Dengue Situation in Bangladesh: An Epidemiological Shift in terms of Morbidity and Mortality

Clinical spectrum and risk factors of severe dengue infection: findings from the 2023 dengue outbreak in Bangladesh

BACKGROUND

Since the first detection of dengue in 2000, Bangladesh has been facing an increasing number of dengue patients and related deaths every year. This situation warrants the importance of quickly identifying severe dengue patients to expedite necessary medical interventions which could potentially reduce the adverse consequences. The aim of this study was to identify clinical features and laboratory parameters of the severe dengue patients in the 2023 dengue outbreak in Bangladesh.

METHODS

This hospital based cross-sectional study included the demographic, clinical and laboratory data of 1313 Dengue patients from several secondary and tertiary hospitals across Bangladesh from August 2023 to December 2023. According to the 2009 WHO classification, dengue cases were classified into severe dengue and non-severe dengue (with and without warning signs). Chi-square test, Fischer's exact test and multiple logistic regression analyses were conducted to identify potential risk factors associated with severe dengue cases.

RESULTS

Of the 1313 patients included in this study, nearly 20% had severe dengue, 36.71% of them were from the 16-25 year age bracket and nearly two-thirds were male. Fever (99.54%) was the most common clinical symptom followed by anorexia (69.54%) and severe headache (66.03%); whereas most common warning signs were severe lethargy (43.64%), persistent vomiting (27.57%), and severe abdominal pain and tenderness (20.03%) across all patients. Gastrointestinal symptoms such as nausea, vomiting, and diarrhea are significantly more common in severe dengue cases compared to non-severe ones. Among the laboratory parameters, decrease of platelet level and increased ALT level was more prominent in severe patients. Multiple logistic regression analysis found that severe abdominal pain, severe lethargy, respiratory distress, altered mental status, decreased urine output, pleural effusion and ascites were positively associated with the development of severe dengue.

CONCLUSION

This study presents warning signs, clinical symptoms and trends of laboratory parameters associated with severe cases of dengue in Bangladesh that can be used in improving patient management in the future.

Clinical and Laboratory Features and Treatment Outcomes of Dengue Fever in Pediatric Cases

Background Globally, dengue fever (DF) is the leading cause of arthropod-borne viral illness, which considerably contributes to an atrocious death rate. The disease is now endemic in some parts of the world, including Bangladesh. The disorder exhibits a wide range of clinical and laboratory features in children. Judicial fluid resuscitation during the critical phase and prompt referral to the appropriate health facility can be lifesaving. Objectives This research appraised clinical and laboratory features and treatment outcomes of DF in pediatric cases. Methods This prospective investigative work was conducted at Islami Bank Hospital, Dhaka, India, from July to October 2023. The study included 135 admitted pediatric cases of DF, either dengue nonstructural protein 1 (NS1) or anti-dengue antibody IgM or IgG positive. Results Among the selected cases, boys were more predominant than girls, and most patients were in the age group of 5 to 10 years (n=46, 34%), most of them belonging to lower-middle-class families (n=56, 41.5%). All of the study participants had raised body temperatures, and most had abdominal pain (n=82, 60.7%), vomiting (n=77, 57%), cough (n=43, 31.9%), headache (n=38, 28.2%), body aches (n=32, 23.7%), and diarrhea (n=23, 17%). Dengue NS1 was positive in 91.1% (n=123) of cases. Raised hematocrit was found in 36.3% (n=49) of cases, leukopenia in 47% (n=63), and thrombocytopenia in 69.6% (n=94) of cases. Most of our patients were categorized as having DF (68.1%, n=92), followed by dengue with warning signs (16.3%, n=22), and severe dengue was present in 15.6% (n=21) of patients. Most were treated with crystalloid, and some with crystalloid and colloid solution. Fortunately, most of them recovered with no death. Conclusion DF may manifest with varied clinical and laboratory features in children. Appropriate treatment of critical phases, depending on clinical and laboratory features, is crucial to reducing dengue-induced miseries and fatal clinical outcomes among the pediatric population.

Dengue in Tomorrow: Predictive Insights From ARIMA and SARIMA Models in Bangladesh: A Time Series Analysis

Backgrounds and Aims

Dengue fever has been a continued public health problem in Bangladesh, with a recent surge in cases. The aim of this study was to train ARIMA and SARIMA models for time series analysis on the monthly prevalence of dengue in Bangladesh and to use these models to forecast the dengue prevalence for the next 12 months.

Methods

This secondary data-based study utilizes AutoRegressive Integrated Moving Average (ARIMA) and Seasonal AutoRegressive Integrated Moving Average (SARIMA) models to forecast dengue prevalence in Bangladesh. Data was sourced from the Institute of Epidemiology Disease Control and Research (IEDCR) and the Directorate General of Health Services (DGHS). STROBE Guideline for observational studies was followed for reporting this study.

Results

The ARIMA (1,1,1) and SARIMA (1,1,2) models were identified as the best-performing models. The forecasts indicate a steady dengue prevalence for 2024 according to ARIMA, while SARIMA predicts significant fluctuations. It was observed that ARIMA (1,1,1) and SARIMA (1,2,2) (1,1,2) 12 were the most suitable models for prediction of dengue prevalence.

Conclusion

These models offer valuable insights for healthcare planning and resource allocation, although external factors and complex interactions must be considered. Dengue prevalence is expected to rise in future in Bangladesh.

Impact of climate change on vector-borne diseases: Exploring hotspots, recent trends and future outlooks in Bangladesh

Climate change is a significant risk multiplier and profoundly influences the transmission dynamics, geographical distribution, and resurgence of vector-borne diseases (VBDs). Bangladesh has a noticeable rise in VBDs attributed to climate change. Despite the severity of this issue, the interconnections between climate change and VBDs in Bangladesh have yet to be thoroughly explored. To address this research gap, our review meticulously examined existing literature on the relationship between climate change and VBDs in Bangladesh. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, we identified 3849 records from SCOPUS, Web of Science, and Google Scholar databases. Ultimately, 22 research articles meeting specific criteria were included. We identified that the literature on the subject matter of this study is non-contemporaneous, with 68% of studies investing datasets before 2014, despite studies on climate change and dengue nexus having increased recently. We pinpointed Dhaka and Chittagong Hill Tracts as the dengue and malaria research hotspots, respectively. We highlighted that the 2023 dengue outbreak illustrates a possible shift in dengue-endemic areas in Bangladesh. Moreover, dengue cases surged by 317% in 2023 compared to 2019 records, with a corresponding 607% increase in mortality compared to 2022. A weak connection was observed between dengue incidents and climate drivers, including the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). However, no compelling evidence supported an association between malaria cases, and Sea Surface Temperature (SST) in the Bay of Bengal, along with the NINO3 phenomenon. We observed minimal microclimatic and non-climatic data inclusion in selected studies. Our review holds implications for policymakers, urging the prioritization of mitigation measures such as year-round surveillance and early warning systems. Ultimately, it calls for resource allocation to empower researchers in advancing the understanding of VBD dynamics amidst changing climates.

Understanding the unprecedented 2023 dengue outbreak in Bangladesh: a data-driven analysis

Objectives

This study aims to elucidate the epidemiological characteristics, spatial distribution, and potential contributing factors associated with the 2022-2023 dengue outbreak in Bangladesh.

Methods

We retrospectively analyzed dengue fever cases reported by national health surveillance systems, focusing on incidence, geographical spread, and fatalities. Statistical methods were used to explore correlations between population density, healthcare capacity, and disease prevalence.

Results

Our study revealed that in 2023, dengue cases and deaths surged five-fold (from 62,382 to 320,835) and nearly six-fold (from 281 to 1699) compared with 2022. Major cities such as Dhaka and Chittagong emerged as epicenters with significantly higher caseloads and mortality rates. The analysis identified a strong positive correlation between population density and disease prevalence, suggesting urbanization as a contributing factor. In addition, a shift in the peak dengue season from August to September was observed. Furthermore, disparities in health care infrastructure were identified, with densely populated areas experiencing critical shortages of hospital beds, potentially impacting fatality rates.

