.5% [95% CI 1.6%–15.4%]) ( Table 1 ).

We excluded 3,473/18,183 respondents for responses of infectious status inconsistent with HER-SYS (answering different infection statuses or different diagnosis date) and reporting a prior infection and 9 because their records were missing data on age or symptoms. A total of 14,710 participants (8,392 cases and 6,318 controls) were eligible for the analysis ( Figure 1 ). Mean age of all participants was 42.4 (SD 11.7) years; 8,502 (57.8%) participants were female and 6,208 (42.2%) male ( Table 2 ). Mean age of case participants was 42.3 (SD 11.6) years; 4,802 (57.2%) case participants were female and 3,590 (42.8%) male. The mean follow-up period from SARS-CoV-2 infection to the response date was 167.9 (SD 14.5) days. Most cases (8,326 [99.2%] patients) demonstrated asymptomatic to mild disease, whereas 66 (0.8%) cases had moderate to severe disease.

Figure 2 . Prevalence and age- and sex-adjusted odds ratios of persistent symptoms in cases compared with controls in study of prevalence and risk factors for post–COVID-19 conditions during Omicron BA.5–dominant wave, Japan....

The percentage of post–COVID-19 condition for cases was 11.8%, whereas the percentage of persistent symptoms among controls was 5.5% ( Figure 2 ). The prevalence did not differ between cases under follow-up for <6 months (11.6%) and cases under follow-up for > 6 months (12.6%). The most frequent post–COVID-19 condition was cough (3.7%), followed by difficulty concentrating (3.1%), hair loss (2.8%), fatigue (2.4%), and brain fog (2.2%). The most frequent persistent symptoms among the controls were sleep disorders (1.3%), followed by cough (0.9%), fatigue (0.7%), and rhinorrhea (0.7%). The age- and sex-adjusted odds ratio (OR) of any persistent symptoms for cases versus controls was 2.33 (95% CI 2.05–2.64). Symptoms with higher OR in cases than controls were ageusia (27.4 [95% CI 6.7–111.8]), muscle weakness (11.8 [95% CI 5.5–25.5]), anosmia (11.6 [95% CI 4.7–28.6]), hair loss (6.5 [95% CI 4.4–9.6]), and brain fog (5.9 [95% CI 3.8–9.0]).

We conducted multivariable logistic regression analysis to investigate the factors associated with post–COVID-19 condition among cases ( Table 3 ). In all 3 models, participants 40–49 years of age had higher odds of having post–COVID-19 condition than those 20–29 years (OR 1.26, 95% CI 1.01–1.57 for model 3); female participants had higher odds of having post–COVID-19 condition than male participants (OR 2.00, 95% CI 1.71–2.34). When models were further adjusted, 2 variables were associated with having post–COVID-19 condition: having any underlying medical conditions (OR 1.36, 95% CI 1.16–1.59, compared with no underlying medical conditions), and severity of acute COVID-19 (mild, OR 2.07, 95% CI 1.18–3.66; moderate, OR 4.49, 95% CI 1.97–10.23, compared with asymptomatic). Those participants vaccinated before infection had lower odds of developing post–COVID-19 condition (OR 0.75, 95% CI 0.60–0.95, compared with unvaccinated). Socioeconomic status, including household income and educational level, was not associated with post–COVID-19 condition.

Among the 992 cases who had experienced any post–COVID-19 condition, 84 (8.5%) answered that the condition was a serious hindrance on their daily lives at the time of response. A total of 402 (40.5%) noted that it was no hindrance, 362 (36.5%) mild hindrance, and 144 (14.5%) moderate hindrance.

We conducted a population-based study using a self-reported questionnaire among adults in Japan who had confirmed SARS-CoV-2 infection during July–August 2022, when the Omicron BA.5 subvariant was dominant. We compared their post–COVID-19 condition with concordant persistent symptoms among noninfected controls. The percentage of post–COVID-19 condition was 11.8% for cases, which was 2.3 times higher than the 5.5% of persistent symptoms noted in controls. The cases had a 6.2% higher prevalence of post–COVID-19 condition than the controls, suggesting that their symptoms were likely associated with SARS-CoV-2 infection.

Population-based studies of infected persons in the United Kingdom (n = 56,003) and the United States (n = 1,480) using smartphone applications reported that the prevalence of post–COVID-19 condition associated with the Omicron variant, defined as symptoms lasting 4 weeks after the infection, was 4.5%–18.7% ( 12 , 23 ). Another population-based study of infected persons in the United States (n = 16,091) showed a prevalence of 11.2% ( 16 ) applying the WHO definition of the continuation or development of new symptoms 3 months after the initial SARS-CoV-2 infection, with those symptoms lasting for > 2 months with no other explanation ( 27 ). Although the definition of post–COVID-19 condition varies among previous studies ( 12 , 16 , 23 , 27 ), the proportion shown in our study is consistent with previous results. In those reports, post–COVID-19 condition was less prevalent among those infected during the Omicron variant–dominant wave than those infected during the previous waves with the ancestral strain predominance ( 16 , 23 ). However, although a multicenter prospective cohort study showed a higher proportion of prolonged severe fatigue and multiple symptoms at 3 months during the pre-Delta wave than that during the Delta and Omicron waves, the differences disappeared after accounting for sociodemographics and vaccination status ( 19 ). Systematic reviews suggested that vaccination before infection was associated with a lower risk of experiencing post–COVID-19 condition ( 30 , 31 ). Similarly, we found that vaccination before infection was associated with lesser post–COVID-19 condition. An in-depth study would clarify whether the reduced risk for post–COVID-19 condition during the Omicron wave was a result of the differences in strains, the effect of vaccination, or both.

