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Identifying COVID-19 Vaccine Deserts Using Machine Learning and Geospatial Analyses to Target Community-Engaged Testing for Vulnerable Rural Populations to Prevent Localized Outbreaks

There is an urgency to address decreased testing, in presence of a Covid-19 vaccine, particularly for communities with lower vaccine uptake which are highly vulnerable to persistent localized micro-outbreaks and subsequently higher Covid-19 associated morbidity and mortality. This proposal utilizes machine learning with time series modeling and geospatial methodologies to identify communities with high Covid-19 transmissibility with lower vaccine uptake.

We will engage these communities by implementing a novel community-engaged testing delivery model which leverages deep connections to place, common to persons living in Appalachia. Furthermore, we build strong connections with local first responders to dynamically tailor testing activities and to establish a grass roots network to conduct future disease screening studies in vulnerable rural populations.

Amount Awarded
Length of grant
17 months

Faculty Involved