I am a disease ecologist who uses computational tools and big data approaches to study where viruses occur and how host communities form. The mechanisms underlying occurrence and spillover typically involves a plethora of factors, such as climate, competition, predation, historical changes in biogeography, and anthropogenic pressures arising from changes in land-use. In my research program, I quantitatively integrate these myriad factors using data from different disciplines to explore where viruses occur and how communities form. The inherent complexity and multidimensional nature of ecological responses requires both modeling rigor and an ability to draw on different disciplines so as to add to unique insights into the mechanisms underlying disease outbreaks. My work operates in many different disciplines and scales.

Research Overview

Ongoing research

How frugivory drives Ebolavirus infections and spillover events

Frugivorous mammals in Sub-Saharan Africa tend to be infected by ebolaviruses. In this project, my collaborators and I are developing fruit tree layers to examine if fruit production could explain where Ebola outbreaks occur. This manuscript is currently under review.

Factors influencing search for the elusive Ebolavirus reservoir

The search for the reservoir of Ebola has puzzled investigators for decades. Very few animals seem to be infected from a wide swath of phylogenetic clades. I have developed a framework that could explain why sampling efforts thus far have failed to identify a reservoir. I have also developed a map highlighting regions where the reservoir is most likely to be found. The manuscript is under review.

Classifying infectious disease outbreaks and forecasting future epidemics

Forecasting future epidemics and pandemics is an important task needing large amounts of data and predictive models. Working with collaborators, I have collected a dataset of disease outbreaks. We are developing a modeling method that can identify epicenters of future epidemics and pandemics. I am looking for motivated students to move this project forward.

Discover how data can drive disease prevention