The proposed effort will develop spatial analysis techniques which can provide information on the spread of Sir Nombre Virus (SNV) in rodent populations throughout a region. This effort will focus on the area encompassed by the Great Basin of the western United States. In order to examine the risk potential from hantavirus, a geographic information system (GIS) database, a modeling framework, and a simulation methodology wall be developed. Peromyscus maniculatus will be the primary host species under study. This project component will be tightly integrated with laboratory and field sampling in) other projects of this Emerging Viruses Research Group (EVRG) proposal to provide an innovative, hierarchical approach for modeling host populations with spatial data inputs. Spatial patterns and environmental constraints in rodent populations will be established from field sampling. Sample data will be tested against GIS-based data sources to determine what relationships exist between rodent populations and habitat characteristics, as derived from remote sensing and GIS data sources. Relationships between virus/host, host/habitat, and habitat/landscape will be structured as a set of rules, whose parameters will be established by laboratory and field studies. This rule base will form the basis for a cellular automaton (CA) simulating the regional spread of the virus in host populations. Cellular automata simulate complex spatial/temporal phenomena by performing discrete iterations of a rule base on neighboring samples set in a spatial framework. CA simulations will be run in a Monte Carlo fashion to provide probabilistic map products characterizing parameters such as mean and variance in time to first contact by SNV. Despite the difficulty in developing a quantitative estimate of host/human transmission probabilities, there are certain predictable relationships between risk of infection and demographic characteristics. We will compile demographic and socio-economic data from the Census and code this information to a map base for comparison with simulation runs. A set of rules will then be constructed in order to provide qualitative information on risk levels throughout the region.