Conclusions

This unprecedented dengue outbreak in Bangladesh highlights the need for a multifaceted approach. Prioritizing vector control, targeted public awareness in identified hotspots, addressing healthcare resource inequities, and further research on environmental and demographic determinants of transmission are crucial for mitigating future outbreaks in Bangladesh.

An effective pan-serotype dengue vaccine and enhanced control strategies could help in reducing the severe dengue burden in Bangladesh-A perspective

Dengue is an important vector-borne disease occurring globally. Dengue virus (DENV) infection can result in a potentially life-threatening disease. To date, no DENV-specific antiviral treatment is available. Moreover, an equally effective pan-serotype dengue virus vaccine is not available. Recently, two DENV vaccines, Dengvaxia and Qdenga, were licensed for limited use. However, none of them have been approved in Bangladesh. DENV is transmitted by Aedes mosquitoes, and global warming caused by climate change favoring Aedes breeding plays an important role in increasing DENV infections in Bangladesh. Dengue is a serious public health concern in Bangladesh. In the year 2023, Bangladesh witnessed its largest dengue outbreak, with the highest number of dengue cases (n = 321,179) and dengue-related deaths (n = 1,705) in a single epidemic year. There is an increased risk of severe dengue in individuals with preexisting DENV-specific immunoglobulin G if the individuals become infected with different DENV serotypes. To date, vector control has remained the mainstay for controlling dengue; therefore, an immediate, strengthened, and effective vector control program is critical and should be regularly performed for controlling dengue outbreaks in Bangladesh. In addition, the use of DENV vaccine in curbing dengue epidemics in Bangladesh requires more consideration and judgment by the respective authority of Bangladesh. This review provides perspectives on the control and prevention of dengue outbreaks. We also discuss the challenges of DENV vaccine use to reduce dengue epidemics infection in Bangladesh.

Dengue fever mapping in Bangladesh: A spatial modeling approach

Background

Epidemics of the dengue virus can trigger widespread morbidity and mortality along with no specific treatment. Examining the spatial autocorrelation and variability of dengue prevalence throughout Bangladesh's 64 districts was the focus of this study.

Methods

The spatial autocorrelation is evaluated with the help of Moran I and Geary C . Local Moran I was used to detect hotspots and cold spots, whereas local Getis Ord G was used to identify only spatial hotspots. The spatial heterogeneity has been detected using various conventional and spatial models, including the Poisson-Gamma model, the Poisson-Lognormal Model, the Conditional Autoregressive (CAR) model, the Convolution model, and the BYM2 model, respectively. These models are implemented using Gibbs sampling and other Bayesian hierarchical approaches to analyze the posterior distribution effectively, enabling inference within a Bayesian context.

Results

The study's findings show that Moran I and Geary C analysis provides a substantial clustering pattern of positive spatial autocorrelation of dengue fever (DF) rates between surrounding districts at a 90% confidence interval. The Local Indicators of Spatial Autocorrelation cluster mapped spatial clusters and outliers based on prevalence rates, while the local Getis-Ord G displayed a thorough breakdown of high or low rates, omitting outliers. Although Chattogram had the most dengue cases (15,752), Khulna district had a higher prevalence rate (133.636) than Chattogram (104.796). The BYM2 model, determined to be well-fitted based on the lowest Deviance Information Criterion value (527.340), explains a significant association between spatial heterogeneity and prevalence rates.

Conclusion

This research pinpoints the district with the highest prevalence rate for dengue and the neighboring districts that also have high risk, allowing government agencies and communities to take the necessary precautions to mollify the risk effect of DF.

Two decades of endemic dengue in Bangladesh (2000-2022): trends, seasonality, and impact of temperature and rainfall patterns on transmission dynamics

The objectives of this study were to compare dengue virus (DENV) cases, deaths, case-fatality ratio [CFR], and meteorological parameters between the first and the recent decades of this century (2000-2010 vs. 2011-2022) and to describe the trends, seasonality, and impact of change of temperature and rainfall patterns on transmission dynamics of dengue in Bangladesh. For the period 2000-2022, dengue cases and death data from Bangladesh's Ministry of Health and Family Welfare's website, and meteorological data from the Bangladesh Meteorological Department were analyzed. A Poisson regression model was performed to identify the impact of meteorological parameters on the monthly dengue cases. A forecast of dengue cases was performed using an autoregressive integrated moving average model. Over the past 23 yr, a total of 244,246 dengue cases were reported including 849 deaths (CFR = 0.35%). The mean annual number of dengue cases increased 8 times during the second decade, with 2,216 cases during 2000-2010 vs. 18,321 cases during 2011-2022. The mean annual number of deaths doubled (21 vs. 46), but the overall CFR has decreased by one-third (0.69% vs. 0.23%). Concurrently, the annual mean temperature increased by 0.49 °C, and rainfall decreased by 314 mm with altered precipitation seasonality. Monthly mean temperature (Incidence risk ratio [IRR]: 1.26), first-lagged rainfall (IRR: 1.08), and second-lagged rainfall (IRR: 1.17) were significantly associated with monthly dengue cases. The increased local temperature and changes in rainfall seasonality might have contributed to the increased dengue cases in Bangladesh.

Excess mortality during the COVID-19 pandemic (2020-2021) in an urban community of Bangladesh

Measuring COVID-19-related mortality is vital for making public health policy decisions. The magnitude of COVID-19-related mortality is largely unknown in low- and middle-income countries (LMICs), including Bangladesh, due to inadequate COVID-19 testing capacity and a lack of robust civil registration and vital statistics systems. Even with the lack of data, cemetery-based death records in LMICs may provide insightful information on potential COVID-19-related mortality rates; nevertheless, there is a dearth of research employing cemetery-based death records. This study aimed to assess the excess mortality during the COVID-19 pandemic in an urban setting in Bangladesh using a cemetery-based death registration dataset. A total of 6,271 deaths recorded between January 2015 and December 2021 were analysed using a Bayesian structural time series model. Exploratory analysis found that the average monthly number of deaths was 69 during the pre-COVID-19 period (January 2015-February 2020), but significantly increased to 92 during the COVID-19 period (March 2020-December 2021). The increase in male deaths was twice as large as the increase in female deaths. Model-based results were not statistically significant (relative effect 17%, 95% credible interval: -18%, 57%), but there was an overall increasing trend during the COVID-19 period, and specific months or shorter periods had a substantial increase. This first-of-its-kind study in Bangladesh has assessed the excess mortality in an urban community during the COVID-19 pandemic. Cemetery-based death registration appears to aid in tracking population mortality, especially in resource-limited countries where collecting data on the ground is challenging during crisis periods; however, additional large-scale research is required.

Twenty-two years of dengue outbreaks in Bangladesh: epidemiology, clinical spectrum, serotypes, and future disease risks

Dengue is the most rapidly spreading mosquito-borne disease and has become a major public health threat, particularly for tropical and subtropical countries including Bangladesh. This comprehensive review aims to summarize the overall scenario of dengue, including disease burden, clinical spectrum, seroprevalence, circulating serotypes/genotypes, and spatial distribution since the first recorded outbreak in Bangladesh. Since the first recorded outbreak in 2000, dengue epidemiology has shown the typical epidemic pattern with more frequent and bigger outbreaks and gradual geographic expansion to non-endemic regions in Bangladesh. For instance, highly confined Rohingya refugee camps that provide shelters to nearly 1.2 million forcibly displaced vulnerable Myanmar nationals in Cox's Bazar district confronted a massive outbreak in 2022. Recent major outbreaks are found to be associated with the emergence of serotype DENV-3, which was undetected for a long time. Consequently, changes in serotypes might be attributed to increased severity in clinical manifestation in recent years. The existing weak surveillance and risk management systems are inadequate to deal with impending dengue risks. The healthcare system, particularly at the district level, is not prepared to manage impending large-scale dengue outbreaks in Bangladesh. Our findings would contribute to the development of strategies for dengue control and management in Bangladesh as well as other similar settings elsewhere in the world.

