Public health precautions for preventing malaria using environmental data

Considering the public health impact of a global pandemic, the reliance on data to understand disease outbreak is important now more than ever. Malaria is the most common mosquito-transmitted disease endemic to certain regions, leading to millions of serious illnesses and deaths each year. Because mosquito vectors are sensitive to environmental conditions such as temperature, precipitation, and humidity, it is possible to map areas currently or imminently at high risk for disease outbreaks using satellite remote sensing. In this paper the authors propose the development of an operational geospatial system for malaria early warning. This can be done by bringing together geographic information system (GIS) tools, artificial neural networks (ANN) for efficient pattern recognition, the best available groundbased environmental data such as epidemiological and vector ecology data, and current satellite remote sensing capabilities. The authors use Vegetation Health Indices (VHI) derived from visible and infrared radiances measured by satellite-mounted Advanced Very High Resolution Radiometers (AVHRR) and available weekly at 4- km resolution as one predictor of malaria risk in Bangladesh. As a study area, we focus on Bangladesh where malaria is a serious public health threat. The technology developed will, however, be largely portable to other countries in the world and applicable to other disease threats. A malaria early warning system will be a boon to international public health, enabling resources to be focused where they will do the most good for stopping pandemics, and will be an invaluable decision support tool for national security assessment and potential troop deployment in regions susceptible to disease outbreaks.