Spatiotemporal Dynamics of Dengue Risk in Bangladesh: A GIS Based Approach

Area of Science:

• Epidemiology
• Environmental Health
• Geographic Information Systems (GIS)

Background:

• Dengue (breakbone fever) is endemic in Bangladesh, with outbreaks typically peaking post-monsoon.
• 2023 saw an unusual early dengue peak in June and the highest case fatality rate in two decades.
• Vector breeding conditions (Aedes aegypti, Aedes albopictus) are influenced by monsoon and warmer temperatures.

Purpose of the Study:

• To analyze the spatiotemporal dynamics of dengue incidence clusters and risk in Bangladesh.
• To identify key environmental and demographic factors influencing dengue transmission.
• To evaluate the effectiveness of a GIS-based multi-criteria decision-making model for dengue risk assessment.

Main Methods:

• Utilized daily dengue case data from 2019-2024.
• Applied spatial autocorrelation (Local Moran's I) and Jaccard Similarity Index (JSI) for hotspot analysis.
• Employed a GIS-based multi-criteria decision-making model (MCDM) with AHP weighting and negative binomial regression.

Main Results:

• Central and south coastal districts (Dhaka, Manikganj, Barisal) identified as major dengue hotspots.
• Significant seasonal and interannual reorganization of hotspots observed, with increased coastal concentration post-2020.
• Weighted AHP model (AUC=0.75) outperformed unweighted model (AUC=0.55) in predicting risk zones.
• Lagged temperature, precipitation, and population density positively correlated with dengue incidence.
• Normalized Difference Built-up Index showed a negative association with dengue incidence.

Conclusions:

• Dengue hotspots are dynamic and increasingly concentrated in coastal regions.
• Climate variables and population density are significant drivers of dengue outbreaks.
• Integrated control strategies focusing on high-risk areas and equitable healthcare access are crucial for managing dengue in Bangladesh.