Recent Dengue Infection in Bangladesh: A Seasonal Endemic Progressing to Year-long Serious Health Concern

Dengue represents one of the most dangerous mosquito-borne viral diseases. Although the disease has been prevalent around the globe over the centuries, recent outbreaks of dengue have devasted the healthcare delivery system of many countries. Being a global infection, dengue virus (DENV) is endemically present mainly in Latin America and Caribbean countries as well as countries in South Asia. The recent outbreak of DENV infection has indicated an exceptional outbreak of DENV in some countries in South Asia. There has been a serious endemic of DENV during 2019. After a heterogeneous pause, another severe outbreak of DENV was reported in some Asian countries in 2023. Among the Asian countries, Bangladesh has reported an acute upsurge of DENV infection in 2023 with record numbers of fatalities. However, this pattern of DENV has not been detected in neighbors of Bangladesh, such as India or other countries in Southeast Asia. This provides an emergent task of dissecting the present DENV infection in Bangladesh from different angles to get insights for future containment of the DENV infection, not only in Bangladesh but also in other DENV endemic areas or DENV-native areas.

How to cite this article

Akbar SMF, Khan S, Mahtab M, et al. Recent Dengue Infection in Bangladesh: A Seasonal Endemic Progressing to Year-long Serious Health Concern. Euroasian J Hepato-Gastroenterol 2023;13(2):145-151.

Towfiqul Islam AR. Knowledge, Attitude and Practices Towards Dengue Fever Among Slum Dwellers: A Case Study in Dhaka City, Bangladesh

Objectives: This study intends to evaluate Dhaka city slum dwellers' responses to Dengue fever (DF). Methods: 745 individuals participated in a KAP survey that was pre-tested. Face-to-face interviews were performed to obtain data. Python with RStudio was used for data management and analysis. The multiple regression models were applied when applicable. Results: 50% of respondents were aware of the deadly effects of DF, its common symptoms, and its infectious nature. However, many were unaware that DF could be asymptomatic, a previously infected person could have DF again, and the virus could be passed to a fetus. Individuals agreed that their families, communities, and authorities should monitor and maintain their environment to prevent Aedes mosquito breeding. However, overall 60% of the study group had inadequate preventative measures. Many participants lacked necessary practices such as taking additional measures (cleaning and covering the water storage) and monitoring potential breeding places. Education and types of media for DF information were shown to promote DF prevention practices. Conclusion: Slum dwellers lack awareness and preventative activities that put them at risk for DF. Authorities must improve dengue surveillance. The findings suggest efficient knowledge distribution, community stimulation, and ongoing monitoring of preventative efforts to reduce DF. A multidisciplinary approach is needed to alter dwellers' behavior since DF control can be done by raising the population's level of life. People and communities must perform competently to eliminate vector breeding sites.

Recent outbreak of dengue in Bangladesh: A threat to public health

Background and Aims

The dengue virus is widespread throughout Bangladesh and significantly contributes to morbidity and mortality. One effective method for preventing further dengue epidemics is to reduce mosquito breeding at the most opportune period each year. This study aims to determine dengue prevalence in 2022 by comparing previous years' data and estimating the period of this disease's most significant incidence.

Methods

From the beginning of 2008-December 15, 2022, we looked at the monthly reports of cases made to the Bangladesh Institute of Epidemiology, Disease Control, and Research.

Results

According to our findings, there were 61089 confirmed dengue cases in 2022, with 269 fatalities - the highest annual death toll for this disease since 2000. Almost one-third (32.14%) of all dengue deaths in Bangladesh occurred in 2022 (1 January-15 December), highlighting the severity of the threat posed by this disease in the coming year. Furthermore, we observe that the months in the second half of any year in Bangladesh are the most at risk for dengue transmission. In 2022, Dhaka city and Chittagong are hit the hardest (incidence: 63.07% vs. 14.42%; morality: 63.34% vs. 24.16%), showing the relevance of population density in spreading this fatal disease.

Conclusion

Statistics show an increase in dengue cases every day, and the year 2022 will be marked as the peak of the disease's death prevalence. Both the individuals and the government of Bangladesh need to take action to reduce the dissemination of this epidemic. If not, the country will soon be in great peril.

Correlation of Dengue and Meteorological Factors in Bangladesh: A Public Health Concern

Dengue virus (DENV) is an enveloped, single-stranded RNA virus, a member of the Flaviviridae family (which causes Dengue fever), and an arthropod-transmitted human viral infection. Bangladesh is well known for having some of Asia's most vulnerable Dengue outbreaks, with climate change, its location, and it's dense population serving as the main contributors. For speculation about DENV outbreak characteristics, it is crucial to determine how meteorological factors correlate with the number of cases. This study used five time series models to observe the trend and forecast Dengue cases. Current data-based research has also applied four statistical models to test the relationship between Dengue-positive cases and meteorological parameters. Datasets were used from NASA for meteorological parameters, and daily DENV cases were obtained from the Directorate General of Health Service (DGHS) open-access websites. During the study period, the mean of DENV cases was 882.26 ± 3993.18, ranging between a minimum of 0 to a maximum of 52,636 daily confirmed cases. The Spearman's rank correlation coefficient between climatic variables and Dengue incidence indicated that no substantial relationship exists between daily Dengue cases and wind speed, temperature, and surface pressure (Spearman's rho; r = -0.007, p > 0.05; r = 0.085, p > 0.05; and r = -0.086, p > 0.05, respectively). Still, a significant relationship exists between daily Dengue cases and dew point, relative humidity, and rainfall (r = 0.158, p < 0.05; r = 0.175, p < 0.05; and r = 0.138, p < 0.05, respectively). Using the ARIMAX and GA models, the relationship for Dengue cases with wind speed is -666.50 [95% CI: -1711.86 to 378.86] and -953.05 [-2403.46 to 497.36], respectively. A similar negative relation between Dengue cases and wind speed was also determined in the GLM model (IRR = 0.98). Dew point and surface pressure also represented a negative correlation in both ARIMAX and GA models, respectively, but the GLM model showed a positive association. Additionally, temperature and relative humidity showed a positive correlation with Dengue cases (105.71 and 57.39, respectively, in the ARIMAX, 633.86, and 200.03 in the GA model). In contrast, both temperature and relative humidity showed negative relation with Dengue cases in the GLM model. In the Poisson regression model, windspeed has a substantial significant negative connection with Dengue cases in all seasons. Temperature and rainfall are significantly and positively associated with Dengue cases in all seasons. The association between meteorological factors and recent outbreak data is the first study where we are aware of the use of maximum time series models in Bangladesh. Taking comprehensive measures against DENV outbreaks in the future can be possible through these findings, which can help fellow researchers and policymakers.

