The emergence of dengue in Bangladesh: epidemiology, challenges and future disease risk

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.

Underreporting of Cases in the COVID-19 Outbreak of Borriana (Spain) during Mass Gathering Events in March 2020: A Cross-Sectional Study

Determining the number of cases of an epidemic is the first function of epidemiological surveillance. An important underreporting of cases was observed in many locations during the first wave of the COVID-19 pandemic. To estimate this underreporting in the COVID-19 outbreak of Borriana (Valencia Community, Spain) in March 2020, a cross-sectional study was performed in June 2020 querying the public health register. Logistic regression models were used. Of a total of 468 symptomatic COVID-19 cases diagnosed in the outbreak through anti-SARS-CoV-2 serology, 36 cases were reported (7.7%), resulting in an underreporting proportion of 92.3% (95% confidence interval [CI], 89.5-94.6%), with 13 unreported cases for every reported case. Only positive SARS-CoV-2 polymerase chain reaction cases were predominantly reported due to a limited testing capacity and following a national protocol. Significant factors associated with underreporting included no medical assistance for COVID-19 disease, with an adjusted odds ratio [aOR] of 10.83 (95% CI 2.49-47.11); no chronic illness, aOR = 2.81 (95% CI 1.28-6.17); middle and lower social classes, aOR = 3.12 (95% CI 1.42-6.85); younger age, aOR = 0.97 (95% CI 0.94-0.99); and a shorter duration of illness, aOR = 0.98 (95% CI 0.97-0.99). To improve the surveillance of future epidemics, new approaches are recommended.

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.

A perspective on the worst ever dengue outbreak 2023 in Bangladesh: What makes this old enemy so deadly, and how can we combat it?

Background and Aims

Bangladesh has been going through outbreaks of dengue fever cases every year since 2000. Yet this year's (2023) episode of dengue fever has crossed every line concerning fatality. Symptoms of the fever range from high fever, headaches, and muscle aches to deadly dengue hemorrhagic fever (DHF). The present review aims to assess the current pathogenicity and associated risk factors of recent dengue outbreaks in Bangladesh.

Methods

To perform this review work, we extracted relevant information from published articles available in PubMed, Scopus, and Google Scholar. We used dengue virus, dengue fever, and dengue outbreaks as keywords while searching for information.

Results

This Aedes mosquito-transmitted viral fever is more common in Bangladesh because of the tropical nature and immense burden of populations, resulting in convenient conditions for the reproduction of the vector. The rapid genetic transformation of this RNA virus and the resistance of its vector against insecticides have intensified the situation. The number of hospitalized patients has increased, and the case fatality rate has risen to 0.47%. Inadequate mosquito control measures, plenty of vector breeding sites, and a lack of public awareness have worsened the situation. Routine spraying of effective insecticides in high-risk zones, regular inspection of potential mosquito breeding sites, and public awareness campaigns are the keys to limiting the spread of this virus. Also, the availability of detection kits, improved hospital settings, and trained health professionals are mandatory to keep disease fatalities under control.

Conclusion

Dengue fever is a preventable disease. The successful development of a competent vaccine is now a prime need for preventing any future upsurge of the disease. Also, we recommend public awareness, vector control activities, and global collaboration to prevent spread.

Bamboo stumps that are artificially in use put pressure on dengue and chikungunya vector control in Dhaka city, Bangladesh

BACKGROUND OBJECTIVES

Aedes aegypti and Ae. albopictus mosquitoes breed in natural and artificial containers, and they transmit dengue and chikungunya. A study was conducted to identify the contribution of bamboo stumps to these disease vectors that were used in the flower garden as pillars to hold the bamboo flex fence.

METHODS

Two sizes of whole bamboo were used to hold fences around gardens at Dhaka University, Bangladesh, and were painted red and green. Mosquito larvae and pupae were collected from bamboo stumps between July and August, and vectors were identified up to the species level. The data were analyzed using the STATA/MP 14.2 version.

RESULTS

83.5% and 0.2% were Ae. albopictus and Ae. aegypti, respectively, and the remaining were Culex and Ar-migeres species. Ae. albopictus, Ae. aegypti, and both species-positive bamboo stumps were 46.9, 0.7, and 47.1%, respectively. 54.5% of the bamboo stumps had at least one mosquito species. The average stump depth for Aedes positive stumps (mean=11.7 cm, SE = 0.5) was significantly (p <0.001) higher than the Aedes negative stumps (mean = 9.5 cm, SE = 0.4). 53.8% and 38.0% stumps were found Aedes positive on the ground and upper sides of fences, respectively, and found significant (p<0.01) differences between both sides. A zero-inflated negative binomial count model is significant at a 5% level of significance, χ2(4) = 11.8, p = 0.019 (<0.05) for Ae. albopictus. Stump depth is found to have a significant positive effect on the number of Aedes-positive stumps.

INTERPRETATION CONCLUSION

Artificially used natural containers are adding pressure to current mosquito control activities as mosquitoes are breeding on them, which needs additional attention.

The Epidemiologic and Clinical Characteristics of the 2023 Dengue Outbreak in Bangladesh

The ongoing 2023 dengue outbreak is the worst ever case reported in Bangladesh. There is a lack of epidemiological studies on the outbreak. A 2-tailed t test was performed. Multivariable logistic regression analysis was conducted. We found about 277 801 cases and 1393 deaths from the 2023 dengue outbreak. About 52% of the cases were from outside of Dhaka. The male:female ratio was about 3:2. The highest frequency of cases was found among people aged 19-29 years (28.7%, 79 673 of 277 801; P = .001). The overall case fatality rate (CFR) was 0.5%. The highest CFR was found among children aged 0-10 years (12%). Fever (99%) was the most prevalent, followed by joint pain (86%). We found significantly higher odds of fatalities (adjusted odds ratio [aOR], 4.21; 95% CI, 3.93-4.74; P = .05), cases (aOR, 3.85; 95% CI, 3.25-4.12; P = .001) and hospitalizations (aOR, 3.26; 95% CI, 3.11-4.04; P = .006) during the 2023 outbreak compared with previous outbreaks during 2008-2022. This is one of the early reports of epidemiological and clinical characteristics of ongoing dengue outbreak.