Population-based large cohort studies in the United Kingdom (n = 606,434 and n = 486,149) and Germany (n = 11,710) reported that patients infected with previous-variant SARS-CoV-2 frequently experienced persistent symptoms such as fatigue, shortness of breath, concentration difficulties, memory disturbance, hair loss, and anosmia ( 5 , 7 , 32 ). Studies on patients infected with the Omicron variant, including a population-based study in the United States (n = 16,091) and hospital-based studies from China (n = 1,829) and India (n = 524), revealed that fatigue, brain fog, cough, and shortness of breath were frequently observed as post–COVID-19 condition ( 13 , 16 , 33 ). Our findings were comparable with previous results; we observed that post–COVID-19 condition after the Omicron-dominant epidemic frequently included neurologic symptoms such as difficulty concentrating, fatigue, and brain fog, in addition to cough and hair loss. In addition, those neurologic symptoms, as well as ageusia, anosmia, and muscle weakness, were distinctive symptoms among cases, who showed a higher OR than controls. Fatigue and neurocognitive impairment are reportedly related to impaired health recovery and reduced working capacity, even among young and middle-aged adults, after mild infection ( 7 ). Our results showed that ≈10% of those who had post–COVID-19 condition had persistent difficulties in daily living 4.5–7 months after the Omicron-dominant wave, which may have led to a deterioration in economic conditions or work productivity. Although background socioeconomic status was not associated with developing post–COVID-19 condition in this study, further investigation is required to evaluate the effect of post–COVID-19 condition on changes in economic conditions, schooling, and employment.

Large-scale population-based cohort studies on infection before the Omicron wave found that post–COVID-19 condition was more common in female persons, smokers, persons with obesity, those with more severe acute COVID-19 symptoms, and those who were deprived or had lower household income ( 5 , 7 , 32 ). Moreover, hospital-based studies in China (n = 21,799) and South Africa (n = 4,685) showed that the female sex, concurrent conditions, and severe acute illnesses were associated with post–COVID-19 condition in association with the Omicron variant ( 14 , 21 ), which was consistent with our findings. Although the results regarding age are unclear, some studies on the Omicron variant have suggested that the population 18–50 years of age has a higher risk for post–COVID-19 condition ( 21 , 34 ). Our study showed that post–COVID-19 condition for those infected during the Omicron-dominant epidemic was also more prevalent in middle-aged persons. A substantial proportion of the working-age population might have been affected; of 9 million persons infected during July–August 2022 in Japan, 31.2% were in their 30s and 40s ( 35 ).

The strengths of this study are the large number of participants including noninfected controls, the population-based approach, and the inclusion of all infected residents registered in the HER-SYS database within a municipality. We compared the infected persons with noninfected persons as a control and assessed the proportion of post–COVID-19 condition after the Omicron-dominant wave.

The first limitation of this study is that the response rate was higher among the infected group than the noninfected group overall. The infected participants may have been more interested in the survey on COVID-19 and post–COVID-19 condition. However, because we did not specify the purpose of the survey to investigate the post–COVID-19 condition but rather informed the participants that we aimed to investigate the effect of the pandemic on their health and daily lives, we believe that the influence of interest in post–COVID-19 condition on the responses to the questionnaire was small. Moreover, the response rate was higher for infected and noninfected female participants and middle-aged infected male participants; this finding could have been because those persons were inherently willing to answer questionnaires more than other persons, or because patients with those attributes (such as female sex and middle age) suffered more from persistent symptoms and had a higher motivation to answer the questionnaire. The results could be biased in both ways; however, we believe the effect was small because the higher odds of having post–COVID-19 condition in our study were consistent with findings from previous studies. Second, although we excluded those who self-reported having SARS-CoV-2 infection, it is possible that some infected persons were included in the controls, causing an underestimation of the difference in persistent symptoms between the cases and controls. Third, because the study was retrospective, recall bias may have occurred. In addition, because we relied on self-reporting, we could not rule out the possibility that the participants’ symptoms were caused by conditions other than COVID-19. However, we estimated the symptoms attributable to COVID-19 by comparing with a noninfected control group. Finally, although this study included all infected persons registered in the nationally established registry system, caution is needed to generalize the results of this single-city analysis to other populations in Japan.

In this population-based study, 11.8% of patients with COVID-19 had post–COVID-19 condition during the Omicron-dominant wave; this rate was 2.3 times higher than the persistent symptoms among noninfected controls. Among the cases, female sex, underlying medical conditions, and severity of acute COVID-19 were associated with having post–COVID-19 condition. We recommend a longer follow-up study of the effects on daily life and socioeconomic status after infection during the Omicron-dominant wave.

Dr. Iba is a senior research fellow at the Institute for Global Health Policy Research, Bureau of International Health Cooperation, National Center for Global Health and Medicine, Tokyo, Japan. Her research focuses on epidemiology and health services research.

Acknowledgments

We thank Keiko Fukuuchi, Atsuko Abe, Shoji Sakano, and the staff of Shinagawa City Public Health Center for their cooperation in conducting this study.

This work was supported by MHLW Research on Emerging and Re-emerging Infectious Diseases and Immunization (program grant no. JPMH21HA2011).