Relationship between Urban Environmental Components and Dengue Prevalence in Dhaka City-An Approach of Spatial Analysis of Satellite Remote Sensing, Hydro-Climatic, and Census Dengue Data

Dengue fever is a tropical viral disease mostly spread by the Aedes aegypti mosquito across the globe. Each year, millions of people have dengue fever, and many die as a result. Since 2002, the severity of dengue in Bangladesh has increased, and in 2019, it reached its worst level ever. This research used satellite imagery to determine the spatial relationship between urban environmental components (UEC) and dengue incidence in Dhaka in 2019. Land surface temperature (LST), urban heat-island (UHI), land-use-land-cover (LULC), population census, and dengue patient data were evaluated. On the other hand, the temporal association between dengue and 2019 UEC data for Dhaka city, such as precipitation, relative humidity, and temperature, were explored. The calculation indicates that the LST in the research region varies between 21.59 and 33.33 degrees Celsius. Multiple UHIs are present within the city, with LST values ranging from 27 to 32 degrees Celsius. In 2019, these UHIs had a higher incidence of dengue. NDVI values between 0.18 and 1 indicate the presence of vegetation and plants, and the NDWI identifies waterbodies with values between 0 and 1. About 2.51%, 2.66%, 12.81%, and 82% of the city is comprised of water, bare ground, vegetation, and settlement, respectively. The kernel density estimate of dengue data reveals that the majority of dengue cases were concentrated in the city's north edge, south, north-west, and center. The dengue risk map was created by combining all of these spatial outputs (LST, UHI, LULC, population density, and dengue data) and revealed that UHIs of Dhaka are places with high ground temperature and lesser vegetation, waterbodies, and dense urban characteristics, with the highest incidence of dengue. The average yearly temperature in 2019 was 25.26 degrees Celsius. May was the warmest month, with an average monthly temperature of 28.83 degrees Celsius. The monsoon and post-monsoon seasons (middle of March to middle of September) of 2019 sustained higher ambient temperatures (>26 °C), greater relative humidity (>80%), and at least 150 mm of precipitation. The study reveals that dengue transmits faster under climatological circumstances characterized by higher temperatures, relative humidity, and precipitation.

Increasing Dengue Burden and Severe Dengue Risk in Bangladesh: An Overview

Dengue is a prevalent and rapidly spreading mosquito-borne viral disease affecting humans. The geographic range of dengue is expanding, and much like in many other tropical regions of the world, dengue has become a major public health issue in Bangladesh. Until a large epidemic dengue outbreak in 2000, sporadic outbreaks have occurred in Bangladesh since 1964. After 2000, varying intensities of dengue activity were observed each year until 2018. However, in 2019, Bangladesh experienced the largest dengue epidemic in its history, with 101,354 dengue cases and 164 dengue-related deaths. Notably, this outbreak occurred in many regions that were previously considered free of the disease. As of 10 December 2022, a total of 60,078 dengue cases and 266 dengue-related deaths were reported in Bangladesh, with the 2022 outbreak being the second largest since 2000. There is an increased genetic diversity of the dengue virus (DENV) in Bangladesh and all four DENV serotypes are prevalent and co-circulating, which increases the risk for severe dengue owing to the antibody-dependent enhancement effect. Vector control remains the mainstay of dengue outbreak prevention; however, the vector control programs adopted in Bangladesh seem inadequate, requiring improved vector control strategies. In this review, we provide an overview of the epidemiology of DENV infection and the risks for a severe dengue outbreak in Bangladesh. Additionally, we discuss different dengue vector control strategies, from which the most suitable and effective measures can be applied in the context of Bangladesh for tackling future dengue epidemics.

S-Adenosyl-l-Homocysteine Exhibits Potential Antiviral Activity Against Dengue Virus Serotype-3 (DENV-3) in Bangladesh: A Viroinformatics-Based Approach

Dengue outbreak is one of the concerning issues in Bangladesh due to the annual outbreak with the alarming number of death and infection. However, there is no effective antiviral drug available to treat dengue-infected patients. This study evaluated and screened antiviral drug candidates against dengue virus serotype 3 (DENV-3) through viroinformatics-based analyses. Since 2017, DENV-3 has been the predominant serotype in Bangladesh. We selected 3 non-structural proteins of DENV-3, named NS3, NS4A, and NS5, as antiviral targets. Protein modeling and validation were performed with VERIFY-3D, Ramachandran plotting, MolProbity, and PROCHECK. We found 4 drug-like compounds from DRUGBANK that can interact with these non-structural proteins of DENV-3. Then, the ADMET profile of these compounds was determined by admetSAR2, and molecular docking was performed with AutoDock, SWISSDOCK, PatchDock, and FireDock. Furthermore, they were subjected to molecular dynamics (MD) simulation study using the DESMOND module of MAESTRO academic version 2021-4 (force field OPLS_2005) to determine their solution's stability in a predefined body environment. Two drug-like compounds named Guanosine-5'-Triphosphate (DB04137) and S-adenosyl-l-homocysteine (DB01752) were found to have an effective binding with these 3 proteins (binding energy > 33.47 KJ/mole). We found NS5 protein was stable and equilibrated in a 100 ns simulation run along with a negligible (<3Å) root-mean-square fluctuation value. The root-mean-square deviation value of the S-adenosyl-l-homocysteine-NS5 complex was less than 3Å, indicating stable binding between them. The global binding energy of S-adenosyl-l-homocysteine with NS5 was -40.52 KJ/mole as ∆G. Moreover, these 2 compounds mentioned above are non-carcinogenic according to their ADMET (chemical absorption, distribution, metabolism, excretion, and toxicity) profile (in silico). These outcomes suggest the suitability of S-adenosyl-l-homocysteine as a potential drug candidate for dengue drug discovery research.

Dengue outbreaks prediction in Bangladesh perspective using distinct multilayer perceptron NN and decision tree

Dengue fever is a disease that has been outbreak worldwide in the last few years. Dengue is a fatal disease; sometimes, it may cause life-threatening complications and even death. Dengue is considered to be one of the critical diseases which is spreading in more than 110 countries. Nearly 45,000 case reports have been found around Bangladesh in the last year. Dengue fever has become a major health hazard in Bangladesh. Hence, early detection would mitigate major casualties of Dengue disease. Distinct studies have been performed concerning Dengue disease; however, no effective study, particularly from Bangladesh's perspective, it seemed that reveals Dengue outbreaks prediction method. In this scenario, this research work aims to analyse the Dengue disease and build an apposite model to predict dengue outbreaks. This paper also aims to find the best technique to early predicts Dengue disease. The real-time data of the patients admitted to different hospitals in Bangladesh is accumulated to achieve the goal of the current research. Then different multilayer perceptron neural networks and a Decision tree are used for Dengue outbreaks prediction. Twenty-five parameters are analysed to find these parameters' infection rates in this work. A comparative study of the developed models' performances is also accomplished to obtain a better Dengue outbreaks prediction model. The results evidence that the Levenberg-Marquardt is the best technique with 97.3% accuracy and 2.7% error in Dengue disease prediction. On the other hand, the Decision tree may have the second choice to assess Dengue disease.

Spatial association of Aedes aegypti with dengue fever hotspots in an endemic region

Background and objective

Dengue is a vector-borne viral disease usually transmitted by Aedes mosquitoes. Around the world, the relationship between local vector density and frequency of dengue cases is being explored and needs further evidence. This study aimed to analyze the potential spatial relationships between the dengue vector (Aedes aegypti) and dengue cases in the megacity of Bangladesh during the 2019 dengue outbreak.

Methods

Vector density measures were used to estimate spatial associations with dengue case distribution. Location was determined for 364 dengue cases who were admitted to Dhaka Medical College Hospital over a period of 4 months. Data were collected using a semi-structured questionnaire, and prior consent was ensured before participation. The Moran global index, Getis-Ord Gi∗, ordinary least squares regression, geographically weighted regression and count data regression methods were used for spatial analysis.

Results

We found that dengue case distribution was not associated with immature Aedes aegypti mosquito (larvae) density across the city. The relationship between larval density measured by the Breteau Index (BI) and House Index (HI) with dengue cases was nonstationary and not statistically significant.

Conclusion

The location of dengue cases appears to be unrelated to vector distribution and vector density. These findings should prompt the search for other transmission risk factors.

Sketch of 2018 dengue outbreak in a megacity, Bangladesh

Background

Dengue has become a major public health threat in Bangladesh since 2000, when the first outbreak was reported. Each outbreak has distinct characteristics, and thus, the report of the outbreak helps to understand the disease process and subsequent clinical management of these patients. On that ground, the study was designed to sketch the clinico-epidemiological characteristics of the 2018 dengue outbreak in Bangladesh.