Understanding the spread of infectious diseases in edge areas of hotspots: dengue epidemics in tropical metropolitan regions

Identifying clusters or hotspots from disease maps is critical in research and practice. Hotspots have been shown to have a higher potential for transmission risk and may be the source of infections, making them a priority for controlling epidemics. However, the role of edge areas of hotspots in disease transmission remains unclear. This study aims to investigate the role of edge areas in disease transmission by examining whether disease incidence rate growth is higher in the edges of disease hotspots during outbreaks. Our data is based on the three most severe dengue epidemic years in Kaohsiung city, Taiwan, from 1998 to 2020. We employed conditional autoregressive (CAR) models and Bayesian areal Wombling methods to identify significant edge areas of hotspots based on the extent of risk difference between adjacent areas. The difference-in-difference (DID) estimator in spatial panel models measures the growth rate of risk by comparing the incidence rate between two groups (hotspots and edge areas) over two time periods. Our results show that in years characterized by exceptionally large-scale outbreaks, the edge areas of hotspots have a more significant increase in disease risk than hotspots, leading to a higher risk of disease transmission and potential disease foci. This finding explains the geographic diffusion mechanism of epidemics, a pattern mixed with expansion and relocation, indicating that the edge areas play an essential role. The study highlights the importance of considering edge areas of hotspots in disease transmission. Furthermore, it provides valuable insights for policymakers and health authorities in designing effective interventions to control large-scale disease outbreaks.

Public knowledge, belief, and preventive practices regarding dengue: Findings from a community-based survey in rural Bangladesh

BACKGROUND

Dengue fever, the most prevalent mosquito-borne viral infection, is a recurrent public health threat in Bangladesh. Despite the government's efforts, dengue outbreaks are on the upswing, and people's knowledge, belief, and preventive practices regarding the disease at the rural community level are unclear.

OBJECTIVE

The objective of this study was to assess the level of knowledge, belief and preventive practices regarding dengue and associated factors among community people from rural Bangladesh.

METHODS

A cross-sectional survey was conducted involving 401 people using a convenient sampling technique from three unions of Savar from August to September 2021. Participants' responses were collected through face-to-face interviews using a pre-tested structured questionnaire that included information related to socio-demographics, dengue-related knowledge, preventive practices, and the health belief model (HBM) constructs. Multiple linear regression analysis was performed to determine the factors associated with the knowledge and preventive practices of dengue.

RESULTS

Overall, participants (mean age = 33.47 ± 12.96 years; age range = 18-75 years) correctly answered 66.15% of the knowledge questions regarding dengue. Higher education, travel to dengue-risk regions, and self-efficacy under the HBM construct were all shown to be strongly associated with dengue knowledge. Regarding HBM constructs, about 80% of the participants perceived dengue as dangerous, but less than half (41.4%) believed themselves susceptible to dengue. Considering perceived barriers, 73.07% of the participants believed their residential area was not suitable for Aedes mosquito breeding. Nearly all (93.52%) believed they always kept their surrounding area clean as part of self-efficacy. Moreover, on average participants engaged in 53.69% of all dengue preventive practices. Being older, female, having a higher education, being a service holder, having a good quality of house structure, and perceived susceptibility as well as self-efficacy under the HBM construct were all factors in participants' dengue prevention activities. Participants' dengue preventative practices were shown to be significantly influenced by their knowledge.

CONCLUSIONS

The findings of this study found a moderate level of knowledge regarding dengue among the participants. Regarding dengue prevention, although participants scored highly in several indicators, the overall preventive practices were not satisfactory. This suggests that there is a pressing need for expanded education outreach aimed at increasing public awareness of dengue and encourage preventive practices within rural communities in Bangladesh.

Effective Preventative Measures are Essential to Lower Disease Burden From Dengue and COVID-19 Co-infection in Bangladesh

Bangladesh is widely recognized as one of the dengue prone nations, and empirical evidence has consistently demonstrated an upward trend in the severity of the disease over time. With the persistent occurrence of dengue in Bangladesh and the ongoing presence of COVID-19, which has not been fully eradicated and may persist for an uncertain period of time, there is a high probability of co-infection between these 2 illnesses. Given the circumstances, the concurrent occurrence of the COVID-19 and dengue epidemics, along with the potential co-infection, may pose an overwhelming burden on healthcare systems that are already grappling with challenges in meeting the existing demand. Due to a lack of awareness, an inadequate health infrastructure, and ineffective disease prevention initiatives, the country is now more susceptible to the threat posed by a co-infection that has been found to be associated with more severe outcomes, marked by significant morbidity and mortality. The objective of this opinion piece is to explore the gravity of co-infection in Bangladesh, as well as the potential challenges to overcome and the preventative measures that need to be implemented to address the severity. This opinion piece proposes a set of modern preventative strategies that, when integrated with conventional methods, have the potential to mitigate disease severity, avert the occurrence of co-infection between COVID-19 and dengue, and halt the co-epidemics of COVID-19 and dengue.

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.

Association of climate factors with dengue incidence in Bangladesh, Dhaka City: A count regression approach

Background

In Bangladesh, particularly in Dhaka city, dengue fever is a major factor in serious sickness and hospitalization. The weather influences the temporal and geographical spread of the vector-borne disease dengue in Dhaka. As a result, rainfall and ambient temperature are considered macro factors influencing dengue since they have a direct impact on Aedes aegypti population density, which changes seasonally dependent on these critical variables. This study aimed to clarify the relationship between climatic variables and the incidence of dengue disease.

Methods

A total of 2253 dengue and climate data were used for this study. Maximum and minimum temperature (°C), humidity (grams of water vapor per kilogram of air g.kg^-1), rainfall (mm), sunshine hour (in (average) hours per day), and wind speed (knots (kt)) in Dhaka were considered as the independent variables for this study which trigger the dengue incidence in Dhaka city, Bangladesh. Missing values were imputed using multiple imputation techniques. Descriptive and correlation analyses were performed for each variable and stationary tests were observed using Dicky Fuller test. However, initially, the Poisson model, zero-inflated regression model, and negative binomial model were fitted for this problem. Finally, the negative binomial model is considered the final model for this study based on minimum AIC values.

Results

The mean of maximum and minimum temperature, wind speed, sunshine hour, and rainfall showed some fluctuations over the years. However, a mean number of dengue cases reported a higher incidence in recent years. Maximum and minimum temperature, humidity, and wind speed were positively correlated with dengue cases. However, rainfall and sunshine hours were negatively associated with dengue cases. The findings showed that factors such as maximum temperature, minimum temperature, humidity, and windspeed are crucial in the transmission cycles of dengue disease. On the other hand, dengue cases decreased with higher levels of rainfall.

Conclusion

The findings of this study will be helpful for policymakers to develop a climate-based warning system in Bangladesh.