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• Figure 1 . Flowchart of participant selection in study of prevalence and risk factors for post–COVID-19 conditions during Omicron BA.5–dominant wave, Japan. Of 29,276 residents 20–69 years of age identified in the...
• Figure 2 . Prevalence and age- and sex-adjusted odds ratios of persistent symptoms in cases compared with controls in study of prevalence and risk factors for post–COVID-19 conditions during Omicron BA.5–dominant wave,...
• Table 1 . Response rates of persons in study of prevalence and risk factors for post–COVID-19 conditions during BA.5 Omicron-dominant wave, Japan
• Table 2 . Characteristics of participants in study of prevalence and risk factors for post–COVID-19 conditions during BA.5 Omicron-dominant wave, Japan
• Table 3 . Factors associated with the prevalence and risk factors for post–COVID-19 conditions during BA.5 Omicron-dominant wave, Japan

Suggested citation for this article : Iba A, Hosozawa M, Hori M, Muto Y, Muraki I, Masuda R, et al. Prevalence of and risk factors for post–COVID-19 condition during Omicron BA.5–dominant wave, Japan. Emerg Infect Dis. 2024 Jul [ date cited ]. https://doi.org/10.3201/eid3007.231723

DOI: 10.3201/eid3007.231723

Original Publication Date: June 14, 2024

Table of Contents – Volume 30, Number 7—July 2024

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Months after being diagnosed with COVID-19, one in five people are still suffering from symptoms, new research finds

One in five adults infected with COVID-19 may still be suffering its effects months after their diagnosis, according to new research out of the United States. 

An investigation by more than two dozen researchers found while the average time of recovery was 20 days, an estimated 22.5 per cent failed to recover 90 days after infection. 

The report, based out of the United States and published in the Journal of the American Medical Association, mirrored recent reporting by Australian researchers. 

The peer-reviewed study used data from the Collaborative Cohort of Cohorts for COVID-19 Research (C4R), a long-term collaboration of 14 different studies across the US.

Some of the studies have been following its own participants for up to 50 years, meaning they can now compare their health pre- and post-COVID-19 diagnosis.

A total of 4,708 participants were asked whether they were "completely recovered from COVID-19". 

Once they confirmed their recovery, they were asked how long it had taken.

"[We] found that one in five adults infected with SARS-CoV-2 did not fully recover by three months post-infection in a racially and ethnically diverse US population-based sample," the report said.

"Recovery by 90 days was less likely in women and participants with pre-pandemic clinical cardiovascular disease.

"Vaccination prior to infection and infection during the Omicron variant wave were associated with greater recovery … results were similar for reinfections."

The research team noted the results may have been limited by the self-reported recovery time and the "potential for measurement error, uncontrolled confounding and selection bias".

Dr Mulu Abraha Woldegiorgis, a researcher at the Australian National University (ANU), told the ABC it was "interesting" to see the findings classified by "before and after Omicron".

"The prevalence [of long COVID] during Omicron was the same as ours," she said. 

"They use slightly different definitions and methodology, but even with that the prevalence was high. It shows us that long COVID is still a public health concern globally." 

Long COVID 'not just cough, or tiredness' 

Four years after the beginning of the pandemic, much about "long COVID" remains a mystery for health officials.

Earlier this year Queensland's chief health officer called for the term  "long COVID" to be scrapped despite stating the symptoms were "real". 

"Using this term long COVID implies this virus has some unique, exceptional and sinister property that differentiates it form other viruses," Dr John Gerrard said. 

"I want to make it clear that the symptoms that some patients describe after having COVID-19 are real. We believe they are real." 

A study of more than 11,000 Australians who had tested positive for COVID-19 has had similar results — almost one in five were still experiencing symptoms three months after a 2022 diagnosis. 

The joint ANU and Western Australia Department of Health study, released in March, found 90 per cent of participants with long COVID were suffering multiple symptoms. 

Tiredness, fatigue, "brain fog", sleep problems, coughing, and changes in their menstrual cycle were frequently reported. 

"Among respondents with long COVID who had worked or studied prior to their infection, 15.2 per cent had reduced their number of hours, and 2.7 per cent had not returned to work at all," the report said. 

The researchers also noted long COVID was more prevalent in its sample than the levels reported by other studies in the United Kingdom and Canada. 

Dr Woldegiorgis was the lead researcher on the ANU report. She said Australia presented a "unique" cohort of highly vaccinated people. 

"You have multiple symptoms, it's not just cough, or tiredness, they have multiple symptoms and that affects them," she said. 

"A longer term assessment is important. What we saw was by 90 days, so a long term follow-up may provide additional information on how people are going in a year or two.  

"What's the recovery period? Are they recovering soon or is the term longer?" 

The report also found those who had been vaccinated were less at risk of developing long COVID. 

"I want to stress the importance of vaccination," Dr Woldegiorgis said.

"In Australia the vast majority were vaccinated ... at least one dose prevents long COVID compared to no vaccination." 

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Gender, immunological response, and covid-19: an assessment of vaccine strategies in a pandemic region of oaxaca, méxico.

1. Introduction

2. materials and methods, 2.1. study population, inclusion criteria, and vaccines, 2.2. sample collection, 2.3. the enzyme-linked immunosorbent assay (elisa), 2.4. statistical analysis, 4. discussion, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Rodríguez-Martínez, L.M.; Chavelas-Reyes, J.L.; Medina-Ramírez, C.F.; Cabrera-Santos, F.J.; Fernández-Santos, N.A.; Aguilar-Durán, J.A.; Pérez-Tapia, S.M.; Rodríguez-González, J.G.; Rodríguez Pérez, M.A. Gender, Immunological Response, and COVID-19: An Assessment of Vaccine Strategies in a Pandemic Region of Oaxaca, México. Microbiol. Res. 2024 , 15 , 1007-1015. https://doi.org/10.3390/microbiolres15020066

Rodríguez-Martínez LM, Chavelas-Reyes JL, Medina-Ramírez CF, Cabrera-Santos FJ, Fernández-Santos NA, Aguilar-Durán JA, Pérez-Tapia SM, Rodríguez-González JG, Rodríguez Pérez MA. Gender, Immunological Response, and COVID-19: An Assessment of Vaccine Strategies in a Pandemic Region of Oaxaca, México. Microbiology Research . 2024; 15(2):1007-1015. https://doi.org/10.3390/microbiolres15020066

