dengue fever research articles

• Research article
• Open access
• Published: 20 September 2021

A study on knowledge, attitudes and practices regarding dengue fever, its prevention and management among dengue patients presenting to a tertiary care hospital in Sri Lanka

• K. P. Jayawickreme   ORCID: orcid.org/0000-0001-9503-2854 1 ,
• D. K. Jayaweera 1 ,
• S. Weerasinghe 1 ,
• D. Warapitiya 1 &
• S. Subasinghe 1  

BMC Infectious Diseases volume  21 , Article number:  981 ( 2021 ) Cite this article

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The World Health Organization (WHO) has ranked dengue as one of the top ten threats to Global health in 2019. Sri Lanka faced a massive dengue epidemic in 2017, the largest outbreak in the country during the last three decades, consisting of 186,101 reported cases, and over 320 deaths. The epidemic was controlled by intense measures taken by the health sector. However, the reported dengue cases and dengue deaths in 2019 were significantly higher than that of 2018. Deaths were mostly due to delay in hospitalization of severe dengue patients. The mortality of dengue hemorrhagic fever is 2–5% if detected early and treated promptly, but is high as 20% if left untreated.

A descriptive cross-sectional study was done among patients with dengue fever presenting to the Sri Jayawardenepura General Hospital during October 2019. Data was collected using a questionnaire comprising 20 questions based on knowledge, attitudes and practices on dengue, which were categorized into questions on awareness of mortality and severity of dengue burden, prevention of dengue vector mosquito breeding and acquiring the infection, patient’s role in dengue management, and warning signs requiring prompt hospitalization.

The mean KAP score on all questions was 55%, while a majority of 65.2% patients scored moderate KAP scores (50–75%) on all questions, and only 7.6% had high KAP scores (> 75%). The highest categorical mean score of 62% was on awareness of dengue prevention, followed by 54% on awareness of dengue burden, and only 51% on dengue management. Only 5.3% patients scored high scores on awareness of dengue management, followed by 28.5%, and 40.9% patients scoring high scores on awareness of dengue burden, and awareness of prevention of dengue respectively. The mean KAP scores on all questions increased with increasing age category.

The population relatively has a better awareness of dengue prevention, as compared to awareness of dengue mortality and dengue management. The identified weak point is patient awareness of the patients’ role in dengue management, and identifying warning signs requiring prompt hospitalization. This results in delay in treatment, which is a major cause for increased mortality. There was a correlation between those who had good knowledge on dengue burden and those who were aware of patients’ role in dengue management. An action plan should be implemented to improve public awareness through education programs on the role of the public and patients in dengue management to drive a better outcome.

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The World Health Organization (WHO) has ranked dengue as one of the top ten threats to Global health in 2019 [ 1 ]. Brady et al. estimates a 3.9 billion prevalence of people, accounting to 40%-50% of the world’s population being at risk of infection. 128 countries worldwide are at risk of dengue infection, of which 70% of the global burden being in Asia [ 2 , 3 ]. The reported dengue cases to WHO increased from < 0.5 million in 2000 to > 3.34 million in 2016, characterized by a worldwide outbreak [ 4 ]. Although the world-wide numbers declined in 2017, there was a significant rise again in 2019 with 4.3 million cases worldwide. The highest number of dengue cases worldwide in 2019 in descending order were reported in Brazil, Philippines, Vietnam, Mexico, Nicaragua, Malaysia and India respectively, with Sri Lanka being placed in the 8th place worldwide, and in the 5th place in Asia [ 5 ]. Following a steady rise in annual dengue cases, Sri Lanka faced a massive dengue epidemic in 2017, which was the largest outbreak in the country during the last three decades, consisting of 186,101 reported cases, and over 320 deaths. The epidemic was controlled by intense measures taken by the health sector. However, the reported dengue cases rose again in 2019 reaching 102,746, being twice the number of reported cases of 51,659 in 2018, indicating re-emergence of an outbreak in 2019. A majority of cases being in the western province, with 20% in the Colombo district [ 6 ]. The dengue deaths in 2019 were 90; higher than the total dengue deaths in 2018 being 58, albeit with reduced mortality rate per overall cases [ 6 , 7 ]. The mortality of dengue fever is < 1%, and that of dengue hemorrhagic fever is 2–5% if detected early and treated promptly, but is high as 20% if dengue hemorrhagic fever is left untreated [ 8 ].

Dengue virus is a flavivirus transmitted by mosquito vectors, such as Aedes aegypti and Aedes albopictus. Dengue fever was first serologically confirmed in Sri Lanka in 1962 [ 9 ]. All four serotypes of dengue virus, DENV-1 to DENV-4 have been circulating in the country, and each serotype has many genotypes [ 9 ]. The most common cause for occurrence of new epidemics is the shift of the circulating serotype and genotype of the dengue virus, which is predisposed by increased foreign travel introducing new strains [ 9 ]. The dengue outbreak in 2003 was predominantly due to DENV-3 and DENV-4. The outbreaks in 2006, 2009 and 2010 was predominantly due to DENV-1 [ 9 ]. The predominant serotype in the 2017 epidemic was DENV-2 which was infrequent since 2009 [ 10 ]. The outbreak in 2019 was predominantly due to previously latent serotype DENV-3 [ 11 ].

The WHO published and implemented a “Global Strategy for Dengue Prevention And Control” targeting the years from 2012 to 2020, with the goals of improving dengue mortality, and morbidity by the year 2020, and estimating the true disease burden. The main elements of the global strategy were diagnosis and case management, integrated surveillance and outbreak preparedness, sustainable vector control, future vaccine implementation, basic operational and implementation research [ 12 ].This global strategy follows 10 priority areas for planning dengue emergency response, adapted from Rigau-Pérez and Clark in 2005, which also includes Engaging the community and relevant professional groups about dengue control as well as their participation in dengue prevention and control [ 13 ].

A recent study in Malaysia, showed that the population had only an average knowledge, and poor attitudes and practices on dengue prevention. They identified that a significant percentage had erroneous beliefs, such as fogging being the mainstay of dengue vector control. It had led them to a false sense of security, while evading actual measures that should be taken. They also identified that a proportion of people believed they had no responsibility in preventing dengue breeding, which needed urgent attention. They highlighted that it was impossible to reduce dengue prevalence without community participation, and concluded that measures were urgently required to educate the public to change their attitudes. The Communications for behavioral changes program on dengue prevention were subsequently implemented by Health departments of Malaysia to improve dengue awareness and prevention [ 14 ].

Although there had been a few studies on public awareness on dengue prevention, there was limited evidence focused on public awareness on their role in dengue prevention and management. It is therefore very important to take active measures to reduce the incidence and mortality of dengue, for which the responsibility lies not only with health professionals, but also with the general public. The purpose of this study is to identify the level of awareness in patients on preventing and managing dengue infection, and awareness of the patient’s role and responsibility in the above. Our goals were to identify areas in dengue control and management that need improvement, to implement policies that raise patient participation to deliver a better outcome of dengue infection, its complications and its management.

Study design

This is a descriptive cross-sectional study assessing the knowledge, attitudes, and practices on dengue fever, its prevention and the patient’s role in management, among the dengue patients presenting to a tertiary care hospital in Sri Lanka during the month of October 2019.

Study setting

The study was done among a random sample of 132 patients with dengue fever or dengue hemorrhagic fever who were admitted to adult medical wards for treatment at the Sri Jayawardenepura General Hospital during October 2019. These patients comprised people from draining areas of the western province of Sri Lanka.

Sample size

The number of patients who presented to the Sri Jayawardenepura General hospital in the month of October 2019 was 200. A sample size of 132 was calculated with a confidence interval of 95%, to match the population to assess a statistically significant result.

Participants

The study population was randomly selected among adult patients older than 13 years of age admitted with dengue infection to the medical wards of the Sri Jayawardenepura General Hospital during the month of October 2019.

Participants were not selected from the same family who would likely to be influenced by similar knowledge, to avoid bias of pseudo-replication.

Data collection

Data collection was commenced after obtaining the approval from the institutional Ethical Review committee of the Sri Jayawardenepura General Hospital and Postgraduate Training Centre (SJGH/20/ERC/017). Data was collected using a self-administered validated questionnaire regarding Knowledge, Attitudes, and Practices (KAP) on dengue in languages English, Sinhala, and Tamil which were translated and extensively reviewed for validation (Additional file 1 : Appendix S1, Additional file 2 : Appendix S2, Additional file 3 : Appendix S3).

Data was collected from randomly selected participants, only after informed written consent was obtained. The questionnaires were filled by the participants themselves using the validated questionnaire of the language convenient to them. The study investigators were with them while filling the questionnaire in case the participants needed to clarify any questions in order to ensure quality. The data was collected anonymously, while strict confidentiality of the responses and the results was maintained.

The questionnaire consisted of 20 questions which, comprised 5 questions on knowledge, 6 questions on attitudes, and 9 questions on practices on dengue fever and haemorrhagic fever, its prevention and patient’s role in management. Prior to analysis they were then re-categorized into questions on awareness of:

mortality and severity of dengue burden—5 questions

prevention of dengue vector mosquito breeding and acquiring the infection—5 questions

patient’s role in dengue management, and warning signs requiring prompt hospitalization—10 questions

The responses to each question was analyzed with percentage estimated of correct responses. The total marks scored by each participant to the whole questionnaire was estimated as a percentage, which has been defined as the “KAP score”. KAP score is an abbreviation used for the total score of the questions based on K nowledge, A ttitudes, and P ractices regarding dengue burden, dengue prevention and management in this study. The total results were categorized as “low” when KAP were < 50%, “moderate” when KAP scores were 50–75%, and “high” when KAP scores were > 75%.

Statistical methods

Data was analyzed using the SPSS (Statistical Package for the Social Sciences) software. All the questionnaire sheets were filled completely and none of the sheets were excluded. The mean of the KAP score of each category was calculated. The percentage of the population who scored low, moderate and high KAP scores was calculated separately. The responses to each of the 20 questions were analyzed separately to infer the areas which needed further improvement in awareness of the general public on dengue.

The study population comprised 61% males, and 39% females with a male: female ratio of 3:2. When categorizing by age, 42% of the study population was less than 30 years old, 36% were between 30 and 50 years old, and 22% were more than 50 years old. Of those who were between 30 and 50 years, 35% were graduates or diploma holders. Of those who were more than 50 years old, 21% were graduates or diploma holders. When categorizing by level of education, 10% of the population was currently schooling, 8% were adults educated up to less than ordinary level (O/L) at school who were not graduates or diploma holders, 18% were adults educated up to O/L at school who were not graduates or diploma holders, 34% were adults educated up to advanced level (A/L) at school who were not graduates or diploma holders, 24% were adults who had completed school education and were undergraduates, 6% were adults who had completed school education and were graduates or diploma holders (Table 1 ).

The mean KAP score of the sample population from the questionnaire was 55.04%. When categorizing the KAP scores as low (< 50%), moderate (50–75%), and high (> 75%), a majority of 65.2% of the population had moderate KAP scores. 27.3% had low KAP scores, and only 7.6% had high KAP scores (Fig. 1 ).

Percentage of the study population who scored under each KAP score level Category. When categorizing the KAP scores as low (< 50%), moderate (50–75%), and high (> 75%) scores, a majority of 65.2% of the population had moderate KAP scores. 27.3% had low KAP scores, and only 7.6% had high KAP scores

The KAP score achieved was higher with increasing age. The highest mean total KAP score of 57.86% was among those > 50 years of age, with those aged < 30 years having a mean KAP score of 53.48% and those aged 30–50 years having a mean KAP score of 55.21% (Fig. 2 ). The mean KAP score on awareness of dengue mortality and burden among the age categories < 30 years, 30–50 years, and > 50 years was 49.29, 56.88, and 58.57% respectively. The mean KAP score on awareness on prevention of dengue vector breeding and acquiring the infection among the age categories < 30 years, 30–50 years, and > 50 years was 63.57, 59.38, and 63.57% respectively. The mean KAP score on awareness of patients’ role in dengue management and warning signs requiring prompt hospital admission among the age categories < 30 years, 30–50 years, and > 50 years was 49.82, 52.08, and 51.79% respectively (Fig. 3 ).

The mean KAP score of each age category. The KAP score achieved was higher with increasing age. The highest mean KAP score of 57.86% was among those > 50 years of age, with those aged < 30 years having a mean KAP score of 53.48% and those aged 30–50 years having a mean KAP score of 55.21%

Comparison of the total KAP score, awareness on mortality and severity ofdengue burden, awareness on prevention of dengue vector breeding and acquiring the infection, and awareness on patient’s role in dengue management, and warning signs requiring prompt hospitalization under each age category

The mean KAP score was higher among those with higher educational qualification levels. The highest mean KAP score of 58.13% was among graduates and professional diploma holders of any field, and the lowest score of 49% was among adults educated in school up to below O/L. The mean total KAP score among those currently schooling was 54.62%. Adults who were not undergraduates, graduates, or diploma holders, who were out of school, but were educated at school up to O/L and those who had completed schooling after A/L had mean total KAP scores of 53.96 and 54.67% respectively. The mean KAP score on awareness of dengue mortality and severity of dengue burden among each of the age categories; schooling, adults educated less than O/L, adults educated up to O/L, adults educated up to A/L, under graduates, graduates or diploma holders were 50.77, 42, 60.83, 50.44, 58.75, and 55% respectively. The mean KAP scores on awareness on prevention of dengue vector breeding and acquiring the infection among each of the educational categories in above order were 60, 60, 60, 64, 60.94, 67.5% respectively. The mean KAP scores on awareness of the patient’s role in dengue management and warning signs requiring prompt hospital admission among each of the educational categories in above order were 53.85, 45, 44.58, 51.56, 55, 55% respectively (Fig. 4 ). The mean KAP score among females was 55.48%. and that of males was 54.75%.

Comparison of the total KAP score, awareness on mortality and severity of dengue burden, awareness on prevention of dengue vector breeding and acquiring the infection, and awareness on patient’s role in dengue management, and warning signs requiring prompt hospitalization under each educational category

When analyzing data by categorizing the questions by the awareness on the area assessed, the highest mean KAP score of 62.05% was on questions on awareness of prevention of dengue vector breeding and acquiring the infection, while the lowest mean KAP score of 51.06% was on questions on awareness of patient’s role in dengue management, and warning signs requiring prompt hospitalization. The mean KAP score on awareness of dengue mortality and severity of burden was 54.02% (Fig. 5 ). On analysis of questions related to awareness of dengue mortality and severity of burden, only 28.8% had high KAP scores, 40.9% had low KAP scores, and 30.3% had moderate KAP scores. On the analysis of questions related to awareness on dengue prevention, an equal percentage of 40.9% had low and high KAP scores respectively, and 18.2% had moderate KAP scores. Analysis of questions related to awareness on patient’s role in dengue management and warning signs prompting hospitalization showed, only 5.3% had high KAP scores, 62.9% had moderate KAP scores, and 31.8% had low KAP scores (Fig. 6 ).

Mean KAP score of each area assessed. 1. Mean KAP score on awareness of mortality and severity of dengue burden- 54%. 2. Mean KAP score on awareness of prevention of dengue breeding and acquiring the infection—62%. 3. Mean KAP score on awareness of patient’s role in dengue management, and warning signs requiring prompt hospitalization—51%

Comparison of percentage of the population who scored low (< 50%), moderate (50%-75%), and high (> 75%) KAP scores under each area assessed

There is no statistically significant correlation between the mean KAP scores on awareness of dengue mortality and severity of dengue burden, and the mean KAP scores on awareness on prevention of dengue vector breeding and acquiring infection according to the spearman’s test (p = 0.084). Although there is a statistically significant correlation between the mean KAP scores on awareness of dengue mortality and severity of dengue burden, and the mean KAP scores on awareness of patient’s role in dengue management and warning signs requiring prompt hospital admission according to the spearman’s test (p = 0.015).