Simulations and fractional modeling of dengue transmission in Bangladesh

Dengue is one of the most infectious diseases in the world. In Bangladesh, dengue occurs nationally and has been endemic for more than a decade. Therefore, it is crucial that we model dengue transmission in order to better understand how the illness behaves. This paper presents and analyzes a novel fractional model for the dengue transmission utilizing the non-integer Caputo derivative (CD) and are analysed using q-homotopy analysis transform method (q-HATM). By using the next generation method, we derive the fundamental reproduction number $ R_0 $ and show the findings based on it. The global stability of the endemic equilibrium (EE) and the disease-free equilibrium (DFE) is calculated using the Lyapunov function. For the proposed fractional model, numerical simulations and dynamical attitude are seen. Moreover, A sensitivity analysis of the model is performed to determine the relative importance of the model parameters to the transmission.

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.

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.

Knowledge, Attitudes, and Practices in Relation to Mosquito-Borne Diseases in Bangladesh

Mosquito-borne diseases (MBDs) such as dengue, malaria, and chikungunya are common in Bangladesh, with frequent outbreaks in the rainy season. Analysis of the knowledge, attitudes, and practices of people toward any crisis is fundamental to addressing any gap. Here, we conducted a cross-sectional study mainly focusing on the northern, southern and central parts of Bangladesh to understand the level of knowledge, attitudes, and practices of people regarding MBDs, mosquito habitats, or control measures. A total of 1720 participants were involved in the study from 33 out of 64 districts of Bangladesh, of which 56.9% were male. While most of them knew about dengue (97.1%), chikungunya (81.4%), and malaria (85.2%), only half of them were aware of filaria (53.3%), which is endemic to the northern region. A knowledge score (0−8, low), (9−16, moderate), (17−24, high), and attitude score (0−4, poor), (5−8, moderate), and (9−13, high) were assigned. While poor and moderate attitudes were considered negative, good attitudes were considered positive. About 45% of the respondents had a moderate knowledge score (50−70); however, about 67.9% of participants showed a good attitude score (>70) towards the control of MBDs. It was found that the knowledge and attitude of the responders were related to their profession (knowledge p < 0.001; attitude, p = 0.002), residential area (knowledge p < 0.001; attitude, p < 0.001), and education level (knowledge p < 0.001; attitude p = 0.004). A mosquito is a kind of nuisance bug, and about 79.8% of responders admitted that they kill mosquitoes as soon as they notice them. They also use bed nets (93.7%) followed by mosquito coils (85.7%) as a preventive method. Interestingly, 73.2% of the responders were reluctant to contact the local government during an increase in mosquito numbers. Overall, the people of Bangladesh have a positive attitude towards the prevention of mosquito-borne diseases. It is highly recommended that the government creates more knowledge regarding this issue and develops collaborative approaches with local people to implement robust preventive measures against mosquito-borne diseases.

Forecasting the incidence of dengue in Bangladesh-Application of time series model

Background

Dengue is an alarming public health concern in terms of its preventive and curative measures among people in Bangladesh; moreover, its sudden outbreak created a lot of suffering among people in 2018. Considering the greater burden of disease in larger epidemic years and the difficulty in understanding current and future needs, it is highly needed to address early warning systems to control epidemics from the earliest.

Objective

The study objective was to select the most appropriate model for dengue incidence and using the selected model, the authors forecast the future dengue outbreak in Bangladesh.

Methods and Materials

This study considered a secondary data set of monthly dengue occurrences over the period of January 2008 to January 2020. Initially, the authors found the suitable model from Autoregressive Integrated Moving Average (ARIMA), Error, Trend, Seasonal (ETS) and Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal (TBATS) models with the help of selected model selection criteria and finally employing the selected model make forecasting of dengue incidences in Bangladesh.

Results

Among ARIMA, ETS, and TBATS models, the ARIMA model performs better than others. The Box-Jenkin's procedure is applicable here and it is found that the best-selected model to forecast the dengue outbreak in the context of Bangladesh is ARIMA (2,1,2).

Conclusion

Before establishing a comprehensive plan for future combating strategies, it is vital to understand the future scenario of dengue occurrence. With this in mind, the authors aimed to select an appropriate model that might predict dengue fever outbreaks in Bangladesh. The findings revealed that dengue fever is expected to become more frequent in the future. The authors believe that the study findings will be helpful to take early initiatives to combat future dengue outbreaks.

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.

Comparison of clinical manifestation of dengue fever in Bangladesh: an observation over a decade

BACKGROUND

The clinical presentation of dengue fever had been observed to change with time since its first outbreak in 2000 in Bangladesh. This report showed the clinical presentation of the 2019 outbreak in Bangladesh along with its comparison to previous outbreaks witnessed in this region.

METHODS

This hospital-based cross-sectional study was conducted in one of the largest tertiary care hospitals in Dhaka city. A total of 553 laboratory-confirmed and 194 probable dengue cases were interviewed. The clinical manifestation of the confirmed cases of the current outbreak was compared with three of the outbreak reports retrieved from the databases. R version 3.6.3 was used for data analysis.

RESULTS

Among the confirmed cases, two-thirds were male (63.2%) and the average age was 27(± 11) years. Positive tests for NS1 and IgM were present in 99.6% (n = 525/527) and 82.6% (n = 38/46) of the cases, respectively. Thrombocytopenia was present in 66.1% of cases. Fever (100%) was common for all. Gastrointestinal (GIT) features, including abdominal pain (86.5%), anorexia and/or vomiting (69.6%), and Diarrhea (> 3 motions/day) (26.2%) were more frequent than typical rash and other pain symptoms. Hypotension was present in approximately a quarter of patients (25%). GIT features (anorexia, nausea, and/or vomiting) and hypotension were more common among adult participants while bleeding manifestation (melena and vaginal bleeding, p = 0.009 & 0.032) was more frequent in pediatric patients. Compared to outbreaks of 2008, 2016, and 2018, increasing trends in GIT symptoms e.g. anorexia, abdominal pain, and diarrhea were observed. While a negative trend in hemorrhagic manifestations (skin rash, melena, and conjunctival hemorrhage/hemorrhagic sclera) and arthralgia/joint pain were found.

CONCLUSION

The present outbreak was noticeably characterized by GIT symptoms and hypotension in addition to the typical clinical features like rash and pain symptoms. An increasing trend in GIT features and decreasing trend in hemorrhagic manifestations was noted over the last decade of dengue outbreaks.

