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Charting Sin Nombre Virus Infections in Deer Mice

Published Aug 18, 2010

Location of Walker River Basin (17) and its eight major vegetation types, as well as developed areas. Piñon-juniper woodland and montane shrubland tend to be highly interspersed and were combined for visual clarity. Because meadows occurred in very small patches, they could not be represented on this map. Map generated at Utah State University as part of the GAP conservation mapping project.

Environmental data from remote sensing and geographic information system maps were  tested as possible indicators of Sin Nombre virus (SNV) infections in deer mouse (Peromyscus maniculatus) populations in the Walker River Basin, Nevada and California. Deer mice from 144 field sites were tested for the presence of SNV infections. Remote sensing and geographic information systems data were used to characterize the vegetation type and density, elevation, slope, and hydrologic features of each field site. The data retroactively predicted infection status of deer mice with up to 80% accuracy. If models of SNV temporal dynamics can be integrated with baseline spatial models, human risk for infection may be assessed with reasonable accuracy.


The Result


It should be possible to estimate the frequency (if not the specific timing) of new infections as a function of a site’s local environment. Additionally, extended longitudinal studies could identify typical infection trajectories of sites based on their environmental characteristics or demographic profiles of their host populations. When combined, these approaches should advance our ability to quantify and predict disease dynamics and human risk.



John D. Boone, K.McGwire, E.Otteson, R. DeBaca, E. Kuhn, P. Villard, P. Brussard, and S. St. Jeor, Remote Sensing and Geographic Information Systems: Charting Sin Nombre Virus Infections in Deer Mice, Emerging Infectious Diseases, Vol. 6, No. 3.

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