Emerging infectious diseases

I have used mathematical models to predict the spread of Ebola and White-nose Syndrome. The models were used to assess the impacts of containment of transmission through behavioral changes (Ebola) and mass die offs of susceptible hosts (White-nose Syndrome).

Assessing the progression of Ebola in Liberia.

I was part of a team of researchers at the University of Georgia and Penn State that developed a multitype branching process model of Ebola transmission in Liberia with time-varying parameters that accounted for changing human behavior. The model included transmission in community, hospital and funeral settings through offspring distributions based on available data. I helped estimate the basic reproduction number of Ebola in Liberia through calculating the threshold for emergence of the model. We used the model to assess the progression of Ebola in Liberia and to explore a multitude of containment scenarios such as increasing the capacity of treatment facilities and the rate of individuals seeking treatment. Our model showed that a background hospitalization rate of 70% (roughly that observed in June-August 2014 in Liberia) would keep the effective reproduction number at approximately unity. A higher hospitalization rate of 85% (the intervention most resembling the situation that transpired in Liberia in the first half of 2015) predicted near complete elimination of Ebola from Liberia between March and June 2015. This work was completed in collaboration with John Drake, Laura Alexander, Reni Kaul, Tomlin Pulliam, Drew Kramer, Andrew Park and Matt Ferrari.

My postdoctoral work has also investigated if local extirpation events will inhibit the spread of White-nose Syndrome, an emerging infectious disease of bats, in the United States.

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Predicted spread of White-nose Syndrome in the contiguous United States by the year 2056.

White-nose Syndrome is an emerging infectious disease that has decimated hibernating bat populations in North America. Since 2006, it has rapidly spread over a wide geographic range. At hibernation sites, mass die offs of bats have occurred, with population declines exceeding 75% at some sites. Such severe declines are a serious cause of concern for the viability of ecologically important bat populations. Spread of White-nose Syndrome at large spatial scales is ultimately constituted by local processes such as transmission within and between hibernation sites and disease-induced mortality. It is not clear how such processes combine to produce the spatiotemporal pattern of spread at the county scale. Will local extinction events at hibernation sites slow down, or halt, spread of White-nose Syndrome over large spatial scales? To answer this question, I developed a dynamical network model in collaboration with Krisztian Magori, Tomlin Pulliam, Marcus Zokan, RajReni Kaul, Heather Barton and John Drake that combines the separate spatial scales through the use of  cave-scale infection histories and U.S. county incidence data. Our model predicts that >80% of counties in the contiguous United States will become eventually infected, suggesting that local extirpation events will not mitigate spread.