Modeling Spatio-temporal Malaria Risk Using Remote Sensing and Environmental Factors.

Background: Remote sensing have been intensively used across many disciplines, however, such information was limited in spatial epidemiology.

Methods: Two years (2009 & 2010) Landsat TM satellite data was used to develop vegetation, water bodies, air temperature and humidity criterion maps to model malaria risk and its spatiotemporal seasonal variation. The criterion maps were used in weighted overlay analysis to generate final categorized malaria risk map.