Rodríguez-Martínez, Luis M., José L. Chavelas-Reyes, Carlo F. Medina-Ramírez, Francisco J. Cabrera-Santos, Nadia A. Fernández-Santos, Jesús A. Aguilar-Durán, Sonia M. Pérez-Tapia, Josefina G. Rodríguez-González, and Mario A. Rodríguez Pérez. 2024. "Gender, Immunological Response, and COVID-19: An Assessment of Vaccine Strategies in a Pandemic Region of Oaxaca, México" Microbiology Research 15, no. 2: 1007-1015. https://doi.org/10.3390/microbiolres15020066

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FDA offers new guidelines for Covid-19 vaccine

By Meghana Keshavan June 17, 2024

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Hello! Today, we talk about the uptick in physicians using ctDNA to determine if resected cancers are truly gone, we see the FDA offering new guidelines for Covid-19 vaccines, and more.

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The need-to-know this morning

• Takeda  reported  negative results  from two Phase 3 studies investigating the use of an experimental drug called soticlestat for the treatment of Dravet syndrome and Lennox-Gastaut syndrome — rare forms of epilepsy. Shares of Ovid Therapeutics, which had  licensed soticlestat to Takeda , fell sharply in early trading.

More physicians are using ctDNA tests

Clinicians are increasingly using blood tests that measure circulating tumor DNA, or ctDNA, to figure out whether any cancerous cells remain after a malignancy is removed. One of the most popular ctDNA diagnostics is the Signatera test made by Natera; revenue for the company was up 52% in the last year.

“We are all recognizing that if a patient has detectable circulating tumor DNA, it’s not a question of if the cancer’s coming back, but when,” one oncologist told STAT’s Angus Chen. “The field recognizes the power of this tool, but I think there remain many questions of how best do we utilize that in the day-to-day management of patients.”

From STAT’s Helen Branswell:  The Food and Drug Administration has changed its advice to Covid-19 vaccine manufacturers, asking them to target the KP.2 subvariant of the virus in their fall boosters, if they are able. Earlier this month an FDA expert panel recommended the  fall shots should target the JN.1 subvariant, from which KP.2 derives . After that meeting of the Vaccines and Related Biological Products Advisory Committee, the agency told manufacturers to target the JN.1 virus. But late last week, the  FDA changed its advice , hoping to more closely align the fall shots to the circulating viruses.

Both Pfizer and Moderna indicated that they could make vaccine targeting either version of the virus, and still deliver their doses in August. But Novavax’s production process takes longer; at the early June meeting of the expert panel, the company said it could only make JN.1 vaccine for this fall. Novavax started making doses targeting JN.1 after the WHO recommended that version of the virus for fall shots in late April. On Friday, the company announced it had filed an application for its updated shot with the FDA.

The chair of the WHO’s coronavirus vaccine panel told the VRBPAC meeting  that it’s hard to gauge at this point whether JN.1 or KP.2 would offer better protection next winter, given the continued evolution of the virus. “KP.2 may be better. But it could also be worse,” said David Wentworth, who also heads the coronavirus division at the Centers for Disease Control and Prevention.

USPTO seeks to prevent patent thickets

The U.S. Patent and Trademark Office has proposed a new way to prevent pharma companies from using patent thickets to postpone generic drugs from making it to market. The potential new rule has to do with “terminal disclaimers,” which allow branded drugmakers to skirt rules and, in essence, get more than one patent for an invention.

Under the proposed rule, if a key patent is later invalidated either through patent infringement litigation in court or a PTO board ruling, the brand-name drug company would agree not to enforce any of the other patents that were linked by the terminal disclaimer.

“In one fell swoop, it can make a difference, and would address patent thickets,” one pharma patent expert told STAT. “Instead of having to challenge, say, 100 different patents, I just have to figure out how they are linked together and try to invalidate the weakest claim.”

Why Disc Medicine’s shares jumped last week

Shares in Disc Medicine  jumped  about 18% Friday after two bits of news: It announced a  stock offering  priced at $36 per share, with aims to raise $178 million. And it announced positive data for three clinical-stage programs during the European Hematology Association meeting last week.

The Boston-area company is developing a drug called bitopertin for erythropoietic protoporphyria, a rare disease that causes photosensitivity and liver problems. Phase 2 results showed significant reductions in a substance called protoporphyrin IX, which increases in patients with the rare blood disease. A Phase 1b/2a study also showed promise in myelofibrosis, and a Phase 1 trial also demonstrated safety and efficacy among healthy volunteers.

• Colorado board decides a pricey Novartis medicine is unaffordable,  STAT
• Novo Nordisk CEO agrees to Bernie Sanders’ demand to testify on Ozempic, Wegovy prices,  STAT
• EU regulator requires secondary cancer risk warning for CAR-T therapies,  Reuters

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The Morning

Two covid theories.

Was the pandemic started by a lab leak or by natural transmission? We look at the evidence.

By David Leonhardt

The origin of the Covid virus remains the pandemic’s biggest mystery. Did the virus jump to human beings from animals being sold at a food market in Wuhan, China? Or did the virus leak from a laboratory in Wuhan?

U.S. officials remain divided. The F.B.I. and the Department of Energy each concluded that a lab leak was the more likely cause. The National Intelligence Council and some other agencies believe that animal-to-human transmission is more likely. The C.I.A. has not taken a position. The question remains important partly because it can inform the strategies to reduce the chances of another horrific pandemic.

A recent Times Opinion essay — by Alina Chan, a biologist — refocused attention on the issue by making the case for the lab-leak theory . In today’s newsletter, I’ll try to lay out the clearest arguments for each side to help you decide which you consider more likely.