Climate Variability, Dengue Vector Abundance and Dengue Fever Cases in Dhaka, Bangladesh: A Time-Series Study

Numerous studies on climate change and variability have revealed that these phenomena have noticeable influence on the epidemiology of dengue fever, and such relationships are complex due to the role of the vector—the Aedes mosquitoes. By undertaking a step-by-step approach, the present study examined the effects of climatic factors on vector abundance and subsequent effects on dengue cases of Dhaka city, Bangladesh. Here, we first analyzed the time-series of Stegomyia indices for Aedes mosquitoes in relation to temperature, rainfall and relative humidity for 2002–2013, and then in relation to reported dengue cases in Dhaka. These data were analyzed at three sequential stages using the generalized linear model (GLM) and generalized additive model (GAM). Results revealed strong evidence that an increase in Aedes abundance is associated with the rise in temperature, relative humidity, and rainfall during the monsoon months, that turns into subsequent increases in dengue incidence. Further we found that (i) the mean rainfall and the lag mean rainfall were significantly related to Container Index, and (ii) the Breteau Index was significantly related to the mean relative humidity and mean rainfall. The relationships of dengue cases with Stegomyia indices and with the mean relative humidity, and the lag mean rainfall were highly significant. In examining longitudinal (2001–2013) data, we found significant evidence of time lag between mean rainfall and dengue cases.

Epidemiology and challenges of dengue surveillance in the WHO South-East Asia Region

Dengue poses a significant health and economic burden in the WHO South-East Asia Region. Approaches for control need to be aligned with current knowledge on the epidemiology of dengue in the region. Such knowledge will ensure improved targeting of interventions to reduce dengue incidence and its socioeconomic impact. This review was undertaken to describe the contemporary epidemiology of dengue and critically analyse the existing surveillance strategies in the region. Over recent decades, dengue incidence has continued to increase with geographical expansion. The region has now become hyper-endemic for multiple dengue virus serotypes/genotypes. Every epidemic cycle was associated with a change of predominant serotype/genotype and this was often associated with severe disease with intense transmission. Classical larval indices are widely used in vector surveillance and adult mosquito samplings are not implemented as a part of routine surveillance. Further, there is a lack of integration of entomological and disease surveillance systems, often leading to inaction or delays in dengue prevention and control. Disease surveillance does not capture all cases, resulting in under-reporting, and has thus failed to adequately represent the true burden of disease in the region. Possible solutions include incorporating adult mosquito sampling into routine vector surveillance, the establishment of laboratory-based sentinel surveillance, integrated vector and dengue disease surveillance and climate-based early warning systems using available technologies like mobile apps.

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.

Climate variability, socio-ecological factors and dengue transmission in tropical Queensland, Australia: A Bayesian spatial analysis

BACKGROUND

Dengue is a wide-spread mosquito-borne disease globally with a likelihood of becoming endemic in tropical Queensland, Australia. The aim of this study was to analyse the spatial variation of dengue notifications in relation to climate variability and socio-ecological factors in the tropical climate zone of Queensland, Australia.

METHODS

Data on the number of dengue cases and climate variables including minimum temperature, maximum temperature and rainfall for the period of January 1^st, 2010 to December 31^st, 2015 were obtained for each Statistical Local Area (SLA) from Queensland Health and Australian Bureau of Meteorology, respectively. Socio-ecological data including estimated resident population, percentage of Indigenous population, housing structure (specifically terrace house), socio-economic index and land use types for each SLA were obtained from Australian Bureau of Statistics, and Australian Bureau of Agricultural and Resource Economics and Sciences, respectively. To quantify the relationship between dengue, climate and socio-ecological factors, multivariate Poisson regression models in a Bayesian framework were developed with a conditional autoregressive prior structure. Posterior parameters were estimated using Bayesian Markov Chain Monte Carlo simulation with Gibbs sampling.

RESULTS

In the tropical climate zone of Queensland, the estimated number of dengue cases was predicted to increase by 85% [95% Credible Interval (CrI): 25%, 186%] and 7% (95% CrI: 0.1%, 14%) for a 1-mm increase in average annual rainfall and 1% increase in the proportion of terrace houses, respectively. The estimated spatial variation (structured random effects) was small compared to the remaining unstructured variation, suggesting that the inclusion of covariates resulted in no residual spatial autocorrelation in dengue data.

CONCLUSIONS

Climate and socio-ecological factors explained much of the heterogeneity of dengue transmission dynamics in the tropical climate zone of Queensland. Results will help to further understand the risk factors of dengue transmission and will provide scientific evidence in designing effective local dengue control programs in the most needed areas.

Dengue in Dhaka, Bangladesh: Hospital-based cross-sectional KAP assessment at Dhaka North and Dhaka South City Corporation area

Dengue, the most important mosquito-borne viral disease of humans is a recurring global health problem. In Bangladesh, dengue outbreaks are on the increase despite the efforts of government and it is not clear what the understanding of the general Dhaka population towards dengue fever is. Knowledge, attitude and practice (KAP) studies are essential guides in public health interventions. Hence, using KAP, this study aims to assess patient-perspectives with regards to factors associated with dengue, as well as investigate the associated factors between the two corporations in Dhaka. A Hospital-based cross-sectional study of 242 fever patients from two city-corporations in Dhaka (Dhaka North City Corporations, DNCC (n = 91, 37.6%) and Dhaka South City Corporation, DSCC (n = 151, 62.4%) was conducted using pre-tested KAP items. Wilcoxon's Rank Sum was used to determine the KAP by DNCC, DSCC and both corporations and multivariate Poisson regression analyses. The two corporations were analysed separately due to the differences in income distribution, concentration of slums, hospitals and clinics. The study found that more than half of the study population were knowledgeable about dengue (mean percentage scores was 52%), possess an appropriate and acceptable attitude towards the disease (69.2%), and about two thirds of the respondents (71.4%) engaged in practices towards its prevention. After adjusting for the potential cofounders, the factors associated with KAP about dengue fever varied between DNCC and DSCC; with duration of residency and use of mosquito nets were associated with knowledge in the north while income class and age were associated with knowledge and attitude in the south. In the pooled analysis (combining both corporations), knowledge of dengue was associated with good practice towards dengue fever among the respondents. The duration of residence in Dhaka (10+ years), not using mosquito nets and length of time spent in the hospital (7+ days) due to dengue, and decreased knowledge (Adjusted coefficient (β) = -0.01, 95%CI: -0.02, -0.01) were associated with attitude towards dengue in DNCC. On the other hand, middle-high income class, age (40+ years) and increased knowledge were associated with practice towards dengue in DSCC (β = 0.02, 95%CI: 0.01, 0.03). Efforts to increase knowledge about dengue fever through education by the administrations of both corporations would benefit from targeting these high-risk groups for a more sustainable outcome.

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.