Methods

This hospital-based cross-sectional study was conducted in one of the largest public medical college hospitals and a single private hospital located in the southern and northern parts of the megacity of the country. A total of 297 confirmed dengue cases were assessed with a preformed pretested questionnaire. Clinico-epidemiological and laboratory parameters were reported along with sociodemographic details. Statistical analysis was performed with SPSS 20.

Results

Male patients were predominantly affected by dengue infection. The mean age of the patients was 31.24 ± 13.99 (SD) years, with a range from 2 to 85 years. Eighty-two percent of patients reported from the Dhaka metropolitan city. The highest percentage of cases (37.1%) was isolated from Bansree, Dhaka city, followed by Rampura (21.4%) and Khilgaon (6.2%). In addition to common symptoms, e.g., fever (90.6%), headache (90.6%), chills (81.8%), anorexia and vomiting (76.4%), backache, and redness of the eyes were two prominent symptoms that affected more than two-thirds of the study population. On the other hand, less common symptoms, such as cough, abdominal pain, and respiratory distress, were present in 39.7%, 33.7%, and 15.5% of patients, respectively. Overall, 17.6% of patients were hypotensive during admission, with a mean systolic blood pressure of 107.65 ± 18.17 (SD) mmHg. Other prominent signs were dehydration (80.5%) and rash (33%).

Conclusion

This outbreak was especially characterized by gastrointestinal symptoms, which were predominant along with other typical features.

Acute febrile illness among outpatients seeking health care in Bangladeshi hospitals prior to the COVID-19 pandemic

Understanding the distribution of pathogens causing acute febrile illness (AFI) is important for clinical management of patients in resource-poor settings. We evaluated the proportion of AFI caused by specific pathogens among outpatients in Bangladesh. During May 2019-March 2020, physicians screened patients aged ≥2 years in outpatient departments of four tertiary level public hospitals. We randomly enrolled patients having measured fever (≥100.4°F) during assessment with onset within the past 14 days. Blood and urine samples were tested at icddr,b through rapid diagnostic tests, bacterial culture, and polymerase chain reaction (PCR). Acute and convalescent samples were sent to the Centers for Disease Control and Prevention (USA) for Rickettsia and Orientia (R/O) and Leptospira tests. Among 690 patients, 69 (10%) had enteric fever (Salmonella enterica serotype Typhi orSalmonella enterica serotype Paratyphi), 51 (7.4%) Escherichia coli, and 28 (4.1%) dengue detected. Of the 441 patients tested for R/O, 39 (8.8%) had rickettsioses. We found 7 (2%) Leptospira cases among the 403 AFI patients tested. Nine patients (1%) were hospitalized, and none died. The highest proportion of enteric fever (15%, 36/231) and rickettsioses (14%, 25/182) was in Rajshahi. Dhaka had the most dengue cases (68%, 19/28). R/O affected older children and young adults (IQR 8-23 years) and was detected more frequently in the 21-25 years age-group (17%, 12/70). R/O was more likely to be found in patients in Rajshahi region than in Sylhet (aOR 2.49, 95% CI 0.85-7.32) between July and December (aOR 2.01, 1.01-5.23), and who had a history of recent animal entry inside their house than not (aOR 2.0, 0.93-4.3). Gram-negative Enterobacteriaceae were the most common bacterial infections, and dengue was the most common viral infection among AFI patients in Bangladeshi hospitals, though there was geographic variability. These results can help guide empiric outpatient AFI management.

Dengue Fever Responses in Dhaka City, Bangladesh: A Cross-Sectional Survey

Objectives: This study intends to evaluate the Dhaka city residents’ individual views toward DF.

Methods: A cross-sectional survey used google forms for collecting data. Python and RStudio were used for data management and analysis. Kruskal-Wallis or Mann-Whitney U test and logistic regression models were performed, where appropriate.

Results: In total 1008 individuals participated in a pre-tested KAP survey. More than 20% reported being affected by DF before the survey, where they rated their current places as being moderately safe (43%). In terms of DF control, 65% had good knowledge, and 68% reported good practice, whereas they demonstrated an overall good attitude. The increased knowledge of individuals could contribute to behavioral changes regarding DF. Female residents demonstrated better DF attitudes (OR: 0.69; p &lt; 0.05) and practices (OR: 0.66; p &lt; 0.01) compared to male residents. Mixed unit residents had poor KAP levels. Educational attainment can also play an essential role in enhancing the attitude level.

Conclusion: Overall, dengue surveillance activities with sufficient campaigns are required for behavioral change in Dhaka city. This information could be integrated into other DF-affected countries’ strategies against dengue outbreaks.

Shapley-Additive-Explanations-Based Factor Analysis for Dengue Severity Prediction using Machine Learning

Dengue is a viral disease that primarily affects tropical and subtropical regions and is especially prevalent in South-East Asia. This mosquito-borne disease sometimes triggers nationwide epidemics, which results in a large number of fatalities. The development of Dengue Haemorrhagic Fever (DHF) is where most cases occur, and a large portion of them are detected among children under the age of ten, with severe conditions often progressing to a critical state known as Dengue Shock Syndrome (DSS). In this study, we analysed two separate datasets from two different countries- Vietnam and Bangladesh, which we referred as VDengu and BDengue, respectively. For the VDengu dataset, as it was structured, supervised learning models were effective for predictive analysis, among which, the decision tree classifier XGBoost in particular produced the best outcome. Furthermore, Shapley Additive Explanation (SHAP) was used over the XGBoost model to assess the significance of individual attributes of the dataset. Among the significant attributes, we applied the SHAP dependence plot to identify the range for each attribute against the number of DHF or DSS cases. In parallel, the dataset from Bangladesh was unstructured; therefore, we applied an unsupervised learning technique, i.e., hierarchical clustering, to find clusters of vital blood components of the patients according to their complete blood count reports. The clusters were further analysed to find the attributes in the dataset that led to DSS or DHF.

Prediction of dengue incidents using hospitalized patients, metrological and socio-economic data in Bangladesh: A machine learning approach

Dengue fever is a severe disease spread by Aedes mosquito-borne dengue viruses (DENVs) in tropical areas such as Bangladesh. Since its breakout in the 1960s, dengue fever has been endemic in Bangladesh, with the highest concentration of infections in the capital, Dhaka. This study aims to develop a machine learning model that can use relevant information about the factors that cause Dengue outbreaks within a geographic region. To predict dengue cases in 11 different districts of Bangladesh, we created a DengueBD dataset and employed two machine learning algorithms, Multiple Linear Regression (MLR) and Support Vector Regression (SVR). This research also explores the correlation among environmental factors like temperature, rainfall, and humidity with the rise and decline trend of Dengue cases in different cities of Bangladesh. The entire dataset was divided into an 80:20 ratio, with 80 percent used for training and 20% used for testing. The research findings imply that, for both the MLR with 67% accuracy along with Mean Absolute Error (MAE) of 4.57 and SVR models with 75% accuracy along with Mean Absolute Error (MAE) of 4.95, the number of dengue cases reduces throughout the winter season in the country and increases mainly during the rainy season in the next ten months, from August 2021 to May 2022. Importantly, Dhaka, Bangladesh's capital, will see the maximum number of dengue patients during this period. Overall, the results of this data-driven analysis show that machine learning algorithms have enormous potential for predicting dengue epidemics.

