Infectious Diseases Work Group
Leads: Antar Jutla (University of Florida) and Tatiana Loboda (University of Maryland-College Park)
The Normalized Difference Vegetation Index (NDVI) is a satellite measurement of the “greeness” of vegetation; NDVI anomalies reveal how much healthier (greener) vegetation is than normal. Greener areas are usually wetter, suggesting better habitat for mosquitoes. Favorable conditions for mosquitoes in 2006 led to Rift Valley fever (RVF) outbreaks in eastern Africa. The region greened again in 2015, but early warnings helped officials prevent the spread of RVF. Credit: NASA Earth Observatory, using NDVI anomaly data from Terra MODIS
This Work Group seeks to improve prediction and prevention systems for environmentally-sensitive infectious diseases (e.g. vector-borne and water-related diseases) that enhance decision-relevant risk monitoring to mitigate human health risks in vulnerable communities.
Primary Goal
To improve prediction and prevention systems for environmentally-sensitive infectious diseases to help reduce risks for human health by application of EO to decision-relevant risk monitoring, with particular focus on underserved communities.
Two overarching goals are to: 1) develop a generalization framework for incorporating climatic and environmental data for enhancing predictive and decision-making mapping capacity to serve as the EO backbone for water- air- and vector-borne diseases; and 2) develop platform for the monitoring and prediction of emerging pathogens and toxins risk in marine and coastal environments coupled with critical EO-derived coastal and inland water quality parameters.
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