The populations response to each individual question is shown in Table 2 . The percentage of the population who knew the correct answer for the questions on awareness of dengue burden and mortality were as follows: The number of reported dengue cases in Sri Lanka for the year during the outbreak in 2017 was close to 200,000 (42%), The number of reported dengue cases in the year 2019 is higher than that of 2018 (52%), Of 100 persons who get dengue fever only 1 or less persons would die per year when detected early and proper access to medical care (The mortality of dengue fever is < 1%) (60%), The mortality rate of dengue hemorrhagic fever is 2–5%, but is high as 20% if left untreated (60%), The WHO has ranked dengue as one of the top ten threats to Global health in 2019 (56%).

The percentage of the population who knew the correct answer for the questions on awareness of dengue prevention were as follows: all persons with dengue fever do not need to be notified to the Public Health Inspector (PHI) (39%), dengue vector mosquitoes breed in muddy water (52%), The peak biting times of the dengue mosquito is morning and evening (80%), If a person gets dengue fever once in their life, they will be immune to it and will not get dengue fever again (44%), discarded tires, coconut shells, and plastic containers collecting rain water in the garden should be destroyed to prevent dengue vector breeding (96%).

The percentage of the population who knew the correct answer to the questions on awareness of dengue management and warning signs which require prompt hospitalization were as follows: There is a special drug available to treat dengue fever (43%), papaya leaf juice increases the platelet count and thus helps treat dengue fever (33%), dengue patients with a platelet count < 150,000/mm 3 with a rapid drop are recommended to be admitted to hospital (85%), abdominal pain in a dengue patient is not an indication for hospital admission (32%), all pregnant mothers with dengue fever are recommended to be admitted in hospital irrespective of the platelet count (83%), NS1 antigen can be tested on any day since the onset of fever to diagnose dengue fever (23%), a negative report of dengue IgM antibody done on the second day since onset of fever means the patient does not have dengue fever (17%), When a dengue patient has a platelet count > 150,000/mm3 and does not meet criteria which require hospital admission, they should drink 2500 ml of oral fluids per day at home (40%), When a dengue patient has a platelet count > 150,000/mm3 and does not meet criteria which require hospital admission, they should check their Full blood count daily to assess the drop in platelet count (65%), dengue patients should avoid having red or brown drinks (89%).

Dengue virus has four serotypes. Acquisition of dengue infection due to one serotype does not give immunity against a subsequent infection with another serotype, though there is about a two years period of cross-protection [ 15 ]. All four serotypes share only 60–75% identity at amino acid level, and are thus considered as different viruses [ 14 ]. Infection from one serotype gives life-long immunity against that particular serotype [ 10 , 15 ]. Once the cross protection wanes off, secondary dengue infection is more severe than primary dengue infection [ 10 , 15 ]. However only 44% of the study population were aware that occurrence of dengue infection once, does not prevent occurrence of the disease again.

Dengue transmission increases during the rainy season in Sri Lanka, mostly in July, due to increasing dengue vector mosquito breeding places. Other causes for increase in the number of dengue cases is urbanization, climate change, and poor vector control and prevention of disease [ 10 ]. 96% of our cohort were aware of the need to destroy and clean water collecting areas, to prevent breeding of the dengue vector, while 84% of the cohort of a similar study done in the central province of Sri Lanka was aware of this same fact. This is probably because the latter study was done in 2015, prior to the dengue epidemic in 2017 [ 16 ]. Intense measures were taken in the country by which the epidemic in 2017 was controlled. This included clean-up campaigns, awareness programs, National dengue prevention and control, National Strategic framework (2016–2020) to align their action with the WHO Global strategy for dengue prevention and control (2012–2020), The Presidential Task Force on Dengue (PTF) and National dengue control unit of the Ministry of Health launched a rapid inter-sectoral program for prevention and control of dengue [ 7 ]. Awareness programs were held in rural and urban community gatherings, taught in school and institutions, shared on social media, television and radio [ 7 ]. However, data regarding the targeted population for these awareness programs was sparse. Dengue is ranked the third commonest notifiable disease in Sri Lanka, by which means the health sector can implement active vector control measures in the identified areas [ 17 ]. Only 39% of the study population was aware that all persons with dengue fever should be notified to the PHI. The low number of people who were aware of the importance of notifying dengue cases to the PHI, was probably due to the general public being unaware of the PHI’s role in dengue prevention, and lack of awareness of their responsibility in notifying cases, and it’s importance in vector control. Lack of notification of disease hinders action taken for vector control, which gives a falsely lower number of reported cases than the actual number. People should be educated on this to improve notification and vector control. Notification to the PHI of dengue patients managed at home or in the hospital should be made mandatory to avoid negligence in notification. This study population had a relatively good awareness about dengue breeding sites and biting times, probably due to awareness programs during the 2017 epidemic. Literature has shown the importance of improving knowledge on dengue prevention to control dengue outbreaks [ 18 ].

A study in Vietnam during the dengue epidemic in 2017 showed that 91% of the study population considered dengue to be dangerous to very dangerous [ 19 ]. Our study evaluated patients already being admitted for treatment of dengue at the Sri Jayawardenepura general hospital, comprising of patients from the western province, which has the highest dengue burden in the country. A similar study was done in the central province of Sri Lanka by Jayalath et al . among out patients visiting the Peradeniya hospital for reasons other than dengue. Jayalath et al. showed that 95% of their study population knew dengue was a severe disease [ 16 ]. 75% of the cohort of a similar study done among patients being admitted for treatment of dengue fever, in the northern province of Sri Lanka in 2017, knew that dengue was a severe disease [ 20 ]. Our study population had a moderate mean KAP score (54%) on questions on awareness on dengue severity and burden. 40.9% of the population had low awareness on severity and burden of dengue, and only 28.8% had high awareness on its severity and burden. This difference in evidence regarding awareness of severity of dengue in the above studies, could be because the questions by which awareness was evaluated was different in the three studies, and because our study, and the study in the northern province evaluated patients who had already acquired dengue fever and were admitted for treatment at that time. It could also be speculated that these populations acquired dengue infection due to their lack of awareness in prevention of disease.

This lack of awareness on the severity of dengue and it’s burden is probably due to most dengue patients uneventfully recovering from uncomplicated dengue fever, and due to successful dengue management by the healthcare system in the country. This study identified that those who had good awareness on the mortality and severity of the burden of dengue, also had a good awareness about their role in managing dengue, as well as warning signs requiring prompt hospital admission. It can be concluded that there is a strong correlation between those who have an appreciation of the gravity of the symptoms caused by dengue, and the likelihood of them educating themselves on dengue management and their active participation in it. Rozita et al. showed that people who were infected by dengue, or had a family member infected by the disease had better knowledge, attitudes and practices about dengue compared to those who did not [ 21 ]. A study in Singapore in 2017 after the country’s largest dengue epidemic showed that attitudes and practices regarding dengue among primary care physicians significantly improved after experiencing the epidemic [ 22 ]. Chanthalay S et al . showed that those who had better knowledge and attitudes regarding dengue are more likely to take precautions to prevent the disease [ 23 ]. Those who have good awareness will have a good understanding of the gravity and impact of the disease, will know the importance of preventing it, and will be aware of necessary preventive measures.

The mortality of dengue fever is < 1%, and that of dengue hemorrhagic fever is 2–5% if detected early and treated promptly, but is high as 20% if dengue hemorrhagic fever is left untreated [ 8 ]. In 2015 Malhi et al. reported that the presence of comorbidities like diabetes mellitus, hypertension, chronic kidney disease, allergies, asthma, ischemic heart disease and hepatic anomalies, as well as delay in identification and treatment were linked to increased mortality from dengue [ 24 ]. However, in 2017 a study by the same authors showed that 50% of dengue deaths were of previously healthy individuals with no comorbidities [ 25 ]. Therefore, the leading cause for dengue related complications and deaths is delayed identification and treatment of disease. This can be due to delays by the patient or health staff, mostly due to delayed patient presentation to the hospital [ 26 ].Studies have shown that late presentation of dengue fever to the hospital leads to increased development of dengue haemorrhagic fever, dengue shock syndrome, multi-organ involvement like acute kidney injury, and increased mortality [ 26 , 27 , 28 ]. According to the study findings, by identifying areas where the public has misconceptions and misunderstandings about dengue fever, its prevention and management, we can implement steps to improve those loop holes. By following correct practices, avoiding malpractices, and timely hospital admission, his will reduce dengue fatality, improve the outcome, and will also reduce the burden on the healthcare system.

The national Guidelines on dengue management indicates the need for hospital admission in a dengue patient if the platelet count is < 100,000, or platelet count between 100,000- 150,000 with a rapid drop in platelets, fever for three days with any warning signs such as abdominal pain, persistent vomiting, mucosal bleeding, lethargy and restlessness [ 29 ]. Irrespective of the above criteria, admission is required in dengue patients who are pregnant, elderly, obese, with comorbidities, or with adverse social circumstances [ 29 ]. In this study, 85 and 83% patients respectively were aware of the indication for admission as per the platelet count or if pregnant, but only 32% patients knew admission was indicated with warning signs like abdominal pain. Therefore, people need to be educated about warning signs of severe dengue infection. People who do not require admission must be educated about cautious self-management at home until they require admission [ 29 ]. By doing so there will be less likelihood to miss warning signs, will have improved outcome, and there will be less burden to hospital staff. Only 40% of patients knew about fluid management at home, but 89% knew to avoid red drinks.

Serological testing is important to confirm the diagnosis of dengue fever when the presentation is atypical or when unsure of the diagnosis. NS1 antigen is tested in the patient’s blood on the first few days of the disease and has a sensitivity of 60–90%. Dengue IgM antibody will be positive in the patient’s blood only after the 5th day of illness [ 29 ]. Therefore, patients should be educated about the ideal time to do each test to avoid false negatives being reported by doing the test at the wrong time of the illness. However, dengue infection cannot be excluded by a negative serological lab report. Few patients knew about the timing of testing, with only 23% and 17% being aware of the timing of testing, and sensitivity of NS1 antigen and dengue IgM respectively. It is important that health care professionals guide patients on the correct timing to do the serological tests. It would be prudent to do such serological tests only on request by a physician, to avoid patients testing at the wrong time, and getting a report which cannot be interpreted at that time of the illness. False negatives of serological testing can further be avoided by laboratory staff rechecking the patients’ day of the illness, and the physicians request form prior to drawing blood.

This study shows that people had misconceptions about dengue management. Only 43% knew there was no special drug to treat dengue fever. There is no particular drug to treat dengue, but is managed by careful monitoring and fluid tailoring resuscitation [ 29 ]. A tetravalent live attenuated dengue vaccine has been registered for use in several countries [ 15 ]. In sero-negative individuals it is believed that the vaccine mimics a silent natural infection, giving temporary cross-protection against all serotypes, and subsequently causing severe dengue infection when primarily infected [ 15 ]. However, its efficacy varies in different countries and is not currently recommended for use in Sri Lanka [ 15 ]. The use of papaya leaf juice in dengue management had recently gained interest, leading to many people consuming the juice assuming improvement of dengue infection. Research has shown papaya leaf juice to improve platelet counts, but has not shown to prevent or reduce fluid leaking in dengue hemorrhagic fever [ 30 ]. This can adversely cause early rise in platelet count masking the onset of fluid leaking, which can be detrimental in managing dengue hemorrhagic fever. 33% of our cohort believed papaya leaf juice helped treat dengue fever, while 13.4% of the cohort in a study done in Sri Lanka in 2015 believed the same to be true. This is probably because the concept of the effect of papaya leaf juice on platelet count came in to light only later on [ 16 ].

This study demonstrated an increasing trend in awareness on all categories, such as among people with a higher level of education, and maturity by age, indicating that education and maturity are important factors for improved awareness. Kumanan et al. showed a significant association between educational level and knowledge regarding dengue fever, and no significant association between educational level and preventive practices [ 20 ]. The trend in our study demonstrated on Fig. 3 suggests that responses in the awareness on dengue mortality and severity of dengue burden steadily increased with age, and strongly influence the mean total KAP scores. The highest awareness in all age categories was on dengue prevention and the lowest awareness in all categories was on patients’ role in dengue management and warning signs requiring prompt hospitalization (Fig. 3 ).

There was inadequate awareness among adults who dropped out of school prior to completion of the full school education up to advanced level even when they are older. This may demonstrate a population with lower level of understanding of the information given, and those who were not regularly educated at school regarding dengue infection as they dropped out. Those who drop out of school are also those who usually have a poor social background, and they may also have inadequate access to social media and electronic media to receive updates about dengue mortality, prevention and management. This highlights the need for any information to reach the people of all social backgrounds when implementing strategies to improve public awareness on dengue infection. Dissemination of information should be done in various ways targeting different populations of different levels of understanding. People with lower education levels should be the main target group requiring more advice and education regarding the patient’s role in dengue management.

This population has a relatively a better awareness on dengue prevention as compared to awareness of dengue mortality and dengue management. This is possibly due to prior media education of the public on prevention during the previous epidemic in 2017. The identified weak point is patient awareness on the patient’s role in dengue management, as well as identifying warning signs requiring prompt hospitalization. It causes delay in treatment, which is a major cause for increased mortality. The trend demonstrated on Fig. 5 suggests that responses in the dengue management and warning signs prompt hospitalization area strongly influence the total KAP scores. This indicates that patient awareness on the role of the public and patients on dengue management is critical in the outcome of dengue infection. An action plan should be implemented targeting improving public awareness by education programs on the role of the public and patients in dengue management, to improve outcome.

The general public play a major role in prevention and management of dengue fever, and influence the outcome. Jayalath et al. showed that 30% of their population believed the responsibility of dengue prevention lay with the public, while 66% believed both the public and the government were responsible [ 16 ]. In order to improve involvement of patients and the public in dengue prevention, control and management, attention should be paid on educating the public and patients on the disease.

Limitations and recommendations for future research

This study focused on 132 patients from one hospital. Therefore, the conclusions can be relevant only to draining areas in the vicinity of this hospital, and may not represent the knowledge, attitudes and practices in other parts of Sri Lanka. However, since majority of the dengue cases in the country are concentrated in the western province, of which a significant number of patients present to the Sri Jayawardenepura General Hospital, the findings of this study may represent the most dengue dense area in the country. Large scale future research from all parts of the country may be beneficial to infer the knowledge, attitudes, and practices of the country as whole.

The general public was educated about Dengue infection by various means, including messages on social media, electronic media, awareness programs at schools, and village meetings, posters and distribution of leaflets, during the dengue epidemic in 2017. This study did not extensively evaluate whether the study participants had been exposed to these prior teaching about Dengue infection, and if they did, by what means they were educated. However almost all the study participants had access to electronic and social media. This may not be the same when inferring on the population in some rural parts of Sri Lanka who may not have similar access to such media education. Awareness programs and active participation of the general public in dengue prevention and management should be implemented. We suggest future follow up research of the awareness on dengue infection among the public, before and after implementing formal dengue awareness strategies to assess the effectiveness of it. In addition to follow up research before and after implementing disease awareness steps, we also suggest future research to assess an association and comparison of dengue mortality and outcome before and after implementing practices to further educate the public, in order to identify its impact on dengue management and outcome.

The population has relatively a better awareness on dengue prevention, as compared to awareness of dengue mortality and dengue management. The identified weak point is patient awareness on the patient’s role in dengue management, and identifying warning signs requiring prompt hospitalization causing delay in treatment, which is a major cause for increased mortality. There was a correlation between those who had good knowledge on dengue burden and those who were aware of the patients’ role in dengue management. There is also an increasing trend in awareness on all categories, especially among people with a higher level of education, and maturity by age, indicating that education and maturity are important factors for improved awareness. An action plan should be implemented targeting improving public awareness on the role of the public and patients in dengue management to improve outcome.

Availability of data and materials

The raw data sets analyzed during the current study are available on reasonable request from the corresponding author.

