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

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.

Mathematical analysis and prediction of future outbreak of dengue on time-varying contact rate using machine learning approach

This article introduces a novel mathematical model analyzing the dynamics of Dengue in the recent past, specifically focusing on the 2023 outbreak of this disease. The model explores the patterns and behaviors of dengue fever in Bangladesh. Incorporating a sinusoidal function reveals significant mid-May to Late October outbreak predictions, aligning with the government's exposed data in our simulation. For different amplitudes (A) within a sequence of values (A = 0.1 to 0.5), the highest number of infected mosquitoes occurs in July. However, simulations project that when βM = 0.5 and A = 0.1, the peak of human infections occurs in late September. Not only the next-generation matrix approach along with the stability of disease-free and endemic equilibrium points are observed, but also a cutting-edge Machine learning (ML) approach such as the Prophet model is explored for forecasting future Dengue outbreaks in Bangladesh. Remarkably, we have fitted our solution curve of infection with the reported data by the government of Bangladesh. We can predict the outcome of 2024 based on the ML Prophet model situation of Dengue will be detrimental and proliferate 25 % compared to 2023. Finally, the study marks a significant milestone in understanding and managing Dengue outbreaks in Bangladesh.

Assessment of perceived dengue risk and prevention practices among youth in Bangladesh

Dengue fever is a global public health concern, especially in countries like Bangladesh. This study examines youth perceived dengue risk, and preventive practices, providing valuable insights into their behavior regarding this mosquito-borne disease. A cross-sectional survey was undertaken in various regions of the Dhaka district in Bangladesh. Face-to-face interviews were conducted with 1,358 participants using convenience sampling, spanning the period from September 2 to October 10, 2023. A semi-structured questionnaire covered informed consent, socio-demographic data, and questions about perceived dengue risk scale (12 items), and prevention practice (13 items). Participants' mean age was 22.02 ± 1.58 years. The average scores for perceived dengue risk, and prevention practices were found to be 51.39 ± 12.01 (out of 96), and 55.57 ± 14.55 (out of 104) respectively. Previous dengue history, history of other vector-borne diseases, gender, educational level, father's educational qualification, employment status, adequate sleep duration, father's occupation, etc. are factors associated with higher risk and prevention practices regarding dengue. The research underscores the importance of tailoring prevention strategies for different demographics, raising awareness, and promoting active engagement in preventive measures. These insights are crucial for developing effective public health policies and campaigns to combat dengue.

The recent burden of dengue infection in Bangladesh: A serious public health issue

Dengue is a rapidly increasing vector-borne disease with a high burden in South and Southeast Asia. This article presents an overview of the current dengue situation in Bangladesh, highlighting the critical public health challenges caused by this infectious disease. Between January and September 2023, a total of 203406 people were infected, and 989 people died, with a case fatality rate of 0.49%. Of these, 96.1% of infections and 95.2% of deaths occurred between July and September. Both infection and mortality rates showed a significant and positive correlation with population density and air quality index. Other environmental and socioeconomic factors may influence the burden of dengue infection. These include temperature, rainfall, humidity, unplanned urbanization, and water storage and waste management practices. To reduce transmission and mortality rates, it is urgent to prioritize early treatment of dengue cases and take measures to address the risk factors associated with dengue infection in the country.

Effects of fine particulate matter (PM2.5) and meteorological factors on the daily confirmed cases of COVID-19 in Bangkok during 2020-2021, Thailand

The ongoing global pandemic caused by the SARS-CoV-2 virus, known as COVID-19, has disrupted public health, businesses, and economies worldwide due to its widespread transmission. While previous research has suggested a possible link between environmental factors and increased COVID-19 cases, the evidence regarding this connection remains inconclusive. The purpose of this research is to determine whether or not there is a connection between the presence of fine particulate matter (PM2.5) and meteorological conditions and COVID-19 infection rates in Bangkok, Thailand. The study employs a statistical method called Generalized Additive Model (GAM) to find a positive and non-linear association between RH, AH, and R and the number of verified COVID-19 cases. The impacts of the seasons (especially summer) and rainfall on the trajectory of COVID-19 cases were also highlighted, with an adjusted R-square of 0.852 and a deviance explained of 85.60%, both of which were statistically significant (p < 0.05). The study results assist in preventing the future seasonal spread of COVID-19, and public health authorities may use these findings to make informed decisions and assess their policies.