Megacities as drivers of national outbreaks: The 2017 chikungunya outbreak in Dhaka, Bangladesh

BACKGROUND

Several large outbreaks of chikungunya have been reported in the Indian Ocean region in the last decade. In 2017, an outbreak occurred in Dhaka, Bangladesh, one of the largest and densest megacities in the world. Population mobility and fluctuations in population density are important drivers of epidemics. Measuring population mobility during outbreaks is challenging but is a particularly important goal in the context of rapidly growing and highly connected cities in low- and middle-income countries, which can act to amplify and spread local epidemics nationally and internationally.

METHODS

We first describe the epidemiology of the 2017 chikungunya outbreak in Dhaka and estimate incidence using a mechanistic model of chikungunya transmission parametrized with epidemiological data from a household survey. We combine the modeled dynamics of chikungunya in Dhaka, with mobility estimates derived from mobile phone data for over 4 million subscribers, to understand the role of population mobility on the spatial spread of chikungunya within and outside Dhaka during the 2017 outbreak.

RESULTS

We estimate a much higher incidence of chikungunya in Dhaka than suggested by official case counts. Vector abundance, local demographics, and population mobility were associated with spatial heterogeneities in incidence in Dhaka. The peak of the outbreak in Dhaka coincided with the annual Eid holidays, during which large numbers of people traveled from Dhaka to other parts of the country. We show that travel during Eid likely resulted in the spread of the infection to the rest of the country.

CONCLUSIONS

Our results highlight the impact of large-scale population movements, for example during holidays, on the spread of infectious diseases. These dynamics are difficult to capture using traditional approaches, and we compare our results to a standard diffusion model, to highlight the value of real-time data from mobile phones for outbreak analysis, forecasting, and surveillance.

Risk Assessment of Dengue Transmission in Bangladesh Using a Spatiotemporal Network Model and Climate Data

Vector-borne disease risk assessment is crucial to optimize surveillance, preventative measures (vector control), and resource allocation (medical supplies). High arthropod abundance and host interaction strongly correlate to vector-borne pathogen transmission. Increasing host density and movement increases the possibility of local and long-distance pathogen transmission. Therefore, we developed a risk-assessment framework using climate (average temperature and rainfall) and host demographic (host density and movement) data, particularly suitable for regions with unreported or underreported incidence data. This framework consisted of a spatiotemporal network-based approach coupled with a compartmental disease model and nonhomogeneous Gillespie algorithm. The correlation of climate data with vector abundance and host–vector interactions is expressed as vectorial capacity—a parameter that governs the spreading of infection from an infected host to a susceptible one via vectors. As an example, the framework is applied for dengue in Bangladesh. Vectorial capacity is inferred for each week throughout a year using average monthly temperature and rainfall data. Long-distance pathogen transmission is expressed with human movement data in the spatiotemporal network. We have identified the spatiotemporal suitability of dengue spreading in Bangladesh as well as the significant-incidence window and peak-incidence period. Analysis of yearly dengue data variation suggests the possibility of a significant outbreak with a new serotype introduction. The outcome of the framework comprised spatiotemporal suitability maps and probabilistic risk maps for spatial infection spreading. This framework is capable of vector-borne disease risk assessment without historical incidence data and can be a useful tool for preparedness with accurate human movement data.

Dengue outbreaks in Bangladesh: Historic epidemic patterns suggest earlier mosquito control intervention in the transmission season could reduce the monthly growth factor and extent of epidemics

Dengue is endemic in Bangladesh and is an important cause of morbidity and mortality. Suppressing the mosquito vector activity at the optimal time annually is a practical strategy to control dengue outbreaks. The objective of this study was to estimate the monthly growth factor (GF) of dengue cases over the past 12 years as a means to identify the optimal time for a vector-control programme in Bangladesh. We reviewed the monthly cases reported by the Institute of Epidemiology, Disease Control and Research of Bangladesh during the period of January 2008–December 2019. We calculated the GF of dengue cases between successive months during this period and report means and 95% confidence intervals (CI). The median number of patients admitted to the hospital with dengue fever per year was 1554 (range: 375–101,354). The mean monthly GF of dengue cases was 1.2 (95% CI: 0.4–2.4). The monthly GF lower CI between April and July was > 1, whereas from September to November and January the upper CI was <1. The highest GF of dengue was recorded in June (mean: 2.4; 95% CI: 1.7–3.5) and lowest in October (mean: 0.43; 95% CI: 0.24–0.73). More than 81% (39/48) months between April and July for the period 2008–2019 had monthly GF > 1 compared to 20% (19/96) months between August and March of the same period. The monthly GF was significantly correlated with monthly rainfall (r = 0.39) and monthly mean temperature (r = 0.30). The growth factor of the dengue cases over the last 12 years appeared to follow a marked periodicity linked to regional rainfall patterns. The increased transmission rate during the months of April–July, a seasonally determined peak suggests the need for strengthening a range of public health interventions, including targeted vector control efforts and community education campaigns.

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The monthly reported dengue cases from January 2008 to December 2019 were analysed to estimate monthly growth factor.

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The monthly growth factor lower 95% confidence interval between April and July was > 1.

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More than 81% (39/48) months between April and July of the period 2008–2019 had monthly GF > 1.

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Only 20% (19/96) of the months between August and March of the period 2008–2019 had monthly GF > 1.

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Controlling the mosquitoes earlier might be more efficient in limiting the dengue outbreaks in Bangladesh.

An Association between Rainy Days with Clinical Dengue Fever in Dhaka, Bangladesh: Findings from a Hospital Based Study

Background: Dengue, a febrile illness, is caused by a Flavivirus transmitted by Aedes aegypti and Aedes albopictus mosquitoes. Climate influences the ecology of the vectors. We aimed to identify the influence of climatic variability on the occurrence of clinical dengue requiring hospitalization in Zone-5, a high incidence area of Dhaka City Corporation (DCC), Bangladesh. Methods and Findings: We retrospectively identified clinical dengue cases hospitalized from Zone-5 of DCC between 2005 and 2009. We extracted records of the four major catchment hospitals of the study area. The Bangladesh Meteorological Department (BMD) provided data on temperature, rainfall, and humidity of DCC for the study period. We used autoregressive integrated moving average (ARIMA) models for the number of monthly dengue hospitalizations. We also modeled all the climatic variables using Poisson regression. During our study period, dengue occurred throughout the year in Zone-5 of DCC. The median number of hospitalized dengue cases was 9 per month. Dengue incidence increased sharply from June, and reached its peak in August. One additional rainy day per month increased dengue cases in the succeeding month by 6% (RR = 1.06, 95% CI: 1.04–1.09). Conclusions: Dengue is transmitted throughout the year in Zone-5 of DCC, with seasonal variation in incidence. The number of rainy days per month is significantly associated with dengue incidence in the subsequent month. Our study suggests the initiation of campaigns in DCC for controlling dengue and other Aedes mosquito borne diseases, including Chikunguniya from the month of May each year. BMD rainfall data may be used to determine campaign timing.