Epidemiological and hematological investigation of Dengue Virus infection

Dengue is a mosquito-borne viral illness that infects humans. For the last few decades, it has been declared a global public health problem. The current study was conducted at the district headquarter hospital (DHQ) Bannu between June to September 2018 based on the seroprevalence of antibodies against dengue virus serotypes and their hematological parameters among the patients. A total of 1738 suspected individuals were diagnosed through NS1, IgG, and IgM antibodies and RT-PCR techniques. Out of all the samples, 716 (41.19%) were found to be positive for dengue. A higher infection rate was found in males (65.92%) as compared to females (34.07%). The most affected age group was 16-40 years, whereas the most affected tehsil was Bannu, where the DENV-3 serotype was prevalent. The rare serotype (DENV-4) was found in 1% of cases. Symptoms including fever (100%), myalgia (100%), headache (61.31%), vomiting (34.63%), and rashes were common among the dengue patients. However, the mild cases showed fewer clinical signs compared to the severe infected cases. The study also revealed a significant association (P<0.05) between hematological parameters and dengue infection, showing a significant decrease in TC, eosinophils, neutrophils, and platelets and a significant increase in monocytes and lymphocytes. Based on the current report, it is concluded that patients with the above symptoms and hematological changes may have increased probability of Dengue and should be kept under observation to separate dengue positive patients and enhance treatment process. This article is protected by copyright. All rights reserved.

A retrospective study on the socio-demographic factors and clinical parameters of dengue disease and their effects on the clinical course and recovery of the patients in a tertiary care hospital of Bangladesh

Dengue, a mosquito transmitted febrile viral disease, is a serious public health concern in Bangladesh. Despite significant number of incidences and reported deaths each year, there are inadequate number of studies relating the temporal trends of the clinical parameters as well as socio-demographic factors with the clinical course of the disease. Therefore, this study aims to associate the clinical parameters, demographic and behavioral factors of the dengue patients admitted in a tertiary care hospital in Dhaka, Bangladesh during the 2019 outbreak of dengue with the clinical course of the disease. Data were collected from the 336 confirmed dengue in-patients and analyzed using SPSS 26.0 software. Majority of the patients were male (2.2 times higher than female) who required longer time to recover compared to females (p < 0.01), urban resident (54.35%) and belonged to the age group of 18–40 years (73.33%). Dengue fever (90.77%) and dengue hemorrhagic fever (5.95%) were reported in most of the dengue patients while fever (98%) was the most frequently observed symptom. A significantly positive association was found between patient’s age and number of manifested symptoms (p = 0.013). Average duration of stay in the hospital was 4.9 days (SD = 1.652) and patient’s recovery time was positively correlated with delayed hospitalization (p < 0.01). Additionally, recovery time was negatively correlated with initial blood pressure (both systolic (p = 0.001, and diastolic (p = 0.023)) and platelet count (p = 0.003) of the patients recorded on the first day of hospitalization. Finally, a statistical model was developed which predicted that, hospital stay could be positively associated with an increasing trend of temperature, systolic blood pressure and reduced platelets count. Findings of this study may be beneficial to better understand the clinical course of the disease, identify the potential risk factors and ensure improved patient management during future dengue outbreaks.

Knowledge, Attitude, and Practices towards Dengue Fever among University Students of Dhaka City, Bangladesh

Dhaka has become the worst affected city in Bangladesh regarding dengue fever (DF). A large number of university students are residing in this city with a high DF risk. This cross-sectional study was conducted to assess the DF status and responses among these students through their Knowledge, Attitude, and Practices (KAP) survey. A total of 625 students participated in an online self-reported survey. Statistical analyses were performed to assess the status and KAP regarding DF. University students from the city perceived their living places as moderately safe (45.28%) against DF, whereas about 20% reported their DF infection history. Some of these students had exemplary DF knowledge (66.72%), attitude (89.28%), and practices (68.32%). However, many of them were also observed with a lack of knowledge about this disease’s infectious behavior, recognizing Aedes mosquito breeding sites, multiple infection cases, and the risk of DF viral infection during pregnancy. Fair correlations (p < 0.001) were determined in the KAP domain. Gender, residential unit, major, and dengue-relevant subjects were found to be significant predictors (p < 0.05) of KAP level in the univariate analysis. Major subject and residential units remained significant predictors of overall KAP level in further multiple analysis. This study revealed the urgency of infectious disease-related subjects and the relevant demonstration into the university curriculum. The study’s findings can assist the university, government and non-governmental organizations, and the health and social workers to prepare a comprehensive dengue response and preparedness plan.

Impact of environmental factors on the spread of dengue fever in Sri Lanka

Dengue fever is a mosquito-borne viral disease caused by the dengue virus of the Flaviviridae family and is responsible for colossal health and economic burden worldwide. This study aimed to investigate the effect of environmental, seasonal, and spatial variations on the spread of dengue fever in Sri Lanka. The study used secondary data of monthly dengue infection and the monthly average of environmental parameters of 26 Sri Lankan regions from January 2015 to December 2019. Besides the descriptive measurements, Kendall's tau_b, Spearman's rho, and Kruskal-Wallis H test have been performed as bivariate analyses. The multivariate generalized linear negative binomial regression model was applied to determine the impacts of meteorological factors on dengue transmission. The aggregate negative binomial regression model disclosed that precipitation (odds ratio: 0.97, p < 0.05), humidity (odds ratio: 1.05, p < 0.01), and air pressure (odds ratio: 1.46, p < 0.01) were significantly influenced the spread of dengue fever in Sri Lanka. The bioclimatic zone is the vital factor that substantially affects the dengue infection, and the wet zone (odds ratio: 6.41, p < 0.05) was more at-risk than the dry zone. The climate season significantly influenced dengue fever transmission, and a higher infection rate was found (odds ratio: 1.46, p < 0.01) in the northeast monsoon season. The findings of this study facilitate policymakers to improve the existing dengue control strategies focusing on the meteorological condition in the local as well as global perspectives.

Clinico-epidemiologic characteristics of the 2019 dengue outbreak in Bangladesh

BACKGROUND

Dengue fever shows a broad range of clinical presentations worldwide. Here we report on our clinical findings during the 2019 dengue outbreak in one of the largest tertiary care hospitals in Dhaka, the capital of Bangladesh.

METHODS

A total of 747 suspected dengue cases (553 confirmed and 194 probable) were interviewed with a pro forma case record form. Statistical analyses were conducted using SPSS 20.0. Ethical clearance was obtained from the Dhaka Medical College.

RESULTS

The mean age of the dengue cases was 27 y and approximately two-thirds were male. Positive tests for NS1 and anti-dengue immunoglobulin M antibody were present in 91.9% and 59.4% of the cases, respectively. Thrombocytopenia was present in 69% of cases and fever was present in 99.1% of cases. Gastrointestinal (GI) features, including anorexia and/or vomiting (69.4%), abdominal pain (39.8%) and diarrhoea (25.6%), were more prevalent than typical rash and pain symptoms. Hypotension was present in approximately one-quarter of patients (25.4%). Probable and confirmed dengue cases have shown similar clinical characteristics and laboratory findings.

CONCLUSIONS

The 2019 outbreak of dengue fever in Bangladesh was characterized by increased presentation with GI features. Recognition of this trend would permit early diagnosis and proper management of patients.

Knowledge, awareness and preventive practices of dengue outbreak in Bangladesh: A countrywide study

Background

Dengue, the mosquito borne disease has become a growing public health threat in Bangladesh due to its gradual increasing morbidity and mortality since 2000. In 2019, the country witnessed the worst ever dengue outbreak. The present study was conducted to characterize the socio-economic factors and knowledge, attitude and practice (KAP) status towards dengue among the people of Bangladesh.

Method

A cross-sectional study was conducted with 1,010 randomly selected respondents from nine different administrative regions of Bangladesh between July and November 2019.

A structured questionnaire was used covering socio-demographic characteristics of the participants including their knowledge, awareness, treatment and practices regarding dengue fever. Factors associated with the knowledge and awareness of dengue were investigated separately, using multivariable logistic regression.