Abbreviations

Dengue virus

Knowledge attitudes and practices

Ordinary level at school

Advanced level at school

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SS is a Consultant Physician [MBBS, MD, FRACP] Medical unit, Sri Jayawardenepura General Hospital. KPJ [MBBS], DKJ [MBBS] and DW [MBBS] are Registrars in Internal medicine, and SW is a Senior Registrar in Medicine at the Sri Jayawardenepura General Hospital.

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Data collection was done by KPJ, DKJ and DW. Analysis, interpretation of data, literature review and writing of the report was done by KPJ. SS and SW guided the study and corrected the final manuscript. All authors read and approved the final manuscript.

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Jayawickreme, K.P., Jayaweera, D.K., Weerasinghe, S. et al. A study on knowledge, attitudes and practices regarding dengue fever, its prevention and management among dengue patients presenting to a tertiary care hospital in Sri Lanka. BMC Infect Dis 21 , 981 (2021). https://doi.org/10.1186/s12879-021-06685-5

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ORIGINAL RESEARCH article

Clinical characteristics and risk factors for severe dengue fever in xishuangbanna, during the dengue outbreak in 2019.

A correction has been applied to this article in:

Corrigendum: Clinical Characteristics and Risk Factors for Severe Dengue Fever in Xishuangbanna, During the Dengue Outbreak in 2019

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• 1 Institute of Medical Biology, Chinese Academy of Medical Sciences, Peking Union Medical College, Kunming, China
• 2 Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Diseases, Kunming, China
• 3 Yunnan Key Laboratory of Vector-Borne Infectious Disease, Kunming, China
• 4 Xishuangbanna Dai Autonomous Prefecture People’s Hospital, Jinhong, China
• 5 Kunming Medical University, Kunming, China

Background: Dengue poses a large burden on the public health systems worldwide. severe dengue (SD) could lead to more serious clinical symptoms and even death. This study aimed to identify the cause of SD in a clinical trial during the dengue outbreak in Xishuangbanna in 2019, and could provide new insights into the pathogenic mechanisms of SD.

Methods: Mosquito-borne viral (DENV, JEV, and CHIKV) infections were identified. The epidemiological factors and clinical symptoms of inpatients in Xishuangbanna were recorded. The IgG and IgM levels in the serum of dengue inpatients were evaluated, and secondary infections were identified. Then, the structural proteins (C/PrM/E) were sequenced and compared with those of the same type of DENV in the same area as before, and their structures were predicted by the SWISS-MODEL ( expasy.org ). The full-length viral genomes were sequenced and aligned with representative strains by BioEidt or MEGA 5.0.

Results: In this outbreak, the clinical symptoms were more serious in SD. The proportion of SD inpatients of male and Han nationality was larger than that of dengue fever (DF) inpatients ( p < 0.05). DENV-2 infection was the majority in DF, with 45 inpatients. However, DENV-1 infection was the most common SD, with 54 inpatients. There were 3 DENV-3-positive inpatients in the DF group and 6 ZIKV-positive inpatients in the SD group. A secondary infection accounted for 76.47% (78 cases) of SD inpatients, but secondary infections were only in 20% (17 cases) of DF inpatients. In the three-dimensional structure of protein analysis, the C/PrM/E of DENV-1 and DENV-2 showed more stability than previous epidemic strains, while DENV-3 in 2019 showed a looser spatial structure. After a complete genome sequencing and analysis, all six DENV-2 strains belonged to cosmopolitan, five of which clustered into one branch. The GC/AT of the five strains decreased from 2014 to 2018. Compared with DF strains, SD strains had no mutations of commonness.

Conclusions: SD may related to secondary heteromorphic dengue in Xishuangbanna in 2019. The coinfection of ZIKV could be another related factor for SD. The currently datas were very limited and only suggestive.

Introduction

Dengue virus (DENV) is a mosquito-borne flavivirus that is transmitted by the vectors, Aedes aegypti and Aedes albopictus , and is a vector-borne infectious disease virus ( Hawley et al., 1987 ). Dengue virus is a single stranded, positive RNA virus with an envelope genome of approximately 11 kb. The genome encodes a polyprotein, which is processed into three structural proteins [the capsid (C), premembrane (prM), and envelope (E) protein] and seven non-structural proteins (NS1-NS5) ( Guzman and Harris, 2015 ). There are currently four circulating serotypes (DENV-1 to DENV-4) that exhibit up to 70% sequence homology ( Bhatt et al., 2020 ). The incubation period of dengue virus infection is 4–7 days ( Bhatt et al., 2020 ). The disease spectrum ranges from asymptomatic infection and moderate febrile illness (DF) to more severe dengue (SD), such as dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS; Chaturvedi et al., 2000 ). The clinical symptoms of SD patients mainly include high fever, severe pain in the bones, joints and muscles, headache, skin rash, lymph node enlargement, bleeding, shock and even death ( World Health Organization, 2009 ).

Dengue was listed as a potential threat among ten diseases by the WHO in 2019 ( Norshidah et al., 2021 ). The global incidence has been estimated at 390 million infected individuals each year. In China, no case was reported from 1949 to 1977 until an outbreak occurred in Guangdong Province in 1978 ( Yue et al., 2020 ). In recent years, dengue cases have been reported in almost all provinces (autonomous regions) in China ( Liu, 2020 ). Southeast Asia is an important area for Aedes aegypti and Aedes albopictus and has always been the main epidemic area of dengue disease. Yunnan, as one of the border provinces of China, is adjacent to the Southeast Asian countries Laos, Myanmar and Vietnam. A total of 15,572 dengue cases were recorded in Yunnan Province from 2013 to 2019, as shown in Figure 1 . Dengue cases were concentrated in the border areas, and a total of 8,477 dengue cases were recorded in Xishuangbanna Prefecture (red circle in Figure 1 ), bordering Laos and Myanmar, including 568 imported cases (6.70%) and 7,909 local cases (93.30%) ( Zhang, 2021 ). In Xishuangbanna, few cases of dengue virus infection were reported before 2013. The number of reported dengue virus infections (DENV-3) rose to 1,319 in 2013, 1,132 in 2015 (DENV-2) and 1348 in 2017 (DENV-1). As of November 2019, the number of dengue virus NS1 positive infections exceeded 3,900 ( Zhang et al., 2021 ). With the increase in the number of infections, the number of inpatients with SD increased to 102 in 2019. According to previous reports, 70 of 634 inpatients (11.04%) had SD in 2013 ( Ma et al., 2016 ). Among the 109 inpatients in 2015, 13 (11.9%) had SD ( Cui et al., 2016 ).

Figure 1. Regional distribution of dengue fever cases in Yunnan Province, China, 2013-2019 (the dates in the picture are from Zhang, 2021 ).

As a more serious form of dengue infection, SD is directly life-threatening. In some areas, the mortality rate of pediatric patients is as high as 5% ( Wang et al., 2016 ). Former studies suggest that age, gender, social status, genetic background, chronic diseases might adversely influence the clinical presentation of dengue infection ( Htun et al., 2015 ). The aim of this article is to study the factors associated with SD. The infection of mosquito-borne viruses [including Zika virus (ZIKV), Japanese encephalitis virus (JEV), and Chikungunya virus (CHIV)] and the serotype of DENV were identified, and the epidemiological factors and clinical symptoms of inpatients in Xishuangbanna were recorded. Then, IgG and IgM in the serum of dengue inpatients were detected, and secondary infections were identified. The structural proteins (C-PrM-E) were sequenced and compared with those of the same type of DENV in the same region. The three-dimensional structure of dengue virus structural proteins was predicted by the SWISS-MODEL ( expasy.org ). Finally, whole genome sequences of 6 inpatients (including 3 SD and 3 DF) were obtained and compared with the sequences of different viruses from different years to detect the homology of the sequence.

Materials and Methods

Study design and participants.

Laboratory-confirmed dengue fever inpatients admitted to the People’s Hospital of Dai Autonomous Prefecture of Xishuangbanna from September to November 2019 were enrolled in this study. Patients were diagnosed based on the Guidelines for the Diagnosis, Treatment, Prevention and Control of Dengue Fever ( World Health Organization, 2009 ). Data on clinical symptoms and laboratory tests were collected for the analysis. Laboratory test data included the white blood cell count (WBC) and the platelet count (PLT). The overall study design is shown in Figure 2 .

Figure 2. Study design and participants.

Mosquito-Borne Virus Identification

A total of 225 DENV-positive serum samples of inpatients were collected from inpatients in the People’s Hospital of Dai Autonomous Prefecture of Xishuangbanna. Dengue NS1 antigen was detected using a DF NS1 test kit (Blue Cross, Beijing, China). Viral RNA was extracted from 140 μL of serum using a QIAamp Viral RNA Mini Kit (QIAGEN, Hilden, Germany) according to the manufacturer’s instructions and stored at −80°C. Viral RNA was used for PCR the identification of the dengue viral subtypes, Zika virus (ZIKV), Japanese encephalitis virus (JEV) and Chikungunya virus (CHIKV), following the identification of flavivirus. The primers were as Supplementary Table 1 shown ( Wang et al., 2016 ). All dengue virus PCR positive samples were labeled for the next step, which included the amplification of the whole gene or the structural protein nucleic acid sequence.

IgG and IgM Antibodies of DENV Detection

DENV IgG and IgM antibodies were detected by enzyme-linked immunosorbent assay (ELISA) (Order Nr: IB05044 or IB05045, Immuno-Biological Laboratories, Inc., Minneapolis, MN, United States) in 225 DENV-positive serum samples of inpatients, according to the instructions of the manufacturer.

Determination of Primary and Secondary Dengue Virus Infection

The judgment basis of primary and secondary infection was defined as follows ( Wei et al., 2016 ): for specimens taken less than 7 days after the onset, both IgM and IgG antibodies were negative, the judgment could not be made. If the IgM antibody was positive, IgG antibody was negative, the judgment was primary infection. The judgment of secondary infection is that both antibodies are positive, or if IgM antibody was negative, IgG antibody and the DENV RNA are both positive.

Analysis of the Amino Acid Sequence of DENV Structural Proteins (C-PrM-E)

Twenty DENV nucleic acid-positive samples were randomly selected to sequence the nucleic acid sequence of DENV structural proteins and then translated into amino acids with BioEdit 7.0. The C-PrM-E structure was used to build a protein structure model with amino acid sequences by the SWISS-MODEL ( expasy.org ).

Amplification of the Full-Length Genome and Analysis of Isolated DENV Nucleotides

Serum from 3 DF inpatients and 3 SD inpatients was selected for sequencing the full-length genome of DENV, all the six samples were from the same twenty DENV nucleic acid-positive samples used. The primers were used in this study were from our former study ( Jiang et al., 2018 ). Sequences were analyzed using BioEdit 7.0 and compared with sequences available from the BLAST database ( blast.ncbi.nlm.nih.gov/Blast.cgi ). Phylogenetic analyses were performed using the neighbor-joining method with the Tajima-Nei model (MEGA, version 6.0 1 ). The DENV genotype was analyzed using the related reference sequences in NCBI (National Center for Biotechnology Information, Minneapolis, MN, United States) and with known genotypes in the phylogenetic tree. The information of reference sequences were shown in Supplementary Table 2 .

Statistical Analysis

The continuous variables were described by the mean ± standard deviation, and the categorical variables were described by the constituent ratio. Differences or associations with p -values <0.05 were considered significant. All data analyses were performed using SPSS 22.0 software (IBM, Armonk, NY, United States) and GraphPad Prism 7.

Ethical Approval

Institutional Review Board approval was obtained from the Ethics Committee of the Institute of Medical Biology, Chinese academy of Medical Sciences, China. All procedures that were performed in the studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Basic Characteristics of Dengue Inpatients

In this study, there were 102 SD patients among the 225 dengue inpatients. Compared with the general dengue patients, the proportions of male and Han nationality inpatients with SD were larger ( p < 0.05) ( Table 1 ). The mean age of DF inpatients was 48.67, the median was 49 (2–97). The youngest is 2 years old and the oldest is 92 years old in DF. The mean age of SD inpatients was 46.14, and the median was 43 (13–88). The youngest is 13 years old and the oldest is 88 years old in SD. The ratio of males to females in SD was 1.76, which was higher than that in DF (0.81). The clinical symptoms were more serious in SD. Compared with DF, the number of low platelet counts (PLT) in SD was greater than that in dengue patients ( p < 0.01). Unexpectedly, other clinical sympt o ms, including fever, vomiting, muscle pain, bleeding, coma, convulsions, and white blood cell counts (WBT), between DF and DHF were no significant differences.

Table 1. Comparison of characteristics of moderate and severe dengue fever inpatients.

A total of 23 diabetics and 29 hypertension patients were found in 225 dengue inpatients. There were 11 inpatients suffering from both two diseases, and 3 of them are SD inpatients. As Table 1 shown, in DF inpatients, 10.57% of patient have diabetes or hypertension, 4.89% have both two diseases. As for SD inpatients, 9.80% of patient have diabetes, 15.69% have hypertension, and only 2.94% have both two diseases. There is no statistical difference between the two groups.

Mosquito-Borne Virus or Virus Coinfection Identification

After nucleic acid samples were extracted and evaluated with specific primers for the presence of different viruses (DENV 1-4, ZIKV, CHIKV, JEV), 54 DENV-1 and 22 DENV-2 were found in 102 samples of sera of SD inpatients. There was one coinfected DENV-1 patient with ZIKV and five coinfected DENV-2 patients with ZIKV. All other viruses were negative. Similarly, among 122 common DF inpatients, there were 19 DENV-1, 45 DENV-2 and 3 DENV-3. The main epidemic serotype of DF inpatients was DENV-2, but the main serotype of SD patients was DENV-1, as shown in Table 2 .

Table 2. Mosquito-borne virus (DENV 1-4, ZIKV, CHIKV, JEV) or virus coinfection identification.

IgG and IgM were detected in 85 DF inpatients, of which 44 were IgM positive and 19 were IgG positive, as shown in Table 3 . In all IgG-positive inpatients, the onset time was less than or equal to 7 days in 17 cases and more than 7 days in 2 cases. IgG and IgM were detected in 95 patients with SD. Among them, 90 patients were IgM positive, and 84 patients were IgG positive. Among all the IgG-positive patients, 78 had an onset time less than or equal to 7 days. According to the judgment basis of primary and secondary infections as previously described in the methods, 78 were secondary infections in SD inpatients and 17 were secondary infections in DF inpatients.

Table 3. IgG and IgM antibodies for DENV detection in dengue inpatients.

Analysis of the Amino Acid Sequence of DENV Structural Proteins (C/PrM/E)

The amino acid sequences of DENV-1, DENV-2 and DENV-3 structural proteins (C/prM/E) were compared by BioEdit. In DENV-1s, compared with the strain KY672931.1 (2015), there were three amino acid mutations of the C protein in strain 5 (2019), from proline(P) to Serine (S), Arginine (R) to Lysine (K) and K to R. Two amino acid mutations were observed in the E protein, including a Leucine (L) to Isoleucine (I), Valine (V) to Alanine (A), and but there were no mutations in the PrM protein. In DENV-2s, compared with strain KY672955.1 (2015), there was one amino acid mutation in the C protein in 15 (2019), K to R. Two amino acid mutations in the PrM protein included K to R, V to A, and one amino acid (L to I) mutation in the E protein. In DENV-3s, compared with strain KR296743.1 (2013), there were two amino acid mutations in the C protein, K to R, asparagine (N) to I, five amino acid mutations in the PrM protein, and ten amino acid mutations in the E protein.