The case for natural transmission

1. It’s the norm.

Covid is part of the coronavirus family, so named because the virus contains a protein shaped like a spike. (Corona is the Latin word for crown.) In recent decades, the main way that coronaviruses have infected people is through animal-to-human transmission, which is also known as natural transmission.

The SARS virus, for example, appears to have jumped from civet cats, a relative of the mongoose, to humans in Asia in 2002. MERS seems to have jumped from camels to people in the Middle East around 2012. There is no previous example of a major coronavirus originating with a lab leak.

When you’re trying to choose between a historically common explanation for a phenomenon and an unusual explanation, the common one is usually the better bet.

Key evidence of Covid’s origins is still missing

Infected animals found

Earliest known cases

exposed to live animals

Antibody evidence of

animals and animal traders

having been infected

Ancestral variants of the virus

found in animals

Documented trade of

host animals between

the area where bats carry

closely related viruses

and the outbreak site

Earliest known cases exposed to live animals

Antibody evidence of animals and

animal traders having been infected

Ancestral variants of the virus found in animals

Documented trade of host animals

between the area where bats carry

closely related viruses and the outbreak site

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• v.25(15); 2020 Apr 16

Coronavirus disease (COVID-19): a scoping review

1 School of Public Health, Lanzhou University, Lanzhou, China

2 These authors contributed equally to this work and share first authorship

3 Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China

Janne Estill

4 Institute of Global Health, University of Geneva, Geneva, Switzerland

5 Institute of Mathematical Statistics and Actuarial Science, University of Bern, Bern, Switzerland

Mengjuan Ren

Jianjian wang.

6 Department of Health Research Methods, Evidence and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Canada

Xiaohui Wang

7 College of Medical Information Engineering, Chengdu University of Traditional Chinese Medicine, Chengdu, China

8 School of Public Health, Chengdu Medical College, Chengdu, China

9 Department of Respiratory Diseases, Children’s Hospital of Chongqing Medical University, Chongqing, China

10 Chongqing Key Laboratory of Pediatrics, Chongqing, China

Xianzhuo Zhang

11 The First School of Clinical Medicine, Lanzhou University, Lanzhou, China

12 The First Hospital of Lanzhou University, Lanzhou, China

Xiaolong Qi

Yangqin xun, yaolong chen.

13 World Health Organization (WHO) Collaborating Centre for Guideline Implementation and Knowledge Translation, Lanzhou, China

14 Guideline International Network Asia, Lanzhou, China

15 Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou University, Lanzhou, China

16 Lanzhou University, an affiliate of the Cochrane China Network, Lanzhou, China

on behalf of the COVID-19 evidence and recommendations working group

17 The study collaborators are acknowledged at the end of the article

Associated Data

In December 2019, a pneumonia caused by a novel coronavirus (SARS-CoV-2) emerged in Wuhan, China and has rapidly spread around the world since then.

This study aims to understand the research gaps related to COVID-19 and propose recommendations for future research.

We undertook a scoping review of COVID-19, comprehensively searching databases and other sources to identify literature on COVID-19 between 1 December 2019 and 6 February 2020. We analysed the sources, publication date, type and topic of the retrieved articles/studies.

We included 249 articles in this scoping review. More than half (59.0%) were conducted in China. Guidance/guidelines and consensuses statements (n = 56; 22.5%) were the most common. Most (n = 192; 77.1%) articles were published in peer-reviewed journals, 35 (14.1%) on preprint servers and 22 (8.8%) posted online. Ten genetic studies (4.0%) focused on the origin of SARS-CoV-2 while the topics of molecular studies varied. Nine of 22 epidemiological studies focused on estimating the basic reproduction number of COVID-19 infection (R 0 ). Of all identified guidance/guidelines (n = 35), only ten fulfilled the strict principles of evidence-based practice. The number of articles published per day increased rapidly until the end of January.

The number of articles on COVID-19 steadily increased before 6 February 2020. However, they lack diversity and are almost non-existent in some study fields, such as clinical research. The findings suggest that evidence for the development of clinical practice guidelines and public health policies will be improved when more results from clinical research becomes available.

Introduction

A new type of coronavirus (severe acute respiratory syndrome coronavirus 2; SARS-CoV-2) that began in Wuhan, China in late 2019 has spread across the world since then. The virus has caused an outbreak of viral pneumonia, which has been named Coronavirus disease (COVID-19). As of 24:00 on 6 February 2020, over 31,000 cases and 636 deaths had been confirmed in China [ 1 ]. Furthermore, more than 1,770,000 cases had been diagnosed in 213 countries, areas or territories as at 13 April 2020 [ 2 ]. On 23 January 2020, Chinese authorities imposed a lockdown of Wuhan [ 3 ]. On 30 January 2020, the World Health Organization (WHO) declared the outbreak a Public Health Emergency of International Concern (PHEIC) [ 4 ] and on 11 March 2020, a pandemic [ 5 ].

The WHO [ 6 - 9 ], the United States (US) Centers for Disease Control and Prevention (CDC) [ 10 , 11 ], the European Centre for Disease Prevention and Control (ECDC) [ 12 , 13 ] as well as Chinese researchers have issued several guidance documents or guidelines to help address the outbreaks. Meanwhile, many scientific journals have rapidly published a number of articles, comments, editorials and perspectives related to COVID-19. It may however be challenging for the global research community to find all the available evidence: many of the first studies on COVID-19 were published in Chinese, and because of the rapidly developing situation, the latest studies are often available on websites or preprint servers only [ 14 ].