Results

Although majority (93.8%) of the respondents had heard about dengue, however, they had still misconceptions about Aedes breeding habitat. Around half of the study population (45.7%) had mistaken belief that Aedes can breed in dirty water and 43.1% knew that Aedes mosquito usually bites around sunrise and sunset. Fever indication was found in 36.6% of people which is the most common symptom of dengue. Among the socio-demographic variables, the level of education of the respondents was identified as an independent predictor for both knowledge (p<0.05) and awareness (p<0.05) of dengue. The preventive practice level was moderately less than the knowledge level though there was a significant association (p<0.05) existed between knowledge and preventive practices. Our study noted that TV/Radio is an effective predominant source of information about dengue fever.

Conclusion

As dengue is emerging in Bangladesh, there is an urgent need to increase health promotion activities through campaigns for eliminating the misconception and considerable knowledge gaps about dengue.

Dengue outbreak 2019: clinical and laboratory profiles of dengue virus infection in Dhaka city

Background

Dengue fever has been one of the most common mosquito-transmitted diseases in the world, affecting more than 128 countries in both tropical and subtropical regions. Bangladesh has been sufferring from dengue outbreaks almost annually since 2000, and in 2019, Bangladesh faced the worst outbreak of dengue to date. This study aimed to provide clinical and biochemical profiles of Bangladesh's dengue-infected patients.

Methods

This cross-sectional study was conducted from August through December 2019 in three tertiary private hospitals in Dhaka, Bangladesh. We collected information on demographic data, clinical characteristics, and laboratory profiles for 542 confirmed hospitalized acute dengue cases using a structured questionnaire.

Results

The average age of the enrolled patients was 26.15 years, and about 50% of patients belonged to the age group of 20–40 years. The most frequent among the prevalent clinical symptoms were fever (93.1%), abdominal pain (29.5%), skin rash (25.3%), and diarrhea (19.7%). 316 patients had some complications, such as breathing problems (41.4%), pleural effusion (38.9%), gum bleeding (11.1%), etc. More than 90% of the patients showed seropositivity for the DENV-NS1 antigen.

Conclusions

Over the last couple of years, dengue fever has become a major health issue for Bangladesh. To reduce the burden of this disease, timely diagnosis and prompt treatment are necessary. This analysis thus yields the clinical features, laboratory profiles, and seropositivity test results of dengue patients from Bangladesh. The research results may help clinicians understand the circumstantial diagnosis of dengue patients and facilitate early intervention.

Epidemiology of dengue virus infections in Nepal, 2006-2019

BACKGROUND

Dengue is one of the newest emerging diseases in Nepal with increasing burden and geographic spread over the years. The main objective of this study was to explore the epidemiological patterns of dengue since its first outbreak (2006) to 2019 in Nepal.

METHODS

This study is a retrospective analysis that covers the last 14 years (2006-2019) of reported dengue cases from Epidemiology Diseases Control Division (EDCD), Ministry of Health and Population, Government of Nepal. Reported cases were plotted over time and maps of reported case incidence were generated (from 2016 through 2019). An ecological analysis of environmental predictors of case incidence was conducted using negative binomial regression.

RESULTS

While endemic dengue has been reported in Nepal since 2006, the case load has increased over time and in 2019 a total of 17 992 dengue cases were reported from 68 districts (from all seven provinces). Compared to the case incidence in 2016, incidence was approximately five times higher in 2018 [incidence rate ratio (IRR): 4.8; 95% confidence interval (CI) 1.5-15.3] and over 140 times higher in 2019 (IRR: 141.6; 95% CI 45.8-438.4). A one standard deviation increase in elevation was associated with a 90% decrease in reported case incidence (IRR: 0.10; 95% CI 0.01-0.20). However, the association between elevation and reported cases varied across the years. In 2018 there was a cluster of cases reported from high elevation Kaski District of Gandaki Province. Our results suggest that dengue infections are increasing in magnitude and expanding out of the lowland areas to higher elevations over time.

CONCLUSIONS

There is a high risk of dengue outbreak in the lowland Terai region, with increasing spread towards the mid-mountains and beyond as seen over the last 14 years. Urgent measures are required to increase the availability of diagnostics and resources to mitigate future dengue epidemics.

Urban educated group's perceptions of the COVID-19 pandemic management in Bangladesh: a qualitative exploration

Background: Since the emergence of the COVID-19 outbreak, Government of Bangladesh (GoB) has taken various measures to restrict virus transmission and inform the people of the situation. However, the success of such measures largely depends on a positive public perception of the government's ability to act decisively and the transparency of its communication. We explored public perceptions of pandemic management efforts by the Bangladeshi health sector decision-makers in this study. Methods: As this qualitative research was conducted during the COVID-19 pandemic, data was gathered through seven online mixed-gender focus group discussions involving 50 purposively selected clinicians and non-clinicians. Results: The study participants concurred that, from the outset, decision-makers failed to engage the right kind of experts, which resulted in poor pandemic management that included imposing lockdown in periphery areas without arranging patient transport to the center, declaring certain hospitals as COVID-19 dedicated without preparing the facilities or the staff, and engaging private hospitals in care without allowing them to test the patients for COVID-19 infection. Several participants also commented on ineffective actions on behalf of the GoB, such as imposing home quarantine instead of institutional, corruption, miscommunication, and inadequate private sector regulation. The perception of the people regarding service providers is that they lacked responsiveness in providing treatment, with some doctors misleading the public by sharing misinformation. Service providers, on the other hand, observed that decision-makers failed to provide them with proper training, personal protective equipment, and workplace security, which has resulted in a high number of deaths among medical staff. Conclusions: The Bangladeshi health sector decision-makers should learn from their mistakes to prevent further unnecessary loss of life and long-term economic downturn. They should adopt a science-based response to the COVID-19 pandemic in the short term while striving to develop a more resilient health system in the long run.

Public perceptions of the COVID-19 pandemic management in Bangladesh: a qualitative exploration

Background: Since the emergence of the COVID-19 outbreak, Government of Bangladesh (GoB) has taken various measures to restrict virus transmission and inform the people of the situation. However, the success of such measures largely depends on a positive public perception of the government's ability to act decisively and the transparency of its communication. We explored public perceptions of pandemic management efforts by the Bangladeshi health sector decision-makers in this study. Methods: As this qualitative research was conducted during the COVID-19 pandemic, data was gathered through seven online mixed-gender focus group discussions involving 50 purposively selected clinicians and non-clinicians. Results: The study participants concurred that, from the outset, decision-makers failed to engage the right kind of experts, which resulted in poor pandemic management that included imposing lockdown in periphery areas without arranging patient transport to the center, declaring certain hospitals as COVID-19 dedicated without preparing the facilities or the staff, and engaging private hospitals in care without allowing them to test the patients for COVID-19 infection. Several participants also commented on ineffective actions on behalf of the GoB, such as imposing home quarantine instead of institutional, corruption, miscommunication, and inadequate private sector regulation. The perception of the people regarding service providers is that they lacked responsiveness in providing treatment, with some doctors misleading the public by sharing misinformation. Service providers, on the other hand, observed that decision-makers failed to provide them with proper training, personal protective equipment, and workplace security, which has resulted in a high number of deaths among medical staff. Conclusions: The Bangladeshi health sector decision-makers should learn from their mistakes to prevent further unnecessary loss of life and long-term economic downturn. They should adopt a science-based response to the COVID-19 pandemic in the short term while striving to develop a more resilient health system in the long run.

Dengue risk assessment using multicriteria decision analysis: A case study of Bhutan

Background

Dengue is the most rapidly spreading vector-borne disease globally, with a 30-fold increase in global incidence over the last 50 years. In Bhutan, dengue incidence has been on the rise since 2004, with numerous outbreaks reported across the country. The aim of this study was to identify and map areas that are vulnerable to dengue in Bhutan.