The possible three-dimensional structures of the structural proteins of DENV-1, DENV-2 and DENV-3 in 2019 were later predicted and compared with those of the same type of DENV in Xishuangbanna Prefecture as previously ( Table 4 ). Homology modeling revealed that four strains of DENV-1/DENV-2 had the same three-dimensional structure. However, the two strains of DENV-3 were different. Among the 21 mutation sites in C/prM/E, there were 11 hydrophobic amino acids and 10 hydrophilic amino acids in 2013. However, there were 8 hydrophobic amino acids and 13 hydrophilic amino acids in 2019. The decrease in hydrophobic amino acids in 2019 led to a looser structure than the strain in 2013.

Table 4. The amino acid sequences of DENV-1, DENV-2 and DENV-3 structural proteins (C/prM/E) were compared by BioEdit, and the protein structure was predicted by SWISS-MODEL ( expasy.org ).

Phylogenetic Analysis of Isolated DENV Nucleotide

To analyze whether the sequence is a factor for the severity of dengue patients, we randomly selected three DENV-2 strains from each of the severe and mild patients for whole genome sequencing. After sequencing, nucleic acid and amino acid sequences were analyzed.

In the nucleotide composition analysis, the sequences from DF inpatients (DF10, DF11, and DF15) or SD inpatients (SD9, SD92, and SD106) were compared with other sequences in China from different years, including the strains, MF940237.1 (China Yunnan Province 2015), MN018339.1 (China Guangdong Province 2014), MN018337.1 (China Guangdong Province 2015), MN018340.1 (China Guangdong Province 2016), MN018341.1 (China Guangdong Province 2017), MK783207.1 (China Guangdong Province 2018), and the DENV-2 standard strain NCBI Reference Sequence (NC 001474.2). The results showed that the GC/AT of DENV-2 in China decreased from 2014 to 2018, except the MN018341.1 strain (China Guangdong Province 2017) ( Table 5 ). However, the GC/AT in five of six strains increased in 2019, and the portion rose to the level of 2014. Compared with the other five strains, the GC/AT of DF15 was closer to that of MK783207.1 (China Guangdong Province 2018). Compared with DF strains, SD strains had no mutations of commonness. Although DF15 is different from other virus strains, an evolutionary tree analysis showed that it belongs to the cosmopolitan type, similar to the other five viruses. According to the phylogenetic analysis, DENV-2 of the 2019 dengue outbreak in Yunnan most likely originated from the China Guangdong Province or Thailand, not Yunan Province ( Figure 3 ).

Table 5. Basic information on the DENV-2 sequences was analyzed by BioEdit.

Figure 3. Neighbor-joining phylogenetic tree generated using the nucleotide sequences of complete dengue virus sequences. Study sequences are labeled in black triangles or hollow circles. Others are standard sequences, including sequences of the DENV-2 subgenotype retrieved from the NCBI GenBank. Phylogenetic trees were constructed by the neighbor-joining method and the Kimura 2-parameter model by the MEGA package.

Dengue poses a large burden on the public health systems worldwide. Due to the lack of an ideal animal model, the pathogenesis of dengue has not yet been elucidated. SD is currently believed to be mainly related to secondary heteromorphic DENV infection, coinfection of mosquito-borne viruses, viral variation and host immune response ( Simmons et al., 2012 ; St. John et al., 2013 ). The purpose of this study was to investigate the clinical characteristics and risk factors for severe dengue fever in Xishuangbanna, during the dengue outbreak in 2019.

As a more serious consequence of dengue, SD patients often have more serious clinical symptoms. However, in this outbreak, the only significant difference between SD and dengue patients is the platelet counts. The number of low platelet counts in SD was greater than that in dengue patients ( p < 0.01). But there were no significant differences between DF and DHF in other clinical symptoms. The small sample size was the main reason for those results and the basic characteristics of certain groups were also very important for the pathogenesis of SD. In South America, Southeast Asia and other countries, SD is considered to occur in children and infants ( Sharp et al., 2017 ). However, in this study, there were only two SD inpatients (13 and 18 years old) younger than 18 years old. The mean ages of SD and DF were 46.14 and 48.67, respectively, which were not significantly different. Compared with DF inpatients, SD inpatients were more likely to be male and of Han nationality ( p < 0.05). The formation of SD is not related to age but is related to gender. The reason may be that the spread of dengue is related to the population mobility. Compared with females, males have a larger proportion of migrant workers and are more vulnerable to mosquito bites, which are more likely to lead to SD.

In 2019, there were 22599 cases of dengue fever, with an incidence rate of 1.63/10 million ( Liu, 2020 ). As a typical dengue epidemic area, in 2019, the main epidemic type in Xishuangbanna Prefecture was DENV-1, with an incidence rate of up to 67%. DENV-2 accounted for 32%, and only one patient had DENV-3, which was consistent with our assumption that the epidemic trend was dengue virus. Although DENV-1 was prevalent in Xishuangbanna in 2017, DENV-1 was still prevalent in Xishuangbanna in 2019. According to former studies, DENV-2 and DENV-3 are more likely to cause SD than DENV-1 and DENV-4 ( Fried et al., 2010 ). Among the first infections of this outbreak, 6 SD inpatients were infected with DENV-2, and 3 SD inpatients were infected with DENV-1. After infection with one DENV serotype for the first time, the serogroup cross reactive antibody produced by the host usually can only protect from other serotypes of DENV infection for 3–6 months. When the host is reinfected with heterotypic DENV, the E or PrM antibody produced by the first infection causes a subneutralization titer in the body and forms an immune complex with the virus being infected, increasing the infection rate and replication of the virus ( Murphy and Whitehead, 2011 ). Therefore, we compared the nucleic acid sequence of the PrM protein of the DENV strain in 2019 with that of the dengue virus strain in the same area. Compared with the previous same virus strain genotype, little difference was observed in the primary structure of DENV-1 and DENV-2, but the higher structures were the same. DENV-3 had some differences in the primary structure, which led to different higher structures. These results indicated that DENV-1 and DENV-2 may be more stable than DENV-3. Previous epidemiological studies have shown that the outbreak of DENV-3 and DENV-2 occurred earlier than that of DENV-1 and was more able to lead to subneutralization titers in first infected people. Thus, DENV-1 should be the main serotype in subsequent secondary infections. Among the secondary infection SD inpatients in this study, 50 (%) were DENV-1 and 13 (%) were DENV-2, which was consistent with our study.

ZIKV, CHKIV, and JEV are also transmitted by the mosquito. When there were multiple arboviruses in one place at the same time, humans may be infected with different types of arboviruses at the same time through mosquito bites. In this study, we compared the coinfection of ZIKV, CHIKV, and JEV in SD or DF to explore whether coinfection can lead to an increase in SD. After detection, six inpatients were infected with ZIKV in the SD group, and 0 were infected in the DF group. However, the clinical symptoms of these six coinfected inpatients were not obviously different from those of other SD patients. These results suggested that coinfection may not lead to an aggravation of the symptoms. Unfortunately, among the six ZIKV infected patients, the serum collection time of five of them is longer than 7 days, and the possibility of secondary dengue infection cannot be ruled out. Due to the small number of coinfections in this cohort, more patients needed to be enrolled, to study the role of ZIKV coinfection in SD patients.

The virulence of viruses could influence the occurrence of SD ( Tuiskunen et al., 2011 ). In this study, we selected three DENV-2 epidemic strains from DF or DHF patients and performed whole genome sequencing and analysis. Compared with the sequences before 2019, the GC/AT in five of six strains increased in 2019. However, there was no regularities of the mutations between SD and DF sequences. The results showed that all the sequences from DF and SD belonged to cosmopolitan, and five of them were in a cluster.

The aim of this study was to investigate the causes of SD through the demographic information of SD patients, the co-infection of mosquito-borne viruses, the identification of DENV serotypes, the presence of DENV secondary infections, and the characteristics of the samples of the DENV complete genomes in Xishuangbanna, 2019 ( Zhang et al., 2021 ). The prevalence of three dengue virus serotypes before 2019 might mediate subneutralization titer antibodies and lead to secondary infections, increasing the number of severe dengue patients in Xishuangbanna in 2019. The results of this study might provide insight into early prognostic factors associated with a severe disease progression and improve the rates of early diagnosis and successful treatment. The currently datas were very limited and only suggestive. More dengue patients should be recruited for those study. More other risk factors, especially environmental factors, the basic situation of patients should be included in those studys.

Data Availability Statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/genbank/ , MZ452990-MZ453011.

Ethics Statement

The studies involving human participants were reviewed and approved by the Ethics Committee of the Institute of Medical Biology, Chinese academy of Medical Sciences, China. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.

Author Contributions

XW and QS have drafted and revised the manuscript. XW contributed to the sequencing, major experiment and analysis of data. QS and PL have designed and administered the study. TL, YS, JZ, XS, and DL contributed to sample collection. All other co-authors contributed to its finalization and approval for publication.

This research was supported by the National Natural Science Foundation of China (31970868), the Youth Project in Yunnan Province (2019FD082), the Foundation of Yunnan Innovation Team (202105AE160020), Major Projects and Key Research and Development Plans of Yunnan Province (2019ZF004), and Yunnan health training project of high level talents (L-2019030, H-2017052).

Conflict of Interest

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

Publisher’s Note

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

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2022.739970/full#supplementary-material

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Keywords : severe dengue fever, IgG, IgM, dengue inpatients, dengue gene sequence

Citation: Wang X, Li T, Shu Y, Zhang J, Shan X, Li D, Ma D, Long S, Pan Y, Chen J, Liu P and Sun Q (2022) Clinical Characteristics and Risk Factors for Severe Dengue Fever in Xishuangbanna, During the Dengue Outbreak in 2019. Front. Microbiol. 13:739970. doi: 10.3389/fmicb.2022.739970

Received: 12 July 2021; Accepted: 25 January 2022; Published: 10 March 2022.

Reviewed by:

Copyright © 2022 Wang, Li, Shu, Zhang, Shan, Li, Ma, Long, Pan, Chen, Liu and Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Qiangming Sun, [email protected] ; Pinghua Liu, [email protected]

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

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Peer-reviewed

Research Article

Risk and predictive factors for severe dengue infection: A systematic review and meta-analysis

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing

Affiliation Division of Clinical Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, P.R. China

Roles Data curation, Investigation, Methodology, Validation, Writing – review & editing

Roles Data curation, Validation, Writing – review & editing

Roles Conceptualization, Supervision, Validation, Writing – original draft, Writing – review & editing

* E-mail: [email protected] (YL); [email protected] (LL)

Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Supervision, Validation, Writing – original draft, Writing – review & editing

• Kangzhuang Yuan, 
• Yuan Chen, 
• Meifeng Zhong, 
• Yongping Lin, 

• Published: April 15, 2022
• https://doi.org/10.1371/journal.pone.0267186
• Peer Review
• Reader Comments

Dengue is a major public health issue worldwide and severe dengue (SD) is life threatening. It is critical to triage patients with dengue infection in the early stage. However, there is limited knowledge on early indicators of SD. The objective of this study is to identify risk factors for the prognosis of SD and try to find out some potential predictive factors for SD from dengue fever (DF) in the early of infection.

The PubMed, Cochrane Library and Web of Science databases were searched for relevant studies from June 1999 to December 2020. The pooled odds ratio (OR) or standardized mean difference (SMD) with 95% confidence intervals (CI) of identified factors was calculated using a fixed or random effect model in the meta-analysis. Tests for heterogeneity, publication bias, subgroup analyses, meta-regression, and a sensitivity analysis were further performed.

A total of 6,848 candidate articles were retrieved, 87 studies with 35,184 DF and 8,173 SD cases met the eligibility criteria. A total of 64 factors were identified, including population and virus characteristics, clinical symptoms and signs, laboratory biomarkers, cytokines, and chemokines; of these factors, 34 were found to be significantly different between DF and SD, while the other 30 factors were not significantly different between the two groups after pooling the data from the relevant studies. Additionally, 9 factors were positive associated with SD within 7 days after illness when the timing subgroup analysis were performed.

Conclusions

Practical factors and biomarkers for the identification of SD were established, which will be helpful for a prompt diagnosis and early effective treatment for those at greatest risk. These outcomes also enhance our knowledge of the clinical manifestations and pathogenesis of SD.

Citation: Yuan K, Chen Y, Zhong M, Lin Y, Liu L (2022) Risk and predictive factors for severe dengue infection: A systematic review and meta-analysis. PLoS ONE 17(4): e0267186. https://doi.org/10.1371/journal.pone.0267186

Editor: Mao-Shui Wang, Shandong Public Health Clinical Center: Shandong Provincial Chest Hospital, CHINA

Received: May 18, 2021; Accepted: April 5, 2022; Published: April 15, 2022

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

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This work was funded by Guangzhou Science Technology and Innovation Committee ( https://sop.gzsi.gov.cn/egrantweb/ , NO. 201607010163 awards to Lidong Liu), Health and Family Planning Commission of Guangdong Province ( http://wsjkw.gd.gov.cn/ , NO. A2016448 awards to Lidong Liu) and Guangzhou Medical University ( https://www.gzhmu.edu.cn/ , NO.2014C24 awards to Lidong Liu). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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

Introduction

Dengue disease is a mosquito-borne viral infection caused by the dengue virus (DENV). Patients infected with DENV have a wide spectrum of clinical manifestations, ranging from asymptomatic to dengue fever (DF) or severe dengue (SD), including dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS) [ 1 , 2 ]. The World Health Organization (WHO) estimated that approximately 2.5 billion people living in dengue-endemic countries [ 3 ]. With an increasing incidence of DENV infections each year, it was estimated that there were 390 million dengue infections per year, of which 96 million manifested symptomatically [ 4 ]; additionally, it was estimated that there were 565,900 disabilities and 9110 deaths in 2013 [ 5 ]. The first licensed recombinant, live-attenuated dengue vaccine (Dengvaxia) recently became clinically available. However, a high risk of adverse outcomes was found among vaccinated individuals who had not been previously exposed to dengue [ 6 , 7 ]. Severe and fatal cases were consistently reported in some endemic areas, such as Southeast Asia, the Western Pacific, and the Americas [ 8 – 10 ]. It has been reported that the DSS mortality is 50 times higher than that of DF [ 11 ], and SD has been a leading cause of serious illness and death among children in some Asian and Latin American countries [ 3 ]. Previous data showed that the SD mortality would decrease from more than 20% to less than 1% if SD were identified and properly treated in a timely fashion [ 3 ]. Hence, the early prediction and recognition of severe cases are critical for dengue disease management.

To help clinicians evaluate the likelihood of severe disease, risk factors for SD have been reported, such as secondary infection, gastrointestinal pain, vomiting, diarrhea, intravascular leakage and bleeding [ 12 ]. Efforts have been consistently made to identify predictive markers for SD [ 13 – 15 ]. Although dengue with warning signs (WS) was referenced in the newly updated WHO guideline [ 1 ], a multicenter study reported that approximately 30% of adults with DF had WS and only 10% developed SD [ 16 ], while another study showed that the sensitivity and specificity of WS were 59–98% and 41–99%, respectively, when they were used to identify SD [ 17 ]. Numerous potential markers for SD have been reported but some have been inconclusive [ 18 – 20 ]. To distinguish SD from DF in the early of infection and try to find out some potential predictive factors, we conducted this systematic review and meta-analysis.

Literature search and study selection

This systematic review was performed according to the recommendations of the PRISMA statement [ 21 ] ( S1 Checklist ) .

The PubMed, Cochrane Library, and Web of Science online databases were systematically searched June 1999 to December 2020. The search was performed using the following query: (dengue) and ((shock) or (severe) or (severity) or (dss) or (dhf) or (dengue shock syndrome) or (dengue haemorrhage fever)). Moreover, the references of included studies and relevant reviews were manually retrieved to collect more studies.

Studies that met the following criteria were included: (1) dengue infections were confirmed by laboratory tests; (2) there were SD and DF groups with characteristic data, such as epidemiological factors, clinical signs, and laboratory parameters; (3) the studies provided original data; (4) the papers were written in English.

Studies meeting the following criteria were excluded: (1) papers with unavailable full texts or data; (2) case reports, reviews, animal studies and in vitro studies; (3) genetic studies; (4) duplicate publications.