Insecticide resistance status of Aedes aegypti in Bangladesh

Background

Arboviral diseases, including dengue and chikungunya, are major public health concerns in Bangladesh where there have been unprecedented levels of transmission reported in recent years. The primary approach to control these diseases is to control the vector Aedes aegypti using pyrethroid insecticides. Although chemical control has long been practiced, no comprehensive analysis of Ae. aegypti susceptibility to insecticides has been conducted to date. The aim of this study was to determine the insecticide resistance status of Ae. aegypti in Bangladesh and investigate the role of detoxification enzymes and altered target site sensitivity as resistance mechanisms.

Methods

Eggs of Aedes mosquitoes were collected using ovitraps from five districts across Bangladesh and in eight neighborhoods of the capital city Dhaka, from August to November 2017. CDC bottle bioassays were conducted for permethrin, deltamethrin, malathion, and bendiocarb using 3- to 5-day-old F₀–F₂ non-blood-fed female mosquitoes. Biochemical assays were conducted to detect metabolic resistance mechanisms, and real-time PCR was performed to determine the frequencies of the knockdown resistance (kdr) mutations Gly1016, Cys1534, and Leu410.

Results

High levels of resistance to permethrin were detected in all Ae. aegypti populations, with mortality ranging from 0 to 14.8% at the diagnostic dose. Substantial resistance continued to be detected against higher (2×) doses of permethrin (5.1–44.4% mortality). Susceptibility to deltamethrin and malathion varied between populations while complete susceptibility to bendiocarb was observed in all populations. Significantly higher levels of esterase and oxidase activity were detected in most of the test populations as compared to the susceptible reference Rockefeller strain. A significant association was detected between permethrin resistance and the presence of Gly1016 and Cys1534 homozygotes. The frequency of kdr (knockdown resistance) alleles varied across the Dhaka Aedes populations. Leu410 was not detected in any of the tested populations.

Conclusions

The detection of widespread pyrethroid resistance and multiple resistance mechanisms highlights the urgency for implementing alternate Ae. aegypti control strategies. In addition, implementing routine monitoring of insecticide resistance in Ae. aegypti in Bangladesh will lead to a greater understanding of susceptibility trends over space and time, thereby enabling the development of improved control strategies.

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.

Zika virus: A possible emerging threat for Bangladesh!

Zika virus, a member of Flaviviridae is the etiology of Zika or Zika fever or Zika virus (ZIKV) disease characterized by mild symptoms similar to very mild form of Dengue or Chikungunya. The virus transmits through Aedes mosquitoes, particularly by Aedes aegypti. The most dangerous effect of ZIKV infection is the ability of the virus to cause microcephaly and congenital malformation to the newborn baby if the mother is infected. The neurological disorders including Guillain-Barré syndrome might be associated with adults and children due to ZIKV infections. Zika has emerged as a serious global public health problem as it has been found in 87 countries, particularly in Africa, America, and Asia and has no vaccine and treatment so far. Bangladesh is at a high risk of ZIKV infection and we consider ZIKV as a possible emerging threat for Bangladesh. This short review summarizes the insights of ZIKV infection, present status of the disease in Bangladesh and its neighboring countries, and recommendations for necessary preparations and strategies to be taken for effective controlling of the ZIKV infection in Bangladesh before getting any havoc.

Risk factors for dengue outbreaks in Odisha, India: A case-control study

BACKGROUND

Environmental and climatic risk factors of dengue outbreak has been studied in detail. However, the socio-epidemiological association with the disease is least explored. The study aims to identify the social and ecological factors associated with emerging dengue in Odisha, India.

METHODS

A population-based case-control study (age and sex matched at the ratio of 1:1) was conducted in six districts of the state in 2017. A structured validated questionnaire was used to collect information for each consenting participant. An ecological household survey was done using a checklist during the month of July-September. Along with the descriptive statistics, conditional logistic regression model was used to calculate the adjusted odds ratio using STATA.

RESULTS

Of 380 cases, nearly 55% were male and the median age was 33years. The adjusted odds of having dengue was nearly three times higher among the people having occupation which demands long travel, presence of breeding sites (1.7; 95% CI 1.2-2.6), presence of swampy area near home (1.5; 95% CI 1.1-2.1) and having travel history close to the index date (1.6; 95% CI 1.1-2.4). People staying in thatched houses had three times higher risk of the disease, however, households keeping the swampy areas clean had 50% less risk for the disease (0.5; 95% CI 0.31-0.67). Nearly 22.2% of cases had a travel history during the index date. Of them, 36% had diagnosis before the travel, whereas, 64% developed the disease after the returning from the travel.

CONCLUSION

Household factors such as occupation and ecological condition of households play important roles in dengue outbreaks in Odisha. However, our study suggests travel/commuting are also essential factors to be considered during disease prevention planning.

Role of container type, behavioural, and ecological factors in Aedes pupal production in Dhaka, Bangladesh: An application of zero-inflated negative binomial model

The container-inhabiting Aedes mosquitoes are the major vectors transmitting dengue and several other arboviral diseases such as chikungunya and zika across the tropical world. Surveillance for immature Aedes, particularly pupae, is an effective tool for measuring dengue outbreak risk. While in Bangladesh, the greatest burden of dengue fever and dengue hemorrhagic fever cases has periodically been occurring since the first major outbreak in 2000, very limited research has yet been pursued to understand the dynamics of Aedes pupal production in this country. In this backdrop, this study was carried out to i) identify containers at household premises contributing to dengue vector productivity; ii) measure the extent of pupae productivity of household containers; and, iii) determine the effects of household ecological factors upon productivity of pupae in the city of Dhaka, Bangladesh. During the monsoon months of 2013, a total of 1,033 containers (674 wet and 363 dry) in 727 household premises in 12 wards of the city of Dhaka were inspected to measure container productivity and collect household ecological, and human behavioural data. The results reveal that the majority of immature mosquitoes (73.52% larvae and 84.91% pupae) developed in containers located outdoor that are used mostly for household chores. Plastic containers (57.55% of all immature mosquito-positive containers) used for household chores produce most of the immature mosquitos. The results of the zero-inflated negative binomial (ZINB) model reveal that pupae production significantly varies by container type (p-value = 0.0136) for the count regression group. However, when considering container size along with container type, container size is found significant for pupae production (p-value = 0.0041), showing that container size is confounded with the container type and the pupae production. Containers greater than 50 litres (L) are likely to produce 4.9 times more pupae than containers with <1L. Two household ecological factors are found to be significant (shade: p-value = 0.005 in the count regression group and type of water: p-value = 0.001 in the excess zero group) for pupae production. We found that containers with partial shade produce 4.6 times more pupae than without any shade, whereas in the excess zero group the expected number of observed zero pupae count is 86.5% lower in containers filled with rain water than those with tap water, tube-well water, ring well water and water from other sources. The most commonly used plastic-made containers (i.e., refrigerator trays, drums, buckets) and flower tubs/trays are the most abundant immature mosquito-positive containers. These findings would help the concerned authorities to formulate programs for changing human behaviour targeting the most productive containers for Aedes habitat management and vector control in the city of Dhaka, Bangladesh.

