Research Interests
I am a quantitative disease ecologist with broad interests in disease dynamics, wildlife health, and conservation. My work combines host ecology or community ecology to understand infection dynamics. My main research interests include:
Disease dynamic consequences of co-infecting pathogens
Emerging infectious disease
Land use change and vector borne disease
Network and spatial models of diseases transmission
Wildlife health and population dynamics
About Me
Great news - as of August, I have started an assistant professor position in the University of Warwick’s School of Life Sciences and the Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research.
Please see the University of Warwick’s website for up-to date information.
Ongoing Projects
Land-use change and mosquito-borne infections
Mosquito-borne infections remain a leading cause of morbidity and mortality in sub-Saharan Africa. We are working with South African National Parks to study how human developments influence seasonal mosquito population dynamics and mosquito-borne disease risk.
Collaborators: Maarten Schrama, Danny Govender
Co-Infections in African buffalo
Interactions between co-infecting pathogens are ubiquitous in wildlife populations. Recent research has shown that co-infecting pathogens can be the most important predictors of subsequent infections and that many interactions are mediated by the host immune response. In this research, we explore the consequences of co-infection at many scales. We use tools from both disease ecology and eco-immunology to study bovine tuberculosis and brucellosis in a free ranging population of African buffalo in Kruger National Park.
Project PIs and Ph.D. advisors: Anna Jolles and Vanessa Ezenwa
Collaborators: Rampal Etienne, Roy Bengis, Brianna Beechler
U.S. Livestock Movement and Disease
The application of network analysis to livestock shipments broadens our understanding of shipment patterns beyond pairwise interactions to the network as a whole. Such a quantitative description of livestock shipments in the U.S. can identify trade communities, describe temporal shipment patterns, and inform the design of disease surveillance and control strategies. This collaborative project uses data-driven models to study livestock shipments and how they influence disease spread.
Project PIs and post-doc advisors: Colleen Webb, Uno Wennergren, Michael Tildesley
Collaborators: Michael Buhnerkempe, Angela D. Luis, Lindsay M. Beck-Johnson, Daniel A. Grear, Ryan S. Miller, Katie Portacci