By analyzing historical patterns of emergence and spread of tick-borne pathogens, we gain insights into the environmental drivers and build spatial risk maps to guide prevention and intervention efforts.
Mapping environmental risk for vector-borne pathogens is a critical tool for disease prevention and control. Our lab has generated the first standardized risk map for Lyme disease based entirely on field-collected data and has modeled the regional dynamics of tick-borne disease spread. We are currently developing a US-wide model to determine how environmental and socioeconomic drivers influence the speed and direction of spread of different tick-borne pathogens. The model will be informed by: 1) county-level data on the presence of Borrelia spp., Babesia spp., and Anaplasma spp. in ticks and humans; 2) remotely sensed data; and 3) distance of naïve counties from those that are colonized. Results of the statistical analysis will be used to build space-time stochastic models of tick-borne disease invasion. The performance of stochastic models will be validated using 15 years of historical data. The model with the best performance will be used to forecast tick-borne disease invasion for the next decade.
LAB MEMBERS: Pilar Fernandez
COLLABORATORS: Donal Bisanzio (University of Oxford), Bryon Backenson and Melissa Prusinski (New York State Department of Health)