The Use of Remote Sensing-Based Surface Inundation Products in Human Health Applications in Eastern Africa

The potential impact of climate variability and change on the spread of infectious disease is of increasing concern to public health. Newly-available remote sensing datasets may be combined with predictive modeling to develop new capabilities to increase the public health community's capacity to employ appropriate information to mitigate the public health impacts of climate on vector-borne diseases such as malaria, leishmaniasis, rift valley fever. We have developed new and improved remote-sensing products for monitoring water bodies and inundation dynamics that have potential utility for forecasting risks of vector-borne disease epidemics. These products include daily and seasonal surface inundation for the East African region based on the global mappings of inundated water fraction derived at the 25-km scale from both active and passive microwave instruments ERS, QuikSCAT, ASCAT, and SSM/I data. We present validation of this product using high resolution (100m) PALSAR classification of inundated areas in this region, along with analysis of the dynamics of this product with observed precipitation (provided by TRMM) and historical malaria occurrence in the east African country of Eritrea. We present a framework for use of these new datasets for prediction of malaria risk.

This work is supported through funding from the NASA Applied Sciences Program, the NASA Terrestrial Ecology Program, and the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program . This study is supported and monitored by National Oceanic and Atmospheric Administration (NOAA) under Grant - CREST Grant # NA11SEC4810004.The statements contained within the manuscript/research article are not the opinions of the funding agency or the U.S. government, but reflect the authors' opinions.