Nationally-representative serostudy of dengue in Bangladesh allows generalizable disease burden estimates

Serostudies are needed to answer generalizable questions on disease risk. However, recruitment is usually biased by age or location. We present a nationally-representative study for dengue from 70 communities in Bangladesh. We collected data on risk factors, trapped mosquitoes and tested serum for IgG. Out of 5866 individuals, 24% had evidence of historic infection, ranging from 3% in the north to >80% in Dhaka. Being male (aOR:1.8, [95%CI:1.5–2.0]) and recent travel (aOR:1.3, [1.1–1.8]) were linked to seropositivity. We estimate that 40 million [34.3–47.2] people have been infected nationally, with 2.4 million ([1.3–4.5]) annual infections. Had we visited only 20 communities, seropositivity estimates would have ranged from 13% to 37%, highlighting the lack of representativeness generated by small numbers of communities. Our findings have implications for both the design of serosurveys and tackling dengue in Bangladesh.

Dengue is a mosquito-borne virus that infects millions of people each year. Often the countries most affected by the virus, such as Bangladesh, do not have the resources needed to tackle the disease. For resources sent to these countries to have the greatest impact, it is important to know which areas are most affected, and which subsets of the population are most at risk. A way to gather this information is to test for dengue virus antibodies a protein produced by the immune system in response to the infection in the blood of individuals. However, previous efforts to use these tests to understand dengue risk in communities have generally only been done in single locations, typically a major city, and the findings of these tests are unlikely to be applicable to the wider population.

Now, Salje et al. have visited 70 different communities from all around Bangladesh and used these tests on blood samples collected from over 5,000 individuals from a range of age-groups. From these measurements it was estimated that an average 2.4 million people are infected with dengue each year in Bangladesh, with major cities, such as Dhaka, experiencing more concentrated levels. The exposure to dengue outside major cities was much lower, and men, who tend to travel more, were found to be at greater risk of infection.

Salje et al. also showed that using a small number of communities to estimate national levels of infection led to misleading results. This highlights the danger of using information collected from a limited number of places to represent the effects of a disease on the wider population.

Public health agencies in Bangladesh will be able to use this information to tackle dengue more effectively, focusing on the areas and the populations most affected by the disease. In addition, the design and analytical approaches used in this study could be applied to other countries, and to different diseases.

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

The escalating dengue situation in Bangladesh has been emerging as a serious public health problem in terms of morbidity and mortality. Results of analysis of 40,476 cases of Bangladesh occurring during 2000-2017 indicated that 49.73% of the dengue cases occurred during the monsoon season (May-August) and 49.22% during the post-monsoon season (September-December). However, data also showed that, since 2014, these trends have been changing, and dengue cases have been reported during the pre-monsoon season. During 2015-2017, in the pre-monsoon season, the dengue cases were reported to be more than seven times higher compared to the previous 14 years. The findings closely correlate with those of the pre-monsoon Aedes vector survey which revealed the presence of high density of larva and pupa of the dengue vectors in the environment all the year round. In our study, climate changes, such as average rainfall, humidity, and temperature, after 2014, and rapid unplanned urbanization were the strong predictors of an imbalance in the existing ecology that has led to increase in dengue cases in 2016 and the emergence of the chikungunya virus for the first time in Bangladesh in 2017. Although 2018 dengue data are relevant but not included in this study due to study time frame, it is interesting to report an increase in the number of dengue cases in pre (2016) and post (2018, which is highest within 18 years) chikungunya outbreak, which favors the study hypothesis. Despite the efforts to control dengue, based primarily on the vector control and case management, the burden and costs of the disease and similar vector-borne diseases will continue to grow in future in our country. Developing a cost-effective vaccine against all the 4 strains of dengue remains a challenge. The CDC, in collaboration with other research organizations, may come forward to initiate and coordinate a large-scale randomized clinical trial of an effective dengue vaccine in Bangladesh.

Geostatistical mapping of the seasonal spread of under-reported dengue cases in Bangladesh

Geographical mapping of dengue in resource-limited settings is crucial for targeting control interventions but is challenging due to the problem of zero-inflation because many cases are not reported. We developed a negative binomial generalised linear mixed effect model accounting for zero-inflation, spatial, and temporal random effects to investigate the spatial variation in monthly dengue cases in Bangladesh. The model was fitted to the district-level (64 districts) monthly reported dengue cases aggregated over the period 2000 to 2009 and Bayesian inference was performed using the integrated nested Laplace approximation. We found that mean monthly temperature and its interaction with mean monthly diurnal temperature range, lagged by two months were significantly associated with dengue incidence. Mean monthly rainfall at two months lag was positively associated with dengue incidence. Densely populated districts and districts bordering India or Myanmar had higher incidence than others. The model estimated that 92% of the annual dengue cases occurred between August and September. Cases were identified across the country with 94% in the capital Dhaka (located almost in the middle of the country). Less than half of the affected districts reported cases as observed from the surveillance data. The proportion reported varied by month with a higher proportion reported in high-incidence districts, but dropped towards the end of high transmission season.

Correlates of Climate Variability and Dengue Fever in Two Metropolitan Cities in Bangladesh

Dengue fever is a major public health concern in Bangladesh with increased incidence during monsoon. We aimed to assess the correlation of temperature, humidity, and rainfall on dengue fever in two dengue endemic cities in Bangladesh. It was a time series analysis of climate factors and dengue occurrence data in Dhaka and Chittagong cities from 1 January 2000 to 31 December 2009. Daily mean temperature, rainfall, and humidity data were obtained from the Bangladesh meteorological department and daily dengue cases data were obtained from the directorate general of health services (DGHS) of Bangladesh. The mean dengue incidence was 31.62 (SD 28.7) per 100,000 in Dhaka whereas it was 5.76 (SD 11.7) per 100,000 population in Chittagong. The incidence of dengue cases was found significantly associated with the monthly mean temperature, total rainfall, and mean humidity in Dhaka, though in Chittagong, the significantly associated factors​ ​​​​​​were monthly total rainfall and mean humidity. The autoregressive integrated moving average (ARIMA) model identified monthly mean humidity and total rainfall as the most significant contributing factors for dengue cases in Dhaka and Chittagong, respectively. Our study reinforces the relationship of climate parameters with dengue fever, which will support policy-makers in developing a climate-based early warning system for dengue in Bangladesh.