All titles and abstracts were first independently reviewed by two authors. The full texts of studies that were potentially eligible to be included were obtained for further reading and scrutiny. Disagreements were resolved by consulting a third author.

Quality assessment

The Newcastle-Ottawa quality assessment scale (NOS) [ 22 ] was used to evaluate the quality of the included studies. Scores were determined by nine metrics: data collection, assignment of the patients, inclusion criteria, exclusion criteria, characteristics of the patient population, interpretation of other characteristics, methodological quality, interpretation of factors and dengue diagnosis. Two authors independently assessed the quality of each original study. Studies were defined as being of low, intermediate, and high quality according to NOS scores of 1–3, 4–6, and 7–9, respectively. The scoring system is available in S1 Table .

Data extraction

Data were independently extracted by two authors if that were presented at least two studies, and the following information was included: the first author, publication date, country/city of origin, patient recruitment period, age of patients, data type, diagnostic method, criteria for diagnosis, sampling time, quality score, and number of cases. DHF, DSS, and SD were defined collectively as SD in this study. Data that could not be reliably extracted or that overlapped were excluded. When duplication was noted, the largest data set was chosen for the meta-analysis. The information is recorded in S2 Table .

Statistical analyses

A meta-analysis for predictive factors was carried out using STATA version 12.0 (STATA Corporation, College Station, TX, USA). Heterogeneity was assessed using the Cochran Q test with its corresponding p values and I 2 statistic. I 2 values of 25%, 50%, and 75% indicated low, moderate, and high levels of heterogeneity, respectively. Heterogeneity was considered statistically significant if the p value was ≤0.10 and I 2 was >40% [ 23 , 24 ]. A random-effect model was used when there was significant heterogeneity; otherwise, a fixed-effect model was used [ 25 ]. Dichotomous and continuous variables were analyzed by calculating the pooled odds ratio (OR) and standardized mean difference (SMD), respectively, with 95% confidence intervals (CI) using a fixed or random effect model.

To explore the potential sources of high heterogeneity among the studies, subgroup analyses and meta-regression were performed for sampling time (≤7 days after onset), the population, data type, criteria for diagnosis, area of origin and study quality, when there were more than ten datasets included [ 26 , 27 ]. The effect of co-variants was considered significant when p was < 0.05 or the 95% CI did not overlap with the original data.

Publication bias was assessed by Begg’s funnel plot and Egger’s linear regression test when there were more than ten datasets included [ 28 , 29 ], and the trim and fill method from Duvall and Tweedie was used by adding studies that appeared to be missing to enhance the symmetry when publication bias was found ( p <0.05) [ 30 ]. The adjusted pooled effect size and 95% CI were computed after adding the potential missing studies. In addition, the sensitivity analysis was carried out using the leave-one-out method to test whether a potential outlier within the included studies could have influenced the meta-analysis summary effects [ 31 ].

Previous studies showed that dengue virus was an important cause of childhood and adult morbidity in Asian and Latin American countries [ 32 ] and people with African ancestry were less susceptible to the severe manifestations of dengue infection [ 33 , 34 ]. Therefore, the subgroups of Asia and America were compared in the Meta-analysis. And sensitivity and sub-analysis of co-variables on the summary effect and heterogeneity were performed for factors with more than ten studies included using the one study omitting analyses to test whether a potential outlier within included studies could have influenced the meta-analysis summary effects [ 31 ].

A total of 6848 studies were identified after the initial search of the databases. After the screening of titles and abstracts, 364 potentially relevant papers were retrieved for detailed assessment, and 87 studies with 35,184 DF and 8,173 SD cases were included in the meta-analysis based on the inclusion and exclusion criteria. A total of 34 factors were found to be significantly different between DF and SD, age, diabetes history, secondary infection, seroDENV-2/3, bleeding, vomiting, ascites, pleural effusion, lethargy and petechiae, were positive associated with SD; HCT, ALT, AST, CK, BUN, LDH, IL-10, IL-8, sVCAM-1, and IP-10 were increasing but total protein, albumin and PLT were decreasing in level during SD. The study selection flow diagram is depicted in Fig 1 .

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0267186.g001

Identification of studies

A total of 87 studies published from January 2000 to December 2020 were ultimately included in the study, and 66 (75.9%), 19 (21.8%), 1 (1.1%), and 1 (1.1%) study originated from Asia, the Americas, Europe, and Oceania, respectively. The WHO 1997 [ 2 ], WHO 2009 [ 1 ], WHO 2011 [ 35 ], WHO 1999b [ 36 ] and Brazilian guidelines [ 37 ] were used for identifying SD in 53 (60.9%), 25 (28.7%), 5 (5.7%), 1 (1.1%) and 3 (3.4%) studies, respectively. The final articles consisted of 53 (60.9%) retrospective, 27 (31.0%) prospective and 7 (8.0%) cross-sectional studies. Based on the NOS scores, 30(34.5%), 55 (63.2%) and 2 (2.3%) studies were of high, inter-mediate and low quality, respectively ( S2 Table ). Twenty-two (25.3%) studies reported a population of children, 27 (31.0%) reported adult populations, 31 (35.6%) reported both and 7 (8.0%) did not describe the populations. Fifty-one studies stated the sampling time, of which 23 stated it was less than 7 days after onset when the samples were drawn. The details of the included studies are presented in S3 Table . Twenty-eight factors ( I 2 >40%) were analyzed for sensitivity and 24 factors were heterogeneous in the subgroup meta-analysis except age and gender in population, hepatomegaly, vomit, and pleural effusion in sampling time ( S4 Table ).

Systematic analysis and meta-analysis

The data sets for 64 factors were extracted from at least two studies. Thirty-four factors were significantly different between patients with DF and those with SD ( Table 1 ), and 30 factors were not correlated with severity ( S5 Table ). A total of 21 factors were identified and 9 revealed positive association with SD within 7 days after onset in the timing subgroup analysis ( S5 Table ).

https://doi.org/10.1371/journal.pone.0267186.t001

Characteristics of the populations.

Age, gender, and diabetes history were identified. After pooling relevant studies, age and diabetes history were positively associated with SD in 46 (SMD = 0.151, 95% CI: 0.027–0.275, p = 0.017) and 9 (OR = 4.418, 95% CI: 2.698–7.232, p <0.001) studies with high heterogeneity ( I 2 = 82.4%, p <0.001; I 2 = 80.4%, p <0.001), respectively. Furthermore, meta-regression analysis revealed that the population and sampling time contributed to the heterogeneity of age. However, based on the subgroup analyses, childhood had no correlation with severity in 10 studies (SMD = 0.004, 95% CI: -0.096–0.104, p = 0.679) without heterogeneity ( I 2 = 0.0%, p = 0.679); and age revealed no correlation with severity in 5 studies (SMD = 0.048, 95%CI: -0.192–0.095, p = 0.510) with low heterogeneity ( I 2 = 10.5%, p = 0.346) within 7 days after onset. Additionally, gender did not correlate with SD ( S6 Table ). Summary effects did not change significantly when the leave-one-out analyses were conducted.

Viral characteristics.

Eighteen studies encompassing 7,659 cases reporting the dengue serotypes together with their severity were obtained, 13 of which originated from Asia and 5 from the Americas. The prevalence rates of DENV-1, DENV-2, DENV-3, and DENV-4 were 39.9%, 29.1%, 19.6% and 11.3%, respectively. A similar seroprevalence distribution in 6,847 cases in Asia was found, with rates of 37.1%, 31.6%, 19.8% and 11.6%, respectively. In contrast, in 812 cases from the Americas, the seroprevalence rates were 63.9%, 8.3%, 18.2% and 9.6%, respectively.

After pooling 17 studies, DENV-2 was positively associated with SD (OR = 1.843, 95% CI: 1.269–2.678, p = 0.001), whereas DENV-1 and DENV-3 had a negative association in 15(OR = 0.709, 95% CI: 0.504–0.997, p = 0.048) and 16(OR = 0.694, 95% CI: 0.492–0.979, p = 0.037) studies, respectively. However, in the subgroup analysis of epidemic areas, DENV-1 revealed an inconsistent result with SD in Asia (OR = 0.810, 95% CI: 0.594–1.104, p = 0.182) and in the Americas (OR = 0.230, 95% CI: 0.044–1.215, p = 0.084); DENV-3 revealed a similar result with SD (OR = 0.650, 95% CI: 0.511–0.828, p <0.001) in Asia but opposite in the Americas (OR = 2.226, 95% CI: 0.080–61.821, p = 0.637). DENV-4 showed no significant difference between the two groups in 9 studies. The details are presented in Fig 2 . In addition, the pooled odds ratio of secondary infection in 22 studies revealed a positive association with SD (OR = 2.693, 95% CI: 2.083–3.481, p <0.001). Also, it revealed a consistent association with SD in 4 studies (OR = 2.448, 95% CI: 0.955–6.277, p = 0.062) within 7 days after onset. Excluding individual studies did not change the summary effects significantly.

A: DENV-1; B: DENV-2; C: DENV-3; D: DENV-4.

https://doi.org/10.1371/journal.pone.0267186.g002

Clinical manifestations.

Days of illness was observed to be much longer in SD (SMD = 0.614, 95% CI: 0.346–0.882, p = 0.000) after pooling 21 studies. Lethargy/dizziness had a positive association with SD (OR = 2.563, 95% CI: 1.517–4.329, p <0.001) after pooling data from 8 studies. Vomiting and abdominal pain were observed to be risk factors for SD in 26 (OR = 1.533, 95% CI: 1.203–1.953, p = 0.001) and 33 (OR = 1.850, 95% CI: 1.466–2.335, p <0.001) studies, respectively, with high heterogeneity. In particularly, persistent vomiting as one of the WS was referred to in 3 studies and had a strong positive pooled effect (OR = 5.569, 95% CI: 3.041–10.000, p <0.001). Diarrhea was also associated with SD in 16 studies (OR = 1.245, 95% CI: 1.008–1.537, p = 0.042) with low heterogeneity ( I 2 = 15.8%, p = 0.273). Additionally, hepatomegaly was highly correlated with SD in 17 studies (OR = 4.403, 95% CI: 3.016–6.430, p <0.001). Hepatomegaly revealed a similar association with SD in 2 (OR = 9.264, 95% CI: 7.034–12.201, p <0.001) studies with low heterogeneity ( I 2 = 0.0%, p = 0.402) within 7 days after onset. The high heterogeneity and summary effect did not change significantly when subgroup analyses of other covariables and leave-one-out analyses were conducted.

Bleeding signs.

Skin rash, petechiae, hematemesis, melena, gum bleeding, epistaxis, and the tourniquet test were identified as bleeding signs in this study. Severe bleeding, including hematemesis, melena, gum bleeding, and epistaxis, had a strong association with SD (OR = 6.856, 95% CI: 4.160–11.300, p = 0.000) after pooling data from 32 studies. It showed a positive association with SD (OR = 8.106, 95% CI: 3.094–21.241, p <0.001) as well when the sampling time subgroup analysis was performed in 7 studies. Additionally, petechiae had a positive association (OR = 2.508, 95% CI: 1.720–3.655, p = 0.000) after pooling data from 19 studies with moderate heterogeneity ( I 2 = 57.2%, p = 0.001).

Plasma leakage.

Pleural effusion and ascites had a strong association with SD after pooling data from 19 (OR = 15.838, 95% CI: 6.974–35.967, p <0.001) and 12 (OR = 24.299, 95% CI: 4.337–136.138, p <0.001) studies, respectively. However, there was publication bias in favor of positive studies according to Egger’s test ( p <0.05) for both. Using the trim and fill method from Duval and Tweedie, no studies was added for ascites, and the positive association remained after 7 missing studies were added for pleural effusion (original OR = 2.731, 95% CI: 1.939–3.521, p = 0.000; adjusted OR = 1.823, 95% CI: 1.114–2.533, p = 0.000). Both revealed a stronger association with SD within 7 days after onset in 2 studies (OR = 87.143, 95% CI: 10.962–693.405, p <0.001; OR = 83.578, 95% CI: 3.786–1844.938, p = 0.005). The details are described in Fig 3 . Additionally, hypotension was observed to be a risk factor for SD (OR = 3.692, 95% CI: 1.670–8.162, p = 0.001) in 11 studies, and publication bias was found. Using the trim and fill method from Duval and Tweedie, 4 missing studies were added, and the association remained unchanged (original OR = 0.672, 95% CI: 0.318–1.025, p <0.001; adjusted OR = 0.452, 95% CI: 0.110–0.793, p = 0.010). The high level of heterogeneity was not reduced, and the summary effect changed significantly when the leave-one-out analyses and subgroup analyses of covariables were conducted.

(A, B) Forest plot for pleural effusion, ascites respectively DF vs SDD, OR: odds ratio. (C, D) Funnel Plots for pleural effusion, ascites respectively (Trim and Fill) DF vs SDD, SE: standardized error.

https://doi.org/10.1371/journal.pone.0267186.g003

Blood cell counts.

Among the markers investigated, a decrease in the platelet count was observed in 38 studies and was revealed to be a risk factor for SD (SMD = -1.070, 95% CI: -1.293–0.848, p <0.001). However, publication bias was observed ( p <0.05). After 7 missing studies were added, the association was stronger (original SMD = -1.070, 95% CI: -1.293–0.848, p <0.001; adjusted SMD = -1.384, 95% CI: -1.665–1.102, p <0.001). Furthermore, another twelve dichotomous datasets were pooled and revealed that thrombocytopenia was strongly associated with SD (OR = 8.146, 95% CI: 3.374–19.665, p <0.001). Additionally, the quantitative analysis showed that hematocrit (HCT) was positively associated with SD (SMD = 0.327, 95% CI: 0.109–0.546, p = 0.003) in 27 studies, and there were 7 dichotomous datasets with elevated HCT levels, which was strongly associated with SD (OR = 12.389, 95% CI: 6.091–25.199, p <0.001). Moreover, sampling time (≤7 days after onset) subgroup analysis was performed and platelet count, thrombocytopenia and HCT were also observed to be risk factors of SD in 10 (SMD = -1.452, 95% CI: -1.872- -1.031, p <0.001), 3 (OR = 48.931, 95% CI: 1.873–1278.431, p <0.001), 7 (SMD = 0.706, 95% CI: 0.122–1.291, p = 0.018) studies, respectively.

Hepatic and renal manifestations, lipids.

Within the list of serum markers, the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were significantly higher in patients with SD than in those with DF (SMD = 1.007, 95% CI: 0.386–1.627, p = 0.001; SMD = 1.278, 95% CI: 0.640–1.916, p <0.001); Also, AST revealed a stronger association with SD in 7 studies (SMD = 1.712, 95% CI: 0.276–3.148, p = 0.019) within 7 days after onset. Additionally, the summary effect of elevated ALT and AST also showed a stronger association with SD after pooling 8 (OR = 4.030, 95% CI: 2.408–6.747, p <0.001) and 4 (OR = 4.053, 95% CI: 2.255–7.287, p <0.001) studies, respectively. However, publication bias was observed on Begg’s test for ALT ( p <0.05) and AST ( p <0.05); no study was added using the trim and fill method. Albumin (ALB) and total protein (TP) levels were significantly lower in patients with SD than in those with DF after pooling 13 (SMD = -0.767, 95% CI: -0.989–0.544, p <0.001) and 5 (SMD = -0.271, 95% CI: -0.449–0.093, p = 0.003) studies, respectively. Meanwhile, hypoproteinemia, hypoalbuminemia, proteinuria, and increased levels of creatine kinase (CK), lactate dehydrogenase (LDH) and blood urea nitrogen (BUN) were positively associated with SD ( Table 1 ).

Coagulation tests.