Methodology/Principal findings

We conducted a multicriteria decision analysis (MCDA) using a weighted linear combination (WLC) to obtain a vulnerability map of dengue. Risk factors (criteria) were identified and assigned with membership values for vulnerability according to the available literature. Sensitivity analysis and validation of the model was conducted to improve the robustness and predictive ability of the map. Our study revealed marked differences in geographical vulnerability to dengue by location and season. Low-lying areas and those located along the southern border were consistently found to be at higher risk of dengue. The vulnerability extended to higher elevation areas including some areas in the Capital city Thimphu during the summer season. The higher risk was mostly associated with relatively high population density, agricultural and built-up landscapes and relatively good road connectivity.

Conclusions

Using MCDA, our study identified vulnerable areas in Bhutan during specific seasons when and where the transmission of dengue is most likely to occur. This study provides evidence for the National Vector-borne Disease Control programme to optimize the use of limited public health resources for surveillance and vector control, to mitigate the public health threat of dengue.

Dengue is an important vector-borne viral disease affecting humans. In Bhutan, dengue incidence is on the rise with increased frequency of outbreaks and spread to new areas. Outbreaks were reported from places as high as above 900m above sea level in recent years. However, dengue control activities in Bhutan are usually initiated at the time of outbreaks. This often leads to a large number of cases and overburden the health system. To address these issues, we developed dengue risk maps at a fine spatial resolution by combining risk factors that mediate the transmission of dengue using a weighted linear combination. Vulnerability to dengue was spatially heterogeneous and varied by season. Dengue is highly vulnerable in low-lying areas throughout the season. However, the vulnerability extended to higher geographical elevations including the nation’s capital during the summer season. The study provides a firm evidence-base to prioritize areas and seasons for dengue control strategies in Bhutan.

A Novel Multiplex RT-PCR Assay for Simultaneous Detection of Dengue and Chikungunya Viruses

The goal of the study was to develop a specific, sensitive, and cost-effective molecular RT-PCR diagnostic assay for the rapid and simultaneous detection of the serotypes of dengue virus (DENV) and Chikungunya virus (CHIKV) from sera of suspected febrile patients. A single-tube, single-step multiplex RT-PCR (mRT-PCR) assay was designed for the detection of viral genomes from clinical and field samples. Specificity and sensitivity of the mRT-PCR assay were evaluated against six different combinations using two reverse transcriptases (AMV-RT and RT-Ace) and three DNA polymerases (LA-Taq, rTaq, and Tth). Among the six combinations, the AMV-RT and LA-Taq combination was more specific and sensitive than other enzyme combinations for detecting viral genomes of DENV-1, DENV-2, DENV-3, and DENV-4 (p < 0.01), and for detecting viral genomes of CHIKV (p < 0.05). The detection limits of the mRT-PCR were 10 focus forming units (FFU) for CHIKV and 1 FFU, 20 FFU, 0.1 FFU, and 10 FFU for DENV-1, DENV-2, DENV-3, and DENV-4, respectively. The primers used for the mRT-PCR did not show any cross-reactivity among the serotypes of DENV or CHIKV. Specificity and sensitivity of the newly developed mRT-PCR were validated using serum samples collected from febrile patients during dengue outbreaks in Bangladesh. The sensitivity for serotype detection of DENV and CHIKV was superior to the virus isolation method and the antigen detection method using the Dengue NS1-Ag assay. This novel mRT-PCR method can be used for molecular epidemiological surveillance of DENV and CHIKV in epidemic and endemic countries.

Hypothetical assessment of efficiency, willingness-to-accept and willingness-to-pay for dengue vaccine and treatment: a contingent valuation survey in Bangladesh

In 2019, Bangladesh has grappled with a record-breaking surge in dengue fever, experiencing the highest number of dengue cases since the year 2000. Together, the intensification of dengue fever combined with a lack of dengue vaccines and appropriate medicines is expected to further the public and government's interests in appropriate and potential dengue vaccines to control the epidemic. We considered people's characteristics, dengue experience, and knowledge to assess their willingness-to-accept (WTA) and willingness-to-pay (WTP) for a hypothetical dengue vaccine and ex-post treatment in Bangladesh (June-July 2019). This study implemented a contingent valuation (CV) method with 3,251 respondents in 10 different locations of Bangladesh. All respondents participated in a hypothetical dengue vaccine scenario consisting of 65% (vaccine A), 80% (vaccine B), and 95% (vaccine C) effectiveness levels with three doses of each vaccine and ex-post dengue treatment. Around 71.2% of respondents were willing to pay for at least one of the hypothetical vaccines: A, B, or C. The average WTPs of the three vaccines amounted to US$ 47.0, US$ 66.0, and US$ 89.0, which were defined as the total cost of the doses necessary to obtain immunity. In Bangladesh, there is a significant demand for low-priced dengue vaccines, which was proven by people's higher acceptance of vaccination practices. Though dengue vaccines are not yet available in Bangladesh, this study provides significant support that both the government and private sectors should work together to develop a reliable and affordable dengue vaccine.

The east coast districts are the possible epicenter of severe dengue in Sabah

BACKGROUND

Malaysia recorded the highest number of dengue cases between 2014 and 2017. There are 13 states and three federal territories in Malaysia, and each area varies in their prevalence of dengue. Sabah is one of the states situated in Borneo, Malaysia. Although dengue has been increasing for the last several years, no study was being done to understand the burden and serotype distribution of the dengue virus (DENV) in Sabah. Therefore, the present study was carried out to understand the epidemiology of the dengue infection and the factors responsible for severe dengue in Sabah.

METHODS

Data on dengue infection were extracted from the dengue database of the state of Sabah from 2013 through 2018. DENV NS-1-positive serum samples from multiple sites throughout Sabah were sent to the state public health laboratory, Kota Kinabalu Public Health Laboratory, for serotype determination. The analysis of factors associated with severe dengue was determined from the data of 2018 only.

RESULTS

In 2013, there were 724 dengue cases; however, from 2014, dengue cases increased exponentially and resulted in 3423 cases in 2018. Increasing dengue cases also led to increased dengue mortality. The number of dengue deaths in 2013 was only five which then gradually increased, and in 2018, 29 patients died. This is an increase of 580% from 2013 to 2018. Deaths were considerably more in the districts of the east coast of Sabah compared with districts in the west coast. During the study period, all DENV serotypes could be identified as serotypes circulating in Sabah. In 2018, the predominant serotype was DENV-3. The monthly peak of dengue infection varied in different years. In the logistic regression analysis, it was identified that children were 6.5 times, patients infected with mixed serotype of DENV were 13 times, and cases from the districts of the east coast were 5.2 times more likely to develop severe dengue.

CONCLUSIONS

An increasing trend of dengue infection has been observed in Sabah. The burden of dengue, severe dengue, and mortality was noted especially in the districts of the east coast of Sabah. Severe dengue was most likely developed in children, cases from the east coast, and patients infected with mixed serotype of DENV.

Reemergence of dengue virus in Bangladesh: Current fatality and the required knowledge

The current fatality of dengue among the Bangladeshi population has drawn the interest of the public health professionals primarily to focus on the environmental, social, and clinical reasoning as well the possible remedies. This year, in 2019, the dengue situation in Bangladesh has appeared with all its dreadful effects leading to the highest death cases due to dengue virus (DENV) infection. According to the Directorate General of Health Services report, this year (2019) the number of DENV-infected people has appeared to be around five times higher (approximately 50,000 cases so far) compared with the last year, 2018 (around 10,000 cases). The present review discussed the current epidemics of dengue infection in Bangladesh as well the possible means of disease curing in terms of general preventive concepts. However, besides the precise treatment of the dengue-affected patients, the knowledge on DENV genome and on the protective immunity against such reemerging disease is essential.

Mapping the emerging burden of dengue

The first nationally-representative survey of dengue has revealed the growing burden of the disease in Bangladesh.