Modeling the Spatial and Temporal of Hantavirus Infection in Host Populations

Project institution: Desert Research Institute, Reno, Nevada

Principal investigator: Kenneth McGwire¹
Co-investigators: Stephen St. Jeor², Michael Buchmeir³, and Dennis Burton³

¹ Desert Research Institute, Reno, Nevada
² Dept. of Microbiology, University of Nevada at Reno
³ The Scripps Research Institute

Laboratory and field studies are being synthesized with environmental information derived from remotely sensed data and a geographic information system (GIS) to develop a model of the spatial and temporal dynamics of Sin Nombre Virus (SNV) infection in deer mice of the Great Basin. This will allow us to estimate prevalence at the regional scale based on the distribution and connectivity of required habitat parameters. This may in turn be translated to risk, based on information on land use and the potential for human exposure. A Monte Carlo based simulation strategy will be used to create probabilistic projections of the virus in host populations and an analysis of dynamics under different scenarios of incidence, climate, and management strategies.

Hypothesis: Environmental data from remote sensing and GIS data sources may be used to model the spatial and temporal dynamics of hantavirus infections in the host rodent species, Peromyscus maniculatus.

Aims:

1. Identify relationships between the population density of P. maniculatus and habitat characteristics.

2. Sample mice in various habitats for SNV infection rates and relate to population and habitat characteristics.

3. Develop a cellular automata that simulates the spatial and temporal dynamics of SNV infection throughout a region.

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Last updated: 27 Mar 2000