Prolonged prothrombin time (PT) and activated partial thromboplastin time (APTT) were found to be significantly associated with SD after pooling 6 studies (SMD = 0.781, 95% CI: 0.219–1.343, p = 0.006; SMD = 0.529, 95% CI: 0.046–1.013, p = 0.032). However, the summary effect of prolonged PT, prolonged APTT, and elevated D-dimer levels had a negative association with SD in two dichotomous datasets ( S5 Table ).

Cytokines and chemokines.

Various detection methods and descriptions of the results were observed in the original literature. A wide blood sampling window was observed, ranging from the acute phase to the convalescence phase. Studies with mean differences in cytokines and chemokines available were selected for the current study. Overall, eleven cytokines and chemokines were identified after pooling the relevant studies. Levels of IL-10, IL-8, sVCAM-1, and IP-10 were positively associated with SD in 6, 3, 2 and 2 studies, respectively ( Table 1 ). Furthermore, subgroup analyses of sampling time showed inconsistent results for IFN-γ. The level was significantly higher in 4 studies (SMD = 0.184, 95% CI: 0.023–0.344, p = 0.025) without heterogeneity ( I 2 = 0.0%, p = 0.480) when sampled early in the disease course (≤7 days of onset). Additionally, most cytokines (except sVCAM-1 and IP-10) had discordant results in the included individual studies.

It is critically important to identify the predictive factors for SD, as the early diagnosis and treatment of SD could reduce mortality and decrease hospitalization durations and costs. The pathogenesis of SD is multifactorial and is not yet well understood. Antibody-dependent enhancement (ADE) due to non-neutralizing cross-reactive antibodies may play a vital role in the mechanism, especially in secondary infection cases [ 38 , 39 ]. Zhang H, et al [ 40 ] conducted a meta-analysis that provided the evidence for the classifications of severe dengue disease according to the new WHO guideline 2009 based on the literature between 2000 and 2012. However, compared with symptoms and signs, virus serotype and plasma biomarkers results were obtained more objectively. In this study, 34 factors including clinical manifestations, virus serotypes, medical history, and plasma biomarkers, were found to be significantly different between DF and SD. Since the critical phase of dengue is usually on days 3–7 of illness [ 1 ], subgroups analysis for sampling time (≤7 days after onset) were performed in this study. Nine factors revealed association with SD within 7 days after onset and could be predictors for SD.

Clinical manifestations

It was further confirmed that SD was associated with secondary infections in the current study, indicating that DF patients with secondary infection had a 2.69 times higher risk of SD than those with only DF. The WS were further confirmed in the current meta-analysis; hepatomegaly, bleeding, pleural effusion, ascites, and persistent vomiting were associated with 4.4, 6.9, 15.8, 24.3, and 5.6 times the risk of SD, respectively, which were consistent with previous study [ 40 ]. Thus, patients with WS should be treated appropriately and in a timely manner to prevent the development of SD. Moreover, lethargy and hypotension had a positive association with SD, which meant that these manifestations are also predictors of SD. However, significant heterogeneity was observed among studies regarding these clinical manifestations. The heterogeneity might be due to inherent differences in populations.

Viral and host factors

This finding also showed a clear difference in the associations of dengue serotypes with the percentage of severe cases. Although DENV-1 accounted for the highest percentage of dengue infections, there was a lower risk of SD on overall, whereas, no statistically significant difference was revealed between patients with DF and those with SD in the Asia and in the Americas, respectively. DENV-2 was a risk factor for SD, even though it had the lowest seroprevalence in the Americas. However, DENV-3 had an inconsistent association with SD, with a negative association in Asia (OR = 0.669, p = 0.021) and no association in the Americas. However, it is premature to draw firm conclusions. The serotypes of DENV were not always reported in the included studies. Only 20.7% of the studies included provided serotype data, and many did not separate primary from secondary dengue infections caused by each dengue serotype. Meanwhile, discordant results have been observed in other studies. DENV-1 is seldom involved in severe cases in Brazil [ 41 ], whereas it was associated with DHF and SD in Singapore [ 42 ] DENV-4 was found to be strongly associated with DSS in Brazil [ 41 ] and individuals infected with DENV-4 had a higher prevalence of respiratory and cutaneous manifestations in South America [ 43 ] Rico-Hesse et al. proposed the term virulent genotypes and revealed an association between two distinct genotypes of DENV-2 and the appearance of DHF in the Americas [ 44 ]. Alternatively, it had been reported that the genetic changes in DENV-3 were associated with the increasing severe dengue epidemics in Sri Lanka [ 45 ]. Thus, the serotype of DENV can contribute to SD differently based on other factors, and the seroprevalence [ 46 ] and changes in the viral genotype [ 47 ] during epidemics might be potential factors affecting the development of SD; this needs further investigation.

In this study, there was no association between age and SD in children, but increasing age results in a higher risk of progressing into SD among adults after pooling 46 studies, agreeing with previous studies[ 15 , 40 , 48 ]. However, consistent conclusions were observed in different populations. For example, pregnant women are 3.4 times more likely to develop SD than non-pregnant women [ 49 ]; as high a proportion as 80% of infants hospitalized with dengue developed DHF/DSS [ 50 ]. Furthermore, individuals with a history of diabetes had a 4.42 times higher risk of SD than those without a history of diabetes. The reason might be that diabetes could result in immune and endothelial dysfunction [ 51 , 52 ].

Plasma biomarkers

Some evidence also indicated that the incidence of low platelet counts, plasma leakage, shock and hemorrhagic manifestations were significantly different in infants compared with older children, and bleeding signs, including rash, petechiae and obvious bleeding were observed approximately 2 times more often in adults than children. [ 53 , 54 ]. An increase in HCT concurrent with a rapid decrease in platelet count was defined as one of the WS by the WHO [ 1 ]. In the current study, thrombocytopenia, an increase in HCT and a decrease in the platelet count were associated with SD, so did in subgroup analysis for sampling time (≤7 days after onset). The leukocyte count is frequently used to evaluate suspected bacterial infections. It had been indicated to be a good marker for differentiating between bacterial versus viral infections in a prospective study [ 55 ]. In the early febrile phase, a decreasing white blood cell count makes the diagnosis of dengue very likely [ 1 ]. However, the counts of the total population and subpopulations of white blood cells were not different between patients with DF and those with SD. As the whole blood counts were dynamic throughout the pathogenic process, a subgroup analysis of sampling time was conducted, but the pooled effect showed no significant difference. Additionally, some studies revealed that atypical lymphocyte count, immature platelet fraction and triple positivity for NS1, Ig M and Ig G would be predictive for SD [ 56 – 58 ], although them couldn’t be included in this meta-analysis. Further studies should be performed to identify in the future.

Liver damage is a well-established characteristic of dengue patients, particularly in severe cases[ 1 , 59 ], and ALT or AST≥1000 IU/L is a diagnostic criterion for SD [ 1 ]; these facts highlight that the liver is involved in the pathogenesis of dengue infection. In this meta-analysis, elevated ALT levels, elevated AST levels and hypoalbuminemia were positively associated with SD. Furthermore, the levels of LD, CK and BUN were increased in patients with SD compared with patients with DF. Unfortunately, there were not enough clinical data available to determine the cutoff values of the indicators. Thus, more clinical studies with defined cutoff values are needed to address these biomarkers in the future.

It is well known that cytokines and chemokines play important roles in the pathogeny of dengue infection but inconsistent association between DF and SD was observed in the literature because of the heterogeneity [ 13 , 60 , 61 ]. In the current study, the pooled results of IL-8, IL-10, sVCAM-1 and IP10 were positively associated with severity. However, these findings should be interpreted cautiously because conflicting results were observed among studies. One of the major hindrances is the inconsistent results in the literature caused by heterogeneity. Large variations were observed among studies with various sampling times. Regarding IFN-γ, a significant positive association with SD was revealed in the acute phase after removing studies with different sampling times. Additionally, the level of IFN-γ was significantly higher in patients with SD than in those with DF, but opposing results were observed during the defervescence and convalescent stages [ 62 , 63 ]. As the levels of cytokines/chemokines are dynamic during the process of infection, they display differences in the timing of their peak responses [ 64 , 65 ]. Thus, different factors should be measured during the appropriate phases. Furthermore, there were significant differences in the levels of IL-8 and VEGFR2 between serum and plasma samples [ 64 , 65 ]. These results merit further investigation with better-defined methodologies, full descriptions of the results and transparency of the sampling time and serotypes. These data would be helpful in overcoming the weaknesses of the currently available publications.

Limitations

There were some limitations in our study. First, there were some markers, such as viremia, nutritional status, and serum levels of C-reactive protein, total cholesterol, and triglycerides, were not analyzed in this study because of insufficient data. Second, the significant heterogeneity was not fully explained by the six covariables investigated. It could have been driven by numerous other factors that were not addressed in this meta-analysis, which shows the need of controls for these factors in order to further confirm the findings in future research. Third, some reasons might conduct biases, such as most reports were retrospective, non-English studies were excluded, samples were processed into plasma or serum and different WHO classification methods were used to assign the disease’s severity.

A list of 34 potential severity markers was investigated in this study; and nine factors, secondary infection, retro orbital pain, hepatomegaly, bleeding, pleural effusion, ascites, increased HCT, and AST, decreased PLT revealed positive relation with SD in early stage (≤7 days after onset). Hence, this study provides information regarding markers that can be used to identify SD in the early stage, facilitating prompt disease management. However, heterogeneity was observed among current studies, which suggests that increased standardization is needed in future clinical reports.

Supporting information

S1 checklist. prisma checklist..

https://doi.org/10.1371/journal.pone.0267186.s001

S1 Table. NOS scoring system for quality assessment.

https://doi.org/10.1371/journal.pone.0267186.s002

S2 Table. The scores of studies included in this meta-analysis according to NOS.

https://doi.org/10.1371/journal.pone.0267186.s003

S3 Table. Characteristics of the studies included in this meta-analysis.

https://doi.org/10.1371/journal.pone.0267186.s004

S4 Table. Sensitivity and sub-analysis on the summary effect and heterogeneity.

https://doi.org/10.1371/journal.pone.0267186.s005

S5 Table. Factors identified by subgroup analysis for sampling time within 7 days after onset of illness.

https://doi.org/10.1371/journal.pone.0267186.s006

S6 Table. Factors not associated with sever dengue disease.

https://doi.org/10.1371/journal.pone.0267186.s007

https://doi.org/10.1371/journal.pone.0267186.s008

Acknowledgments

The authors would like to thank Dr. Peihuang Wu for assistance during the preparation of this manuscript.

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• Published: 27 November 2023

Viral infections

Severe dengue progression beyond enhancement

• Camila D. Odio   ORCID: orcid.org/0000-0002-1730-4380 1 ,
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The immune response to dengue virus infection is a well-coordinated balancing act. New research shows that an imbalanced response — driven partially by the productive infection of antigen-presenting cells — is associated with progression to severe disease.

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What Is Dengue?

• 1 Division of Infectious Disease, Department of Internal Medicine, Michigan Medicine, Ann Arbor
• 2 Deputy Editor, JAMA
• Viewpoint Opportunities for Improved Dengue Control in the US Territories Alfonso C. Hernandez-Romieu, MD, MPH; Laura E. Adams, DVM, MPH; Gabriela Paz-Bailey, MD, MSc, PhD JAMA
• Medical News in Brief Dengue Cases Surge in Latin America and Caribbean Emily Harris JAMA
• Research Letter Neurological or Psychiatric Disorders After Dengue Fever Hong-Ci Lin, MD; Hsueh-Pu Chou, MD; Yung-Chih Chiang, MD; Renin Chang, MD, PhD; Yao-Shen Chen, MD; Yu-Chung Juan, MD JAMA Network Open

Dengue is a viral infection spread to humans by mosquitoes of the Aedes genus.

Signs and Symptoms of Dengue

Most people with dengue have no symptoms. Approximately one-quarter of people have mild illness that develops 4 to 7 days after being bitten by an infected mosquito. The most common symptom of dengue is fever, which may be accompanied by pain in the eyes, bones, joints, and muscles, as well as nausea, vomiting, and rash.

Approximately 5% of patients with dengue develop severe symptoms such as persistent vomiting, severe abdominal pain, gastrointestinal or vaginal bleeding, shortness of breath, low blood pressure, and lethargy. People at highest risk of severe dengue include pregnant individuals and those who have had prior infection with a different dengue virus.

Who Is Affected by Dengue and How Common Is It?

There are 4 different dengue viruses, so people can get dengue more than once in their lifetime. Dengue affects people in Central and South America, Africa, the Middle East, Southeast Asia, and the Pacific Islands. Among US territories and freely associated states, dengue is found in Puerto Rico, the US Virgin Islands, Micronesia, the Marshall Islands, and Palau.

Each year, up to 400 million people worldwide are infected with dengue, and 4 billion people live in areas with a risk of dengue. In 2023, the Centers for Disease Control and Prevention (CDC) reported 1709 travel-associated cases of dengue and 1206 cases of dengue that were acquired in the US.

How Is Dengue Diagnosed and Treated?

Testing for dengue is performed in specialized laboratories. During the first 5 days of illness, dengue can be diagnosed by detecting the virus in the blood using a polymerase chain reaction (PCR) test. After the fourth day of infection, testing for antibodies in the blood can be used to detect infection with dengue.

There is no effective antiviral medication for dengue. Individuals with mild illness should drink plenty of fluids to prevent dehydration. Fever can be treated with acetaminophen (paracetamol). Patients with severe dengue should be hospitalized for close monitoring and supportive treatment.

How to Prevent Dengue

People living in or traveling to areas with dengue should avoid mosquito bites by using recommended insect repellents (those with DEET or other Environmental Protection Agency–registered insect repellents with an active ingredient) and by wearing loose-fitting, long-sleeve shirts and pants treated with permethrin. Screens on windows and doors and use of air conditioning, when available, instead of opening windows, can decrease the risk of contact with mosquitoes. Avoiding and eliminating sources of standing water (such as flowerpot saucers, buckets, and birdbaths) is also important in controlling the mosquito population.

In 2021, the CDC’s Advisory Committee on Immunization Practices (ACIP) recommended dengue vaccination for children aged 9 to 16 years who live in American Samoa, Puerto Rico, or the US Virgin Islands and have evidence of prior dengue infection. Vaccination is not recommended for children who have never been infected with dengue or for travelers to an area where dengue is common.

For More Information

Centers for Disease Control and Prevention www.cdc.gov/dengue/index.html

Published Online: August 15, 2024. doi:10.1001/jama.2024.8573

Conflict of Interest Disclosures: None reported.

Source: Infectious Diseases Society of America. https://www.idsociety.org/science-speaks-blog/2024/dengue-a-growing-health-threat-internationally

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Correlation of Vitamin B12 Levels with Clinical Manifestations, Thrombocytopenia, Hospital Stay, and Platelet Recovery in Dengue Patients

• Original Paper
• Published: 17 August 2024
• Volume 6 , article number  88 , ( 2024 )

Cite this article

• Poonam Gupta   ORCID: orcid.org/0009-0007-8473-9492 1 ,
• Ajeet Kumar Chaurasia   ORCID: orcid.org/0009-0008-3887-9731 1 ,
• Apurwa Pratap Mall 1 ,
• Manoj Kumar Mathur 1 &
• Ashish Kumar Gautam 1  

Dengue is a prevalent viral infection with diverse clinical manifestations. This study aims to examine the impact of low vitamin B12 levels in dengue patients, to explore the prevalence of serum vitamin B12 deficiency in dengue patients and its correlation with clinical manifestations, severity of thrombocytopenia, hospital stay, units of platelets transfused, and patient outcomes. This was conducted as a prospective cross-sectional study at MLNMC, Prayagraj, on 250 dengue patients. Among them, 189 tested positive for dengue serology. After excluding 5 patients, our detailed study focused on 184 subjects with serum vitamin B12 levels ranging from < 83 to > 2000 ng/ml. The prevalence of vitamin B12 deficiency among dengue cases was 37.0%. Notably, cases with vitamin B12 levels < 200 ng/ml were more likely to exhibit melena (20.6% vs. 6.9%) and epistaxis (10.3% vs. 0.9%) and conversely lesser incidence of joint pains (69.1% vs. 87.9%). MCV levels were significantly higher in cases with B12 levels < 200 ng/ml (96.78 ± 9.76 vs. 84.13 ± 7.14 femtolitres/cell). Platelet counts at presentation were significantly higher in cases with vitamin B12 ≥ 200 ng/ml (0.74 ± 0.43 vs. 0.56 ± 0.32 lacs/µl). Furthermore, cases with vitamin B12 < 200 ng/ml experienced higher rates of indoor admissions (92.6% vs. 75.0%) and longer hospital stays (4.38 ± 2.23 vs. 3.52 ± 2.60 days) and required more platelet transfusion units (4.63 ± 2.60 vs. 3.11 ± 1.99 days). Vitamin B12 levels play a crucial role in the clinical manifestations of dengue and are associated with increased severity of thrombocytopenia, prolonged hospital stays, and heightened requirements for platelet transfusion.

