ArticlePLOS global public health2022
Prediction of dengue annual incidence using seasonal climate variability in Bangladesh between 2000 and 2018.
Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Application of a Temporal Fusion Transformer and Long-Term Climate and Disease Data to Assess the Predictive Power and Understand the Drivers for Malaria and Dengue.International journal of environmental research and public health · 2026Article
- Article
- Modelling climatic and temporal dynamics of dengue transmission in Bangladesh using deep learning models.PLOS global public health · 2026Article
- Multivariate forecasting of dengue infection in Bangladesh: evaluating the influence of data downscaling on machine learning predictive accuracy.BMC infectious diseases · 2025Article
- Dengue Early Warning System and Outbreak Prediction Tool in Bangladesh Using Interpretable Tree-Based Machine Learning Model.Health science reports · 2025Article
- Forecasting dengue in Bangladesh using meteorological variables with a novel feature selection approach.Scientific reports · 2024Article
- Modeling zoonotic and vector-borne viruses.Current opinion in virology · 2024Review
- Association of climate factors with dengue incidence in Bangladesh, Dhaka City: A count regression approach.Heliyon · 2023Article
- Correlation of Dengue and Meteorological Factors in Bangladesh: A Public Health Concern.International journal of environmental research and public health · 2023Article
- 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.International journal of environmental research and public health · 2023Article
- Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The incidence of dengue has increased rapidly in Bangladesh since 2010 with an outbreak in 2018 reaching a historically high number of cases, 10,148. A better understanding of the effects of climate variability before dengue season on the increasing incidence of dengue in Bangladesh can enable early warning of future outbreaks. We developed a generalized linear model to predict the number of annual dengue cases based on monthly minimum temperature, rainfall and sunshine prior to dengue season. Variable selection and leave-one-out cross-validation were performed to identify the best prediction model and to evaluate the model's performance. Our model successfully predicted the largest outbreak in 2018, with 10,077 cases (95% CI: [9,912-10,276]), in addition to smaller outbreaks in five different years (2003, 2006, 2010, 2012 and 2014) and successfully identified the increasing trend in cases between 2010 and 2018. We found that temperature was positively associated with the annual incidence during the late winter months (between January and March) but negatively associated during the early summer (between April and June). Our results might be suggest an optimal minimum temperature for mosquito growth of 21-23°C. This study has implications for understanding how climate variability has affected recent dengue expansion in neighbours of Bangladesh (such as northern India and Southeast Asia).
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Registered trials
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