A Multiscale Satellite Based Prediction of Diarrheal Disease: Case Study from Cholera (Invited Presentation)

Cholera and cholera-like diarrheal infections continue to be a public health threat. In fact, the risk of diarrheal disease increase exponentially in a region where population vulnerability intersects extreme climate or natural hazard. Water and sanitation infrastructure (WASH) remains one of the most effective intervention strategies to mitigate disease risk. The sheer cost to provide sustained WASH infrastructure on global scales is perhaps practically not feasible under any financial scenario. Therefore, the critical question remains as to where and when to provide WASH infrastructure and regulate water resources that may reduce burden of disease. Cholera outbreaks can be classified in three forms– epidemic (sudden or seasonal outbreaks), endemic (recurrence and persistence of the disease for several consecutive years) and mixed-mode endemic (combination of certain epidemic and endemic conditions) with significant spatial and temporal heterogeneity. With more than a decade of satellite data available, it is now possible to understand and develop a modeling schema for predicting probabilities of occurrence of infectious pathogens (V. cholerae) on global scales. Using data from multiple satellites (AVHRR, TRMM, GPM, MODIS, VIIRS, GRACE, SWOT), we estimated ensemble probability distribution of vibrio growth risks in coastal and inland water regions using four ecological niche models. The models were calibrated on a local scale using reported occurrence of pathogens and thereafter, simulated along the coastal and inland regions of the globe. NASA Earth Exchange (NEX) data for 2030, 2050, 2070 and 2090 were used to simulate future scenarios of vibrio presence in the aquatic media. We will show risk maps for vulnerability of regions to vibrio growth under present and future climate scenarios. It will enable general public and health professions to determine seasonal habitats for presence of vibrios that is likely to reduce interaction of human population with pathogens, and hence decrease disease burden.