Circulating dengue virus serotypes in Bangladesh from 2013 to 2016

To identify the circulating serotype(s) of dengue viruses in Bangladesh, a retrospective molecular identification was performed on stored serum samples of dengue surveillance during the period of 2013-2016. Real time RT-PCR was performed on serum samples collected from the patients with less than 5 days fever for detection of dengue virus nucleic acid. The samples, positive for dengue PCR were further analyzed for serotypes by real time RT-PCR. The overall prevalence of dengue virus infection was varied among 13-42% in study years with a single peak flanked by April to September. Among the four dengue serotypes DEN1 and DEN2 were in the circulation in three metropolitan cities with sequential emergence of DEN1 where DEN2 was persisted constantly during the study period. Persistence of all four serotypes in the neighboring country makes Bangladesh vulnerable for devastating secondary infection by introduction of new serotype(s) other than currently circulating viruses in the country. Thus continuous virological surveillance is crucial for early warning of emergence of new serotype in the circulation and public health preparedness.

Risk factors for the presence of dengue vector mosquitoes, and determinants of their prevalence and larval site selection in Dhaka, Bangladesh

Dengue viruses are responsible for over 100 million infections a year worldwide and are a public health concern in Bangladesh. Although risk of transmission is high, data on vector population characteristics are scanty in Bangladesh; therefore, a comprehensive prediction of the patterns of local virus transmission is not possible. Recognizing these gaps, multi-year entomological surveys were carried out in Dhaka, where the disease is most frequently reported. The specific objectives of the present study are threefold: i) to determine the risk factors for the presence of Aedes mosquitoes; ii) to identify the types of most productive and key containers; and iii) to estimate the effects of climatic factors on Aedes abundance in the city of Dhaka, Bangladesh. Entomological surveys were conducted in 12 out of 90 wards in Dhaka. These wards were selected using a probability proportional sampling procedure during the monsoon seasons in 2011, 2012 and 2013 and in the dry season in 2012. All containers inside and around sampled households were inspected for mosquito larvae and pupae, and containers were classified according to their relative size, use pattern, and materials of construction. During the study period (2011-2013), 12,680 larvae and pupae were collected. About 82% of the identified immature mosquitoes were Aedes aegypti, while the remainder were Ae. albopictus and other mosquito species. The largest number of immature mosquitoes was collected from tires and refrigerator trays during 2011 and 2012 monsoon seasons. Conversely, plastic drums were the most productive during the 2012 dry and 2013 monsoon season. Vehicle parts and discarded construction materials were the most efficient producers of Aedes mosquitoes in all surveys. The presence of Aedes mosquitoes was significantly (p < 0.05) higher in low socio-economic zones of Dhaka. Container location, presence of vegetation, and availability of shade for containers were also significantly associated with finding immature Aedes mosquitoes, based on multivariable analysis after confounder adjustment. Rainfall, temperature, and relative humidity also significantly affected the mean abundance of mosquitoes. Proper use, disposal, and recycling of the containers that effectively produce large numbers of Aedes vector mosquitoes may decrease the risk of arboviral transmission.

Chikungunya outbreak (2017) in Bangladesh: Clinical profile, economic impact and quality of life during the acute phase of the disease

Background

Chikungunya virus causes mosquito-transmitted infection that leads to extensive morbidity affecting substantial quality of life. Disease associated morbidity, quality of life, and financial loss are seldom reported in resources limited countries, such as Bangladesh. We reported the acute clinical profile, quality of life and consequent economic burden of the affected individuals in the recent chikungunya outbreak (May to September 2017) in Dhaka city, Bangladesh.

Methods

We conducted a cross-sectional study during the peak of chikungunya outbreak (July 24 to August 5, 2017) to document the clinical profiles of confirmed cases (laboratory test positive) and probable cases diagnosed by medical practitioners. Data related to clinical symptoms, treatment cost, loss of productivity due to missing work days, and quality of life during their first two-weeks of symptom onset were collected via face to face interview using a structured questionnaire. World Health Organization endorsed questionnaire was used to assess the quality of life.

Results

A total of 1,326 chikungunya cases were investigated. Multivariate analysis of major clinical variables showed no statistically significant differences between confirmed and probable cases. All the patients reported joint pain and fever. Other more frequently reported symptoms include headache, loss of appetite, rash, myalgia, and itching. Arthralgia was polyarticular in 56.3% of the patients. Notably, more than 70% patients reported joint pain as the first presenting symptom. About 83% of the patients reported low to very low overall quality of life. Nearly 30% of the patients lost more than 10 days of productivity due to severe arthropathy.

Conclusions

This study represents one of the largest samples studied so far around the world describing the clinical profile of chikungunya infection. Our findings would contribute to establish an effective syndromic surveillance system for early detection and timely public health intervention of future chikungunya outbreaks in resource-limited settings like Bangladesh.

A major outbreak of chikungunya virus occurred for the first time in Dhaka, Bangladesh between May and September 2017. In this study, a face-to-face interview with a structured questionnaire was conducted to collect data to investigate the clinical symptoms, quality of life, and economic aspects of 1,326 chikungunya patients during the first two weeks of infection. The severity of the disease was similar to previously reported severe outbreaks elsewhere but joint pain prior to fever emerged as a unique symptom in the Dhaka outbreak. This unique clinical feature was consistent across age and sex of the patients. Some clinical symptoms varied with age. For instance, a higher proportion of skin rash were found among children (under 15) while morning stiffness, severity, and duration of pain were proportionally higher among other age groups. Joint swelling was most commonly noted in elderly patients (60+ years). About 83% of the patients reported low to very low overall quality of life (QoL) during first two weeks of chikungunya infection. Elderly patients reported lower average QoL scores compared to <60 years. Interestingly, housewives reported higher QoL score compared to those of businessmen and service holders. In particular, patients in the highest monthly income category bracket (BDT 50,000 per month; >$606 per month) reported the lowest average overall score. Nearly 95% of the patients have mostly confined to sickbed and approximately 30% of them lost more than 10 days of productivity due to severe arthropathy. Our study would contribute to establishing an effective syndromic surveillance system for early detection and timely public health intervention of future chikungunya outbreaks in resource-limited countries like Bangladesh.