Data Driven Dengue Dynamics via Satellite Data

Vector-borne diseases like dengue remain a major global public health concern, with transmission strongly shaped by environmental factors. We examine how precipitation (rainfall), vegetation density, and temperature relate to dengue incidence across Sri Lanka using satellite-based data from NASA’s Earth Observing System including the Global Precipitation Measurement (GPM) and Moderate Resolution Imaging Spectroradiometer (MODIS) derived Normalized Difference Vegetation Index (NDVI). We explored spatial and related statistical associations between weather conditions and dengue spread across the country. Results show substantial regional variability in dengue incidence, with urban districts such as Colombo reporting higher case counts despite low vegetation level. A negative association was observed between NDVI values and dengue cases, while rainfall in both daytime and nighttime land surface temperatures (average temperature) had a weaker relationship with dengue across districts. These findings demonstrate the potential of using satellite-derived environmental data for large-scale dengue outbreak surveillance and highlight the integration of climate indicators with public health datasets to support predictive modeling, as well as the implementation of Early Warning Systems (EWS) to improve dengue prevention strategies in Sri Lanka and other countries.