Scoping reviews are regarded as a valid tool to map the available evidence on a given topic, to clarify the characteristics of body of literature, to organise the key concepts and their relationship and to analyse knowledge gaps [ 15 ]. The methodology continues to be developed, and a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRSIMA) extension for Scoping Reviews (PRISMA-SCR) including reporting guidance was published in 2018 [ 16 ]. Given the urgency of the COVID-19 epidemic and the need to understand and access information about it, a scoping review was considered suitable for the situation. We therefore conducted this scoping review to help identify research gaps related to this new viral disease and propose recommendations for future research on COVID-19.

Search strategy

We performed a systematic search of MEDLINE via PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data and China Biology Medicine (CBM) on 27 February 2020 with the terms “COVID-19” OR “SARS-CoV-2” OR “2019 novel coronavirus” OR “2019-nCoV” OR “Wuhan coronavirus” OR “novel coronavirus” OR “Wuhan seafood market pneumonia virus” OR “Wuhan virus”, published between 1 December 2019 and 6 February 2020 (see Supplement S1 for details of search strategies). Because of potential delays in indexing of databases, we also searched selected infectious disease journals ( Supplementary Table S1 ). We also searched Google Scholar; the official websites of WHO ( https://www.who.int/ ), US CDC ( https://www.cdc.gov/ ), ECDC ( https://www.ecdc.europa.eu/en ), Public Health England (PHE) ( https://www.gov.uk/government/organisations/public-health-england ); some preprint servers, including BioRxiv ( https://www.biorxiv.org/ ), ChemRxiv ( https://chemrxiv.org/ ), medRxiv ( https://www.medrxiv.org/ ) and SSRN ( https://www.ssrn.com/index.cfm/en/ ); and reference lists of the identified articles to find reports of additional studies.

Inclusion and exclusion criteria

We included all literature related to COVID-19 published in English and Chinese between 1 December 2019 and 6 February 2020 without restrictions, including guidance/guidelines, reviews, clinical studies, basic research, epidemiological studies and comments. Documents and guidance/guidelines posted by international organisations, government institutions, associations and societies were also included. We excluded news reports that were not published in scientific journals, and articles where we failed to access full text despite contacting the authors.

Article selection and data extraction

Two reviewers (ML and XL) screened all titles, abstracts and full texts independently and solved disagreements by consensus or consultation with a third reviewer. Then the following information was extracted: (i) title, (ii) first author, (iii) whether peer-reviewed or not, (iv) journal, (v) publication or posted date, (vi) first author’s country (or international organisation), (vii) type of article/study and (viii) topic. The details are shown in Supplementary Table S2 .

Data analysis

We conducted a descriptive analysis of the characteristics of the included literature. We described the source where we found the article, publication date, type of article/study, and topic of article/study or guidance/guideline on COVID-19 to examine the existing gaps in research. We categorised the literature into guidance/guidelines and consensus statements, reviews, clinical studies (including randomised controlled trials and observational studies), basic research, epidemiological studies, editorial comments on COVID-19 and other categories if identified. We conducted this scoping review in accordance with the PRISMA-ScR Checklist [ 16 ] ( Supplementary Table S3 ).

Search results

We identified 1,511 records, 280 of which were excluded as duplicates. Title and abstract screening were conducted for the remaining 1,231 articles, 989 of which were excluded because of being unrelated to COVID-19. For two articles, we failed to access the full text after contacting the authors. We retrieved the full texts of the 242 remaining articles. After further screening and supplementary searching of articles published or posted between 31 January 2020 and 6 February 2020, we identified an additional 42 articles and a total of 249 articles were included in the review ( Figure 1 ).

Flowchart of selection process for the scoping review of coronavirus disease (COVID-19) articles/studies and results, 1 December 2019–6 February 2020

CBM: China Biology Medicine; CNKI: China National Knowledge Infrastructure.

Characteristics of included articles/studies

Of the 249 included articles/studies, 147 (59.0%) were from China. The article/study type varied vastly, which we broadly characterised into 11 types ( Table 1 ). Of these, guidance/guidelines and consensuses statements were the most common (n = 56; 22.5%).

SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; WHO: World Health Organization.

a Includes the websites of WHO, United States Centers for Disease Control and Prevention (US CDC), European Centre for Disease Prevention and Control (ECDC) and Public Heath England (PHE), and preprint servers.

b Other than cross-sectional studies.

c Includes reviews and correspondence that discussed the characteristics of the virus in general.

d Other than traditional Chinese medicine.

Sources of articles/studies

Of all included articles/studies, 192 (77.1%) were published in peer-reviewed journals, 35 (14.1%) were posted on preprint servers and 22 (8.8%) were published on the official websites of public health organisations. The journal with the highest number of articles was The Lancet, with 13 (6.8%) published articles. Of preprint articles, most (n = 28) were posted on BioRxiv. Articles published on official websites were mainly COVID-19 guidance/guidelines, including 10 WHO interim guidance documents, nine US CDC interim guidelines/guidance documents, two ECDC guidance documents and one Communicable Diseases Network Australia (CNDA) guideline.

Publication date

Figure 2 shows the cumulative number of articles published daily between 10 January 2020 and 6 February 2020. As at 6 February 2020, the number of articles on COVID-19 had been steadily increasing. Of the 192 articles that were published in peer-reviewed journals, the highest number of journal publications on a single day was on 30 January, with 24 articles (12.5%). For the 35 preprints, the number posted per day rose steadily from 19 January 2020 to 6 February 2020.

Cumulative number of coronavirus disease (COVID-19)-related articles/studies included in the scoping review, 10 January–6 February 2020 (n = 249)

Type of article/study

The types of articles/studies published on each day are shown in Figure 3 . The daily number of guidance/guidelines peaked between 29 January and 3 February whereas the number of published reviews showed an increasing trend since 29 January 2020. Only one systematic review was identified [ 17 ]. We found no randomised controlled studies or cohort studies.

Number of coronavirus disease (COVID-19)-related articles/studies published per day according to type, 10 January–6 February 2020 (n = 249)

a Including cross-sectional studies.

The different types of articles/studies focused on different topics. The basic research could be divided broadly into two categories: 21 genetic studies and 12 molecular biology studies. Ten genetic studies traced the origin of SARS-CoV-2 and tried to determine the possible virus reservoir. Among these, most suggested that SARS-CoV-2 evolved from a bat-CoV, namely bat-SL-CoVZC45, bat-SL-CoVZXC21, bat-SL-CoVZX45 and bat-CoV-RaTG13 as potential candidates [ 18 - 26 ]. However, Ji et al. [ 18 ] found snakes to be the most probable reservoir for SARS-CoV-2 while Guo et al. [ 26 ] suggested mink could be a candidate reservoir. Of the molecular studies, five [ 27 - 31 ] showed that the key receptor of SARS-CoV-2 is angiotensin converting enzyme 2 (ACE2), which is highly expressed in lung type II alveolar cells (AT2) [ 27 ], positive cholangiocytes [ 29 ], upper oesophagus, stratified epithelial cells and absorptive enterocytes from ileum and colon [ 30 ]. The other studies included an assessment of the cross-reactivity of anti-SARS-CoV antibodies with SARS-CoV-2 spike protein [ 32 ], and SARS-CoV-2 main proteases [ 33 , 34 ].

The main topic of epidemiological studies was the estimation of the transmissibility of COVID-19. The value of the basic reproduction number (R 0 ) varied across studies [ 35 - 43 ], however, all estimated it to be higher than one, which indicates the potential for sustained human-to-human transmission. According to the nine articles [ 35 - 43 ], R 0 ranges between 2.2 and 3.9. Some studies showed that the transmissibility of SARS-CoV-2 is comparable to [ 37 , 44 ] or even higher [ 39 ] than SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). In addition, studies focused on the disease burden associated with COVID-19 [ 45 ] and the global patterns of disease dispersion [ 46 , 47 ].

Most reviews on COVID-19 gave a brief summary of the clinical features [ 48 - 51 ] and the characteristics of SARS-CoV-2 [ 52 - 54 ], as well as recommendations on how to prevent and control [ 55 - 60 ] this novel pneumonia. A systematic review [ 17 ] explored the possibility of using lopinavir/ritonavir (LPV/r) to treat COVID-19, with the results supporting the use of LPV/r as a part of an experimental regimen for COVID-19 pneumonia treatment. Clinical features were reported in 21 studies [ 48 - 51 , 61 - 77 ]. The main symptoms of patients with COVID-19 at onset were found to be fever and cough, with a reduced lymphocyte count, which is similar to previous beta coronavirus infections [ 78 , 79 ].

Seventeen of the 56 editorials, comments and letters [ 80 - 96 ] were first reports or comments on the situation of the COVID-19 epidemic. Some [ 97 - 101 ] also briefly introduced the general information and characteristics of the new virus. The mapping of article/study type and topics, as well as associated gaps, is shown in Table 2 .

a Other than cross-sectional studies.

b Includes perspectives, case-control study and investigation protocols.

c Other than traditional Chinese medicine.

d Guidance/guideline or consensus statement: guidance for laboratory biosafety, caring and travellers, and national capacity review tools; review: reviews on human resources of healthcare, the causes and counter-measures of Wuhan ‘stigma’, and public health; letter: outbreak assessment; epidemiology study: studies on disease burden, the number of unreported cases, and infection fatality; editorial: journal’s opinion on matters related to COVID-19, and incidence rate estimation; cross-sectional study: hazard vulnerability analyses, epidemiology reports, and studies on public attitudes and perception; other: investigation protocol.

Guidance/guidelines and consensus statements

Of the 56 published guidance/guidelines and consensuses statements, 35 were guidance/guidelines. Nine of the 35 addressed the treatment and management of COVID-19 infection, eight addressed prevention and five addressed diagnostics. Ten of the guidance/guidelines were interim guidance documents issued by the WHO, including those on COVID-19 prevention, surveillance, assessment, care, management and mask use [ 6 - 9 , 102 - 107 ]. The US CDC published nine interim guidance/guidelines documents for evaluating, preventing and managing the new coronavirus [ 10 , 11 , 108 - 114 ]. In addition, ECDC published two guidance documents about COVID-19 patient care and the management of persons having had contact with SARS-CoV-2 cases [ 12 , 13 ]. Chinese researches also published 14 rapid-advice guidance/guidelines documents on diagnosis, prevention and management of COVID-19, all of which were interim guidance/guidelines documents developed by hospitals [ 115 - 128 ].

Only eight of the guidance documents/guidelines formed a guideline development group (GDG) [ 129 ]; the recommendations of 15 guidance documents/guidelines, including six developed by the WHO, were difficult to distinguish. Only ten guidance/guidelines fulfilled the strict principles of evidence-based practice and cited reference documents, which were mainly epidemic reports, government documents, and indirect evidence related to SARS-CoV or MERS-CoV [ 6 , 7 , 105 , 116 - 118 , 120 , 122 , 125 , 126 ]. Only two guidelines, both developed by Chinese researchers, were graded using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach [ 116 , 117 ]. Among the 35 guidance/guidelines, one [ 115 ] was completely on Traditional Chinese medicine and one [ 116 ] covered Chinese medicine. One Australian guideline [ 130 ] was adapted from SARS-CoV guidelines.

Our scoping review shows that while the number of articles on COVID-19 has been constantly increasing, as at 6 February, there were still clear gaps in several study types and research fields. We identified that some study types, in particular randomised controlled trials and cohort studies, were still non-existent before 6 February. According to a preliminary search of the Cochrane Network database up to 10 April 2020, the number of randomised controlled trials (RCTs) (n = 8) and observational studies (n = 42) still remains low [ 131 ].

We also found that there were only a few studies on clinical practice, making it difficult to develop clinical practice guidelines and health policies. The reason for the gaps in this area may be the rapid development of the outbreak and limited understanding of the new virus and the disease caused by it. Moreover, it takes time to conduct clinical research. When facing a public health emergency with a previously unknown cause, researchers should conduct studies on whether some clinical practice and public health interventions from other public health emergencies can be used as indirect evidence. However, we identified no such studies in our review.

We found that 14% of the studies related to COVID-19 were posted on preprint servers. This approach of sharing research as quickly as possible is very reasonable, especially in the case of such public health emergency. Previous studies have shown that preprints can accelerate progress in handling outbreaks of infectious disease [ 132 , 133 ].

The research topics in different types of articles/studies had both similarities and differences. Basic research was mostly focused on exploring the origin and reservoirs of the new virus, while epidemiological studies mainly focused on its transmissibility. Reviews and reports provided more general information of the virus and the outbreak, while guidance/guidelines included recommendations on how to prevent and control it.

Clinical practice guidelines are statements that include recommendations intended to optimise patient care that are informed by a systematic review of evidence and an assessment of the benefits and harms of alternative care options [ 134 ]. Clinical practice guidelines can inform healthcare workers' actions [ 134 ], and, especially when public health emergencies occur, rapid advice guidelines can guide clinicians in terms of how to perform related work [ 135 ]. After the outbreak of COVID-19, the WHO, US CDC and ECDC released guidance/guidelines as soon as possible, as did several Chinese institutions. However, most of these documents did not establish formal guideline development groups, and they did not fulfil the strict principles of evidence-based practice. For example, most guidance/guidelines did not grade the quality of evidence and strength of recommendations, and thus owed to the emerging crisis, such guidance/guidelines need to be considered with these limitations in mind. In 2007, the WHO published guidance about the process of developing rapid advice guidelines [ 129 ], stating that when a public health emergency occurs, a rapid review is needed and the development time should not exceed 6 months [ 135 ]. However, considering the limited time to set up panels, this could be a challenge for guidance/guideline developers. Nonetheless, we still expect guidance/guideline developers to establish formal development groups and fulfil the evidence-based practice principles.

Our scoping review can help researchers identify research gaps so as to conduct research to fill these gaps. For example, in the current situation, a systematic review to estimate the incubation period or research on new drugs or treatments, would be of great importance. This scoping review has several strengths. We performed a systematic search of a comprehensive set of sources, including databases, preprint servers, and official websites of international organisations and associations at the early stage of the pandemic. Furthermore, our large sample size is sufficient to illustrate the state of research and identify research gaps related to COVID-19 at the onset of the pandemic.

This study also has some limitations. Because of the delay in indexing, some articles published as at 6 February 2020 may not have been identified. Also, because our retrieval time was only until this date, articles published or posted after this date, of which there have been many, have not been included in the analysis. As some preprints, guidance/guidelines and disease control plans are constantly updated, the publication date we extracted may not be the time of their first publication time. Also, we did not assess the quality of the included literature because of diversity of the types of included articles. Another limitation of our study was that it only included articles published in English and Chinese, which could introduce publication bias. However, as the epidemic was most heavily affecting China until early February, it is reasonable to expect that literature published in English and Chinese up until this point in time covered the majority of the available knowledge. Finally, we were unable to access the full texts of two articles despite contacting the authors. However, compared with the total number of articles included in the review, we anticipate that the exclusion of these two articles is unlikely to have a major impact.

This scoping review shows the state of literature published or posted online related to COVID-19 as at 6 February 2020. The number of articles in this field has steadily increased since the outbreak became evident. However, the types of studies lacked diversity, especially clinical studies. More clinical research is needed, but in the rapidly evolving global pandemic, we encourage researchers to continuously review the latest literature, to take into account the latest available evidence and avoid overlapping work, and to improve evidence for the development of clinical practice guidelines and public health policies.

Acknowledgements

Funding statement: 2020 Key R & D project of Gansu Province; Special funding for prevention and control of emergency of COVID-19 from Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province (No. GSEBMKT-2020YJ01).

The members of the COVID-19 evidence and recommendations working group: Xiao Liu (Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China); Nan Yang (Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China); Shuya Lu (Sichuan Provincial People’s hospital, Chengdu, China ); Peipei Du ( School of Public Health, Chengdu Medical College, Chengdu, China); Yanfang Ma (Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China); Zijun Wang (Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China); Qianling Shi (The First School of Clinical Medicine, Lanzhou University, Lanzhou, China); Hairong Zhang (Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China); Qiangqiang Guo (School of Public Health, ShanXi Medical University, Taiyuan,China); Yuting Yang (Children's Hospital of Chongqing Medical University, Chongqing, China); Bo Yang (Children's Hospital of Chongqing Medical University, Chongqing, China); Shouyuan Wu (School of Public Health, Lanzhou University, Lanzhou, China); Xiaoqin Wang (Michael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, Ontario, Canada).

Supplementary Data

Conflict of interest: None declared.

Authors’ contributions: All authors have read and agree to the published version of the manuscript. Conceptualisation, YC and XW; methodology, ML, XL and JE; software, YL, MR and JW; data extraction, QW, SZ, MR, XZ, LW, QZ and SY; formal analysis, XL and ML; resources, ML and WL; writing—original draft preparation, ML, XL, WM and XQ; writing—review and editing, YX, XY, YC, XW, SY, XF, WM, JE, EL and XQ; visualisation, ML and XL; supervision, YC and XW; project administration, YC; funding acquisition, YC.