SPATIAL DISTRIBUTION MODEL OF A HANTAVIRUS

CARBAJO, A.; PARDIÑAS, U.F.J.

JOURNAL OF MAMMALOGY

American Society of Mammalogist - Allen Press

Lugar: Lawrence; Año: 2007 vol. 88 p. 1555 - 1558

0022-2372

A 1st step in understanding the ecology of rodents as reservoirs and their relation with the disease they transmit is to determine their geographical distribution. This distribution can be modeled as a function of environmental variables. We georeferenced an extensive database of records of the hantavirus reservoir Oligoryzomys longicaudatus (Cricetidae: Sigmodontinae) in Argentina and used generalized linear models to model the probability of the presence of this reservoir as a function of environmental variables. The variables used in the multiple logistic regression were temperature, precipitation, evapotranspiration, altitude, tree cover, grass cover, bare soil cover, and distance to rivers, to water bodies, and to roads; 2 phytogeographic classifications also were included. Spatial autocorrelation was considered in the model by including a spatial dependence covariate. The best model included temