Satellite remote sensing technologies produce consistent, repeatable environmental measurements across nearly the entire surface of the Earth. The resulting storehouse of information has many potential applications in the study of human health, including mapping the geographic distributions of infectious diseases, monitoring the health impacts of climatic variability and land use change, and forecasting future health risks. Although there have been many calls for expanding the use of earth observation technologies in the health sciences, there are few examples of operational systems with a demonstrated impact on public health. Remote sensing experts typically have little understanding of how their products can be applied in the study of human health, and most health scientists and public health professionals lack the time, technical skills, and computational tools required to acquire, process, and analyze satellite remote sensing data. To more effectively bridge the gap between the remote sensing and public health fields, we will develop a web-based decision support system that will provide health scientists and practitioners with access to a suite of environmental measurements for use in the surveillance and forecasting of mosquito-borne infectious diseases.
Specific aims are to: (1) Develop a system for automated processing of satellite remote sensing data to generate environmental measurements that can provide early warning of disease outbreaks, (2) Analyze the predictive capabilities of these remote sensing products using retrospective datasets of human disease cases, and (3) Develop a web-based decision support system to facilitate visualization and analysis of remote sensing products by public health practitioners. This system will integrate a variety of currently-available datasets including land surface temperature, precipitation, vegetation indices, and land cover maps. It will also include a novel measurement of actual evapotranspiration (ETa) that will enhance our ability to characterize near-surface moisture that affects mosquito behavior and breeding habitats. The system will be implemented and tested via two cases studies: one focused on Malaria in the Amhara regional state of Ethiopia, and the other focused on West Nile virus in the Northern Great Plains. In both of these case studies, we will actively partner with public health practitioners from government agencies and non-governmental organizations to gain feedback on the usability of the decision support tools and the value of the environmental information provided. We expect that the information provided by the project will make a significant contribution toward efforts to reduce the burden of mosquito-borne infectious disease within the two case study areas, and that the system will also serve as a model for future efforts to apply earth observation technologies in the fields of epidemiology and public health.

Public Health Relevance

Mosquito-borne infectious diseases are a major public health concern in many parts of the world. Malaria is a major health problem in Ethiopia, where more than 5 million cases occur annually. West Nile virus is the predominant mosquito-borne disease in the United States, with a particularly high incidence of human disease in the Northern Great Plains. The development of disease surveillance and early-warning systems can help reduce the burden of these diseases by identifying high-risk areas and allowing public health practitioners to prioritize mosquito control and other disease-prevention efforts.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Project (R01)
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Biomedical Computing and Health Informatics Study Section (BCHI)
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Gezmu, Misrak
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South Dakota State University
Other Domestic Higher Education
United States
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Merkord, Christopher L; Liu, Yi; Mihretie, Abere et al. (2017) Integrating malaria surveillance with climate data for outbreak detection and forecasting: the EPIDEMIA system. Malar J 16:89
Liu, Yi; Hu, Jiameng; Snell-Feikema, Isaiah et al. (2015) Software to Facilitate Remote Sensing Data Access for Disease Early Warning Systems. Environ Model Softw 74:247-257
Midekisa, Alemayehu; Beyene, Belay; Mihretie, Abere et al. (2015) Seasonal associations of climatic drivers and malaria in the highlands of Ethiopia. Parasit Vectors 8:339
Wimberly, Michael C; Lamsal, Aashis; Giacomo, Paolla et al. (2014) Regional variation of climatic influences on West Nile virus outbreaks in the United States. Am J Trop Med Hyg 91:677-84
Wimberly, Michael C; Giacomo, Paolla; Kightlinger, Lon et al. (2013) Spatio-temporal epidemiology of human West Nile virus disease in South Dakota. Int J Environ Res Public Health 10:5584-602
Chuang, Ting-Wu; Henebry, Geoffrey M; Kimball, John S et al. (2012) Satellite Microwave Remote Sensing for Environmental Modeling of Mosquito Population Dynamics. Remote Sens Environ 125:147-156
Wimberly, Michael C; Midekisa, Alemayehu; Semuniguse, Paulos et al. (2012) Spatial synchrony of malaria outbreaks in a highland region of Ethiopia. Trop Med Int Health 17:1192-201
Midekisa, Alemayehu; Senay, Gabriel; Henebry, Geoffrey M et al. (2012) Remote sensing-based time series models for malaria early warning in the highlands of Ethiopia. Malar J 11:165
Chuang, Ting-Wu; Wimberly, Michael C (2012) Remote sensing of climatic anomalies and West Nile virus incidence in the northern Great Plains of the United States. PLoS One 7:e46882
Chuang, Ting-Wu; Hockett, Christine W; Kightlinger, Lon et al. (2012) Landscape-level spatial patterns of West Nile virus risk in the northern Great Plains. Am J Trop Med Hyg 86:724-31

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