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Gupta, P., Chaurasia, A.K., Mall, A.P. et al. Correlation of Vitamin B12 Levels with Clinical Manifestations, Thrombocytopenia, Hospital Stay, and Platelet Recovery in Dengue Patients. SN Compr. Clin. Med. 6 , 88 (2024). https://doi.org/10.1007/s42399-024-01717-y

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Dynamics and Efficacy: A Comprehensive Evaluation of the Advanced Dengue Fever Surveillance and Early Warning System in Ningbo City, 2023

Affiliations.

• 1 Department of Infectious Disease Control and Prevention, Ningbo Prefectural Center for Disease Control and Prevention, Ningbo, Zhejiang Province, People's Republic of China.
• 2 State Key Laboratory of Vaccines for Infectious Diseases, Xiang' an Biomedicine Laboratory, School of Public Health, Xiamen University, Xiamen, Fujian Province, People's Republic of China.
• PMID: 39140008
• PMCID: PMC11321351
• DOI: 10.2147/RMHP.S470237

Objective: To conduct a comprehensive evaluation of the Dengue Fever Surveillance and Early Warning System deployed in Ningbo City during 2023, focusing on its capacity for timely identification and reporting of dengue fever cases, particularly imported cases from endemic regions.

Methods: A detailed data of patient clinical features and blood profile trends was collected from clinical records and surveillance reports, focusing on the rapid diagnostic processes and surveillance rigor. This study assessed the effectiveness of the system in identifying and reporting dengue cases and identified the limitations of the existing framework through a basic statistical approach.

Results: The system demonstrated timely identification and reporting of dengue fever cases, with a particular emphasis on imported cases. However, several limitations were identified, including the need for more precise monitoring criteria and improved coordination with medical entities.

Conclusion: The study underscores the critical role of public health bodies in managing disease outbreaks and advocates for enhanced methodologies to refine epidemic control efforts. The findings contribute to the advancement of early warning mechanisms and the improvement of proactive infectious disease monitoring in metropolitan environments, providing valuable insights for fortifying the Dengue Fever Surveillance and Early Warning System in Ningbo City.

Keywords: Dengue fever; Early-warning; Imported; Surveillance.

© 2024 Zhang et al.

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Conflict of interest statement

The authors declare that they have no competing interests in this work.

The Temporal and Regional Distribution…

The Temporal and Regional Distribution for Dengue Infections in Ningbo, 2023.

The flow chart of dengue…

The flow chart of dengue fever prevention and control in Ningbo.

Reporting times of Dengue infections…

Reporting times of Dengue infections for the new system lagging those for traditional…

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Dengue infection in India: A systematic review and meta-analysis

Parasuraman ganeshkumar.

1 Department of Epidemiology, National Institute of Epidemiology, Chennai, Tamil Nadu, India

Manoj V. Murhekar

Veeraraghavadoss poornima.

2 School of Public Health, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India

Velusamy Saravanakumar

Krishnendu sukumaran, anandan anandaselvasankar.

3 Campbell Collaboration, New Delhi, India

Sanjay M. Mehendale

4 Division of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India

Associated Data

All relevant data are within the paper and its Supporting Information files.

Introduction

Dengue is the most extensively spread mosquito-borne disease; endemic in more than 100 countries. Information about dengue disease burden, its prevalence, incidence and geographic distribution is critical in planning appropriate control measures against dengue fever. We conducted a systematic review and meta-analysis of dengue fever in India

We searched for studies published until 2017 reporting the incidence, the prevalence or case fatality of dengue in India. Our primary outcomes were (a) prevalence of laboratory confirmed dengue infection among clinically suspected patients, (b) seroprevalence in the general population and (c) case fatality ratio among laboratory confirmed dengue patients. We used binomial–normal mixed effects regression model to estimate the pooled proportion of dengue infections. Forest plots were used to display pooled estimates. The metafor package of R software was used to conduct meta-analysis.

Of the 2285 identified articles on dengue, we included 233 in the analysis wherein 180 reported prevalence of laboratory confirmed dengue infection, seven reported seroprevalence as evidenced by IgG or neutralizing antibodies against dengue and 77 reported case fatality. The overall estimate of the prevalence of laboratory confirmed dengue infection among clinically suspected patients was 38.3% (95% CI: 34.8%–41.8%). The pooled estimate of dengue seroprevalence in the general population and CFR among laboratory confirmed patients was 56.9% (95% CI: 37.5–74.4) and 2.6% (95% CI: 2–3.4) respectively. There was significant heterogeneity in reported outcomes (p-values<0.001).

Conclusions

Identified gaps in the understanding of dengue epidemiology in India emphasize the need to initiate community-based cohort studies representing different geographic regions to generate reliable estimates of age-specific incidence of dengue and studies to generate dengue seroprevalence data in the country.

Author summary

Dengue fever, an extensively spread mosquito-borne disease, is endemic in more than 100 countries. Information about dengue disease burden, its prevalence and incidence and geographic distribution is necessary to guide in planning appropriate control measures including the dengue vaccine that has recently been licensed in a few countries. We performed a systematic review and meta-analysis of published studies in India on dengue. The overall estimate of the prevalence of laboratory confirmed dengue infection based on testing of more than 200,000 clinically suspected patients from 180 Indian studies was 38.3%. The pooled estimate of dengue seroprevalence in the general population and CFR among laboratory confirmed dengue patients was 56.9% and 2.6% respectively. There were no community-based studies reporting incidence of dengue. Our review also identified certain knowledge gaps about dengue epidemiology in the country. Identified gaps in the understanding of dengue epidemiology in India emphasize the need to initiate community-based cohort studies representing different geographic regions to generate reliable estimates of age-specific incidence of dengue and studies to generate dengue seroprevalence data in the country.

Dengue is the most extensively spread mosquito-borne disease, transmitted by infected mosquitoes of Aedes species. Dengue infection in humans results from four dengue virus serotypes (DEN-1, DEN-2, DEN-3, and DEN-4) of Flavivirus genus. As per the WHO 1997 classification, symptomatic dengue virus infection has been classified into dengue fever (DF), dengue haemorrhagic fever (DHF) and dengue shock syndrome (DSS). The revised WHO classification of 2009 categorizes dengue patients according to different levels of severity as dengue without warning signs, dengue with warning signs (abdominal pain, persistent vomiting, fluid accumulation, mucosal bleeding, lethargy, liver enlargement, increasing haematocrit with decreasing platelets) and severe dengue [ 1 , 2 , 3 ]. Dengue fever is endemic in more than 100 countries with most cases reported from the Americas, South-East Asia and Western Pacific regions of WHO [ 1 ]. In India, dengue is endemic in almost all states and is the leading cause of hospitalization. Dengue fever had a predominant urban distribution a few decades earlier, but is now also reported from peri-urban as well as rural areas [ 4 , 5 ]. Surveillance for dengue fever in India is conducted through a network of more than 600 sentinel hospitals under the National Vector Borne Disease Control Program (NVBDCP) [ 6 ], Integrated Disease Surveillance Program (IDSP) [ 7 ] and a network of 52 Virus Research and Diagnostic Laboratories (VRDL) established by Department of Health Research [ 8 ]. In 2010, an estimated 33 million cases had occurred in the country [ 9 ]. During 2016, the NVBDCP reported more than 100,000 laboratory confirmed cases of dengue [ 6 ]. It is therefore possible that dengue disease burden is grossly under-estimated in India.

High dengue disease burden and frequent outbreaks result in a serious drain on country’s economy and stress on the health systems. In India, case detection, case management, and vector control are the main strategies for prevention and control of dengue virus transmission [ 6 ]. A new dengue vaccine is now available and several vaccines are in the process of development [ 10 , 11 , 12 ]. Information about dengue disease burden, its prevalence, incidence and geographic distribution is necessary in decisions on appropriate utilization of existing and emerging prevention and control strategies. With this background, we conducted a systematic review and meta-analysis to estimate the disease burden of dengue fever in India. We also reviewed serotype distribution of dengue viruses in circulation, and estimated case fatality ratios as well as proportion of secondary infections.

Search strategy and selection criteria

This systematic review is registered in PROSPERO (Reg. No. CRD 42017065625). We searched Medline (PubMed), Cochrane Central, WHOLIS, Scopus, Science Direct, Ovid, Google Scholar, POPLINE, Cost-Effectiveness Analysis (CEA) Registry and Paediatric Economic Database Evaluation (PEDE) databases for articles published up to 2017. The main search terms included incidence, prevalence, number of reported cases, mortality, disease burden, cost of illness, or economic burden of dengue in India. The complete search strategy is described in S1 Appendix . Back referencing of included studies in bibliography was also done to identify additional studies.

Review approach

The search results were initially imported to Zotero software (Version 4.0.29.5) and duplicate records were removed. During title screening, we examined relevant studies from various databases. Our inclusion criterion was studies reporting dengue infection in India, not restricted to setting, design, purpose and population. Titles thus selected were subjected to abstract screening. Studies were considered eligible for further examination in full text if their abstracts reported incidence, prevalence, number of reported cases, mortality or the burden of dengue fever anywhere in India. Studies reporting complications of dengue, serotype details of dengue virus as well as seroprevalence of dengue were also included. Using a pre-designed data extraction form, two reviewers extracted details from selected studies independently. The data, which differed between the reviewers, were resolved by consensus. Information about the year of publication, study setting (hospital/laboratory based, or community-based), study location, study period, laboratory investigations, number of suspected patients tested and positives, age distribution of cases, and details of dengue serotypes were abstracted ( S1 Dataset ).

The primary outcome measures of interest were (a) prevalence (proportion) of laboratory confirmed dengue infection among clinically suspected patients in hospital/laboratory based or community-based studies, (b) seroprevalence of dengue in the general population and (c) case fatality ratio among laboratory confirmed dengue patients. The diagnosis of acute dengue infection among the clinically suspected patients was based on any of the following laboratory criteria: (a) detection of non-structural protein-1 (NS1) antigen, (b) Immunoglobulin M (IgM) antibodies against dengue virus (c) haemagglutination inhibition (HI) antibodies against dengue virus, (d) Real-time polymerase chain reaction (RT-PCR) positivity or (e) virus isolation. Seroprevalence of dengue was based on detection of IgG or neutralizing antibodies against dengue virus. Studies providing prevalence (proportion) of laboratory confirmed dengue infection among clinically suspected patients were classified into (a) hospital/laboratory-based surveillance studies and (b) outbreak investigations or hospital/laboratory-based surveillance studies when the outbreak was ongoing in the area, as mentioned in the original research paper. Studies regarding outbreak investigations considered an increase in number of reported cases of febrile illness in a geographical area, as the criteria for defining an outbreak. The outbreak investigations included one or more of the following activities: active search for case-patients in the community, calculation of attack rates for suspected case-patients, confirmation of aetiology and entomological investigations. For the case fatality ratio, the numerator included reported number of deaths due to dengue and denominator as laboratory confirmed dengue patients.

Our secondary outcomes of interest were the following: (a) proportion of primary and secondary infections among the laboratory confirmed dengue patients. This classification was made based on the information about dengue serology provided in the paper. Primary dengue infection was defined as acute infection, as indicated by qualitative detection of NS1 antigen, and/or IgM or HI antibodies or RT-PCR positivity and absence of IgG antibodies against dengue virus. A case of acute infection as defined above, in presence of IgG antibodies, was considered as secondary dengue infection [ 2 , 13 , 14 ]. Some of the studies used the ratio of IgG to IgM antibodies as the criteria for differentiating primary and secondary infections [ 14 ]; (b) distribution of predominant and co-circulating dengue virus serotypes; (c) proportion of severe dengue infections based on WHO 1997 or WHO 2009 criteria [ 1 , 2 ]. The category of severe dengue infection included patients with DHF and DSS as per the WHO 1997 classification as well as severe dengue infections classified as per the WHO 2009 classification and (d) cost of illness, which included reported direct and indirect costs associated with dengue hospitalization.

Risk of bias

The risk of bias was assessed using a modified Joanna Briggs Institute (JBI) appraisal checklist for studies reporting prevalence data [ 15 ] and essential items listed in the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist [ 16 ]. The criteria for assessing bias primarily included methods for selecting participants, methods for laboratory testing, and outcome variables (Supplementary file S2 Appendix ).

Statistical analysis

We conducted quantitative synthesis to derive meta-estimates of primary and secondary outcomes (severity of disease and primary/ secondary infections) and qualitative synthesis to describe the serotype distribution and economic burden due to dengue. We followed Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines [ 17 ]. For each study, primary outcomes (prevalence of acute infection, seroprevalence and CFR) were summarized as proportion and their 95% confidence intervals were computed. We used logit and inverse logit transformations for variance stabilization of proportions [ 18 ]. Binomial–Normal mixed effects regression model was used to estimate the pooled proportion of dengue infections. Forest plots were used to display pooled estimates. Heterogeneity was tested using likelihood ratio test. Funnel plots with logit prevalence on x-axis and standard errors on y-axis and Egger’s test were used to evaluate publication bias. Independent variables potentially associated with the prevalence of laboratory confirmed dengue were included as fixed-effects in univariate and multivariate binomial meta-regression models. P <0.05 was considered statistically significant. Sensitivity analysis was carried out by leaving out one study at a time in the order of publication to check for consistency of pooled estimates. Analyses were performed in the R statistical programming language using the ‘metafor’ package [ 19 , 20 ].

Characteristics of included studies

The search strategy initially identified 2,285 articles from different databases. After removal of duplicates, 1,259 articles were considered for title and abstract screening. Seven hundred and forty-six articles were excluded for reasons provided in Fig 1 . Thus, 513 articles were found to be eligible for full-text review. After the review of full-text articles, 233 studies were included for the analysis [ 21 – 253 ]. The details of the studies included in the review are provided in the PRISMA flowchart ( Fig 1 ). None of the studies reported incidence of dengue fever.

Primary outcomes

Prevalence (proportion) of laboratory confirmed dengue fever.

Of the 233 studies included in the analysis, 180 provided information about proportion of laboratory confirmed dengue cases among clinically suspected patients [ 21 – 200 ]. This included 154 studies conducted in hospital or laboratory setting [ 21 – 174 ] and 26 studies reporting outbreak investigations [ 175 – 200 ]. Of the 154 studies conducted in hospital/ laboratory setting, 40 were conducted when an outbreak was ongoing in the area [ 135 – 74 ]. The diagnosis of acute dengue infection was based on a single assay in 86 studies (IgM antibodies = 68, RT-PCR = 11, HI antibodies = 4, virus isolation = 2, detection of NS1 antigen = 1) and more than one assay in 95 studies.

Case definitions used : Of the 154 studies conducted in hospital settings, WHO or NVBDCP case definitions were used by 39 and 2 studies respectively. The remaining studies used case definitions such as acute febrile illness/acute undifferentiated illness (n = 20), and clinically suspected dengue fever (n = 93). Similarly, of the 26 reported outbreaks, investigators used WHO or NVBDCP case definitions in 7 and 2 settings respectively, whereas acute febrile illness and clinically suspected dengue fever case definitions were used in 5 and 12 settings respectively.

Place and time distribution of studies : Of the 154 studies conducted in hospital setting, 75, 41, 27 and 7 were from north, south, east and western Indian states respectively, whereas 3 studies were from north-eastern states. One study reported data from VRDL network, covering multiple regions in India [ 65 ]. Of the 26 outbreaks, most (10, 38.5%) were reported from Southern states, followed by 9 (34.6%) in the north, 4 (15.4%) in the east, and 3 (11.5%) in the north-eastern Indian states. Most (65, 42.2%) studies conducted in hospital settings were between 2011–2017, while 48 (31.2%) were conducted between 2006–2010 and 41 (26.6%) were conducted before 2006. Eighteen (69.2%) of the 26 outbreaks were reported after 2000.

Of the 180 studies which reported proportion of dengue cases, 74 studies (30%) provided the details of laboratory confirmed cases by month with most (n = 60, 81%) reporting higher dengue positivity between August and November months.

Age distribution of dengue cases : The age distribution of laboratory confirmed dengue patients was available from 52 out of 180 studies. The pooled median age of laboratory confirmed dengue cases in these studies was 22 years ( Fig 2 ). Fifteen (28.8%) studies reported the median age of dengue cases below 15 years.

Estimates of prevalence (proportion) : The overall estimate of the prevalence of laboratory confirmed dengue infection in the random effects model based on testing of 213,285 clinically suspected patients from 180 studies was 38.3% (95% CI: 34.8%–41.8%) ( Fig 3 ). There was a significant heterogeneity in the prevalence reported by the 180 studies (LRT p<0.001). The prevalence of laboratory confirmed dengue infection was higher in studies reporting outbreaks or hospital-based surveillance studies during outbreaks (47.3%, 95% CI: 40.9–53.8) as compared to hospital-based surveillance studies (33.6%, 95% CI: 29.9–37.5) ( S1A and S1B Fig ). The attack rates of suspected dengue case patients were available in 8 out of the 26 outbreak investigations reports. The attack rates ranged between 1.9% and 19.5%.

Error bars indicate 95% confidence intervals. Diamonds show the pooled estimates with 95% confidence intervals based on random effects (RE) model.

In the univariate mixed effect meta-regression model, odds of laboratory confirmation were higher in case of outbreaks or hospital-based studies conducted during outbreaks (OR = 1.8, 95% CI: 1.3–2.4). Studies which used WHO/ NVBDCP case definitions for enrolment of patients also had higher odds of detecting laboratory confirmed dengue compared to studies which used acute febrile illness/ clinically suspected dengue cases as case definitions. Compared to studies conducted before 2006–10, studies conducted between 2011 and 2017 had higher odds of identifying laboratory confirmed patients (OR = 1.33, 95% CI: 0.93–1.9). The odds of laboratory confirmation did not differ by region ( Table 1 ). In the multivariate meta-regression model constructed by including all covariates, case definition (WHO/NVBDCP), type of study (hospital-based surveillance studies conducted during outbreaks or outbreaks) and period of study (prior to 2005 and 2011–2017) were associated with higher odds of dengue cases being laboratory confirmed.

Ref—Reference category; CI—Confidence interval; P*–P value.

Seroprevalence of dengue among healthy individuals

We included 7 studies reporting seroprevalence of dengue based on detection of IgG (n = 5), neutralizing antibodies (n = 1) or HI antibodies (n = 1) against dengue in the analysis [ 201 – 207 ]. These studies, conducted in 12 Indian states [Andaman and Nicobar islands (n = 1), Andhra Pradesh (n = 2), Tamil Nadu (n = 3), Delhi (n = 4), West Bengal (n = 1), and Maharashtra (n = 1)], surveyed 6,551 individuals. The study population surveyed in these studies included healthy children (n = 2), general population (n = 3), blood donors (n = 1) and neighbourhood contacts of dengue confirmed cases (n = 1). The overall seroprevalence of dengue fever based on these studies was 56.9% (95% CI: 37.5–74.4) ( Fig 4 ). The age-specific prevalence of IgG antibodies was available in three studies [ 201 , 204 , 206 ]. There was a significant heterogeneity in the seroprevalence reported by the seven studies (LRT p<0.001). In the 3 studies which provided age specific seroprevalence, by the age of 9 years, 47.6% -73.4% children were reported to have developed IgG or neutralizing antibodies against dengue ( Table 2 ).

Figure in square bracket indicate reference

Case fatality ratios (CFR)

Seventy-seven studies provided information about case fatality ratios; most of them (n = 72, 93.5%) were conducted after 2000. The reported CFRs in these studies ranged from 0% to 25%. There was a significant heterogeneity in the CFRs reported by the 74 studies (LRT p<0.001). Twenty (25.9%) studies reported CFR of 2% or more. Three studies [ 30 , 239 , 195 ] which affected overall meta-estimates due to small denominator and hence were excluded from analysis. The pooled estimate of CFR was 2.6% (95% CI: 2.0–3.4) ( Fig 5 ).

Secondary outcomes

Primary and secondary dengue infection.

A total of 49 studies provided data which enabled classification of laboratory confirmed dengue into primary and secondary dengue infections. The number of patients with acute dengue infections in these studies ranged between 13 and 1752. Only two studies estimated the proportion of secondary infection based on IgG to IgM ratio [ 174 , 237 ]. The prevalence of secondary dengue infection was <10% in 6 studies, 10–25% in 9 studies, 26–50% in 12 studies, 51–75% in 17 studies and >75% in 5 studies. The overall proportion of secondary dengue infection among laboratory confirmed patients was 42.9% (95%CI: 33.7–52.6) ( Fig 6 ).

Proportion of severe cases

Information about severity of dengue was available in 49 studies. Most studies (n = 46, 93.9%) used the WHO 1997 classification while 3 studies used the WHO 2009 classification for dengue severity. The reported proportion of severe dengue cases among laboratory confirmed patients ranged between 1.4% and 97.4%. The overall proportion of severe dengue among laboratory confirmed studies in the random effects model was 28.9% (95% CI: 22.2–36.6) ( Fig 7 ).

Serotypes of dengue virus

Information about dengue serotypes was available in 51 studies. These studies were conducted in 19 Indian states; with a regional distribution of north (n = 28), south (n = 13), east (n = 4), northeast (n = 4), and west (n = 2). Thirty-eight (75%) of the 51 studies reported circulation of more than one serotype. The predominant serotypes reported in these studies were DEN-2 and DEN-1 in the northern region, DEN-2 and DEN-3 in the southern region, and DEN-1 and DEN-2 in the eastern and the western regions. In the four studies reported from the north-eastern region, the predominant serotypes was DEN-3 followed by DEN-1 and DEN-2 serotypes ( Table 3 ).

Key for coloured cell: Blue—One circulating serotype, Yellow—two co-circulating serotypes, Green—three co- circulating serotypes, Orange—four co- circulating serotypes. Numbers mentioned in the cell indicate predominant serotypes, in descending order.

Economic burden

Direct and Indirect cost analysis : An estimate of direct and indirect costs was reported in three studies. The average direct cost per case of dengue ranged between USD 23.5 and USD 161 and the indirect cost was around USD 25 whereas the average cost of hospitalization ranged between USD 186 and USD 432.2 [range 249 -252]. The cost of dengue treatment in the private health sector was two to four times higher than that in the public sector hospitals [ 249 , 253 ].

Economic impact of dengue on National Economy : Three macro-level studies addressed the economic impact of dengue faced by India [ 250 , 251 , 253 ]. It was estimated that the average total economic burden due to dengue in India was USD 27.4 million [ 251 ]. Another study estimated that the total direct medical cost of dengue in 2012 was USD 548 million [ 253 ]. The overall economic burden of dengue would be even higher if the cost borne by individual patients is combined with the society level cost of dengue prevention, vector control, disease control and its management, dengue surveillance as well as the cost of research and development [ 250 , 251 , 253 ].

Publication bias and sensitivity analysis

Funnel plots and Egger’s test revealed no publication bias in the estimates of dengue prevalence in hospital-based surveillance studies, hospital-based surveillance studies during outbreaks and outbreak investigations. CFR estimates, however, showed a significant publication bias, and studies with high prevalence were more likely to be published. In the sensitivity analysis, the estimated pooled proportions were found to be consistent for all study outcomes. ( S3 Appendix )

The present study has estimated the burden of dengue fever based on published literature from India spanning over five decades. Most of the published literature included in the analysis were hospital/ laboratory-based surveillance studies or reports of dengue outbreak investigations. Additionally the published data from VRDL network has been included in the analysis [ 65 , 96 ]. The data from the other two nationally representative surveillance platforms could not be used for the analysis because surveillance data from NVBDCP only reports the number of laboratory confirmed dengue cases, while the IDSP data is not available in the public domain.

There was no community-based epidemiological study reporting the incidence of dengue fever. Our analysis revealed that among the clinically suspected dengue fever patients, the estimated prevalence of laboratory-confirmed dengue infection was 38%. The burden of dengue was also variable in studies conducted in different settings. Our findings indicated that most of the laboratory confirmed dengue cases in India occurred in young adults. Dengue positivity was higher between the months of August and November, corresponding to monsoon and post-monsoon season in most states in India.

In the meta-regression, studies that had used WHO/NVBDCP case definitions and the hospital based studies conducted during outbreaks or studies reporting outbreaks were more likely to have laboratory confirmation of dengue. The odds of laboratory confirmation were also higher among studies conducted during the period of 2011 to 2017, as compared to studies conducted prior to the year 2000.

Information about seroprevalence of dengue in the general population is a useful indicator for measuring endemicity of dengue fever. The dengue vaccine (CYD-TDV) manufactured by Sanofi Pasteur has been introduced in two sub-national programs in Philippines and Brazil [ 254 ] and it has been suggested that vaccine acts by boosting the naturally acquired immunity [ 255 ]. WHO SAGE conditionally recommends the use of this vaccine for areas in which dengue is highly endemic as defined by seroprevalence in the population targeted for vaccination [ 12 , 256 ]. The results of the two vaccine trials and mathematical modelling suggest that optimal benefits of vaccination if seroprevalence in the age group targeted for vaccination was in the range of ≥70% [ 255 , 256 ]. In 2018, WHO revised the recommendation from population sero-prevalence criteria to pre-vaccination screening strategy [ 257 ]. The pooled estimate based on the seven studies conducted in India indicated a dengue seroprevalence of 57%. However, this estimated seroprevalence is not representative of the country, as these studies were conducted only in 12 Indian states, and some had used a convenience sampling method [ 201 ].

The computed pooled estimate of case fatality due to dengue in India was 2.6% with a high variability in the reported CFRs. The CFR estimated in our study was higher than the estimate of 1.14% (95% CI: 0.82–1.58) reported in the meta-analysis of 77 studies conducted globally; in the 69 studies which adopted WHO 1997 dengue case classification, the pooled CFR was 1.1% (0.8–1.6) while the pooled CFR for 8 studies which used the WHO 2009 case definition, the pooled CFR was 1.6% (95% CI: 0.64–4.0) [ 258 ]. Higher CFR observed in our analysis could be due to smaller sample sizes as 14 of the 35 studies that reported CFR of 2.6 or higher had a sample size of 100 or less, while in the remaining 21 studies the denominator ranging between 101 and 400. Also, we only considered laboratory confirmed dengue cases in the denominator for the calculation of CFR. As per the NVBDCP surveillance data, a total of 683,545 dengue cases and 2,576 deaths were reported in India during 2009–2017 giving a CFR of 0.38% [ 6 ]. The lower CFR estimates from NVBDCP data could probably be on account of under-reporting of deaths due to dengue, or inclusion of higher number of mild cases in the denominator [ 259 ]. As per the NVBDCP surveillance data, an average of 28,227 dengue cases and 154 deaths were reported annually during 2009–2012. The number of dengue cases reported increased thereafter, with an average of 100,690 cases per year during 2013–2017. However, the reported number of deaths did not increase proportionately. The information about severity of dengue cases is not available from NVBDCP surveillance data.

The published studies from India indicated circulation of all the four-dengue serotypes, with DEN-2 and DEN-3 being the more commonly reported serotypes. Two third of the studies reported circulation of more than one serotype. Co-circulation of multiple serotypes was particularly evident from the published studies in Delhi. More than two third (16/19) studies from Delhi reported circulation of more than one serotype; and most of the studies conducted in the last 10 years identified co-circulation of more than one serotype [ Table 3 ]. Our review also revealed that more than two-fifth of the laboratory confirmed infections were secondary dengue infections and nearly one-fourth of the cases were severe in nature. Circulation of numerous dengue serotypes is known to increase the probability of secondary infection, leading to a higher risk of severe dengue disease [ 260 ].

Our systematic review has certain limitations. First, our study included only peer-reviewed literature from selected databases and we excluded grey literature which may have provided additional data. Second, most of the studies on disease burden were hospital-based, with no community-based studies estimating incidence. Hospital-based studies do not provide any information about the community level transmission as hospitalization is a function of health-seeking behaviour of the population. In absence of the information about health seeking behaviour provided in these studies, we estimated the prevalence of dengue using number of patients tested in the hospitals as the denominator. Third, the hospital-based studies used varying case definitions and laboratory tests to confirm dengue infection. Fourth, information about the type of health facility (public or private), or residential status of patients (urban or rural), and age was not uniformly reported and hence we did not estimate the dengue prevalence by these variables.

In conclusion, the findings of our systematic review indicate that dengue continues to be an important public health problem in India, as evidenced by the high proportion of dengue positivity, severity and case fatality as well as co-circulation of multiple dengue virus serotypes. Our review also identified certain research gaps in the understanding on dengue epidemiology in the country. There is a need to initiate well planned community-based cohort studies representing different geographic regions of the country in order to generate reliable estimates of age-specific incidence of dengue fever in India. As such studies are cost intensive, a national level survey to estimate age-stratified dengue seroprevalence rates could be an alternative. Such estimates could be used to derive the relative proportions of primary and secondary infections using mathematical models [ 261 ]. Well planned studies in different geographic settings are also needed to generate reliable data about economic burden from India. Although the existing dengue surveillance platforms of NVBDCP, IDSP and VRDL are generating data about dengue disease burden, these systems could be strengthened to also generate data about dengue serotypes, severity, and primary and secondary infection from India.

Supporting information

S1 appendix, s2 appendix, s3 appendix, s1 checklist, funding statement.

The study was funded by the Department of Bio-technology, Govt of India. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Fibonacci wavelet collocation method for solving dengue fever sir model.

1. Introduction

2. fundamental definitions, 2.1. fibonacci polynomials, 2.2. fibonacci wavelets, 3. function approximation, 4. operational matrix of integration (omi), 5. stability analysis and solution of dengue fever sir model by fibonacci wavelet collocation method, 6. error analysis, 7. comparison of solutions obtained from different numerical methods (fwcm, bwcm, and rk4) and their error analysis, 8. conclusions, author contributions, data availability statement, conflicts of interest.

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Kumar, A.; Khan, A.; Abdullah, A. Fibonacci Wavelet Collocation Method for Solving Dengue Fever SIR Model. Mathematics 2024 , 12 , 2565. https://doi.org/10.3390/math12162565

Kumar A, Khan A, Abdullah A. Fibonacci Wavelet Collocation Method for Solving Dengue Fever SIR Model. Mathematics . 2024; 12(16):2565. https://doi.org/10.3390/math12162565

Kumar, Amit, Ayub Khan, and Abdullah Abdullah. 2024. "Fibonacci Wavelet Collocation Method for Solving Dengue Fever SIR Model" Mathematics 12, no. 16: 2565. https://doi.org/10.3390/math12162565

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