AI may also help researchers develop a surprising new pandemic early-warning system. Monitoring wild animals for infectious disease outbreaks is a critical part of not only ecosystem management and biodiversity protection, but also of pandemic preparedness, since many diseases that devastate humans originate in the wild. But surveillance is difficult, making it hard to detect such threats early. A solution might come from space. Sick people and animals move their bodies differently than they do when they are healthy. Their social interactions are also significantly disrupted. High-resolution satellite imaging processed with AI might spot abnormal movements suggesting animals are ill—a possibility the researchers explored with captive buffalo herds in the first year of this project. In herds with higher levels of bovine tuberculosis, they found, animals tended to keep more distance from one another. Renewed this year, this seed grant will continue to study how AI might allow for automated detection of wildlife diseases from space.
Participants
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Vanessa Ezenwa
Professor for the School of Medecine
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Will Rogers
Graduate Student
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Steve Chang
Associate Professor of Psychology and of Neuroscience, co-Director of Undergraduate Studies for the Neuroscience (NSCI) Major, co-Director of Graduate Studies, Interdepartment
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Lacey Hughey
Ecologist, Program Coordinator for the Smithsonian National Zoo and Conservation Biology Institute
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Jared Stabach
Research Ecologist for the Smithsonian National Zoo and Conservation Biology Institute
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Caleb Robinson
Principal Research Science Manager for Microsoft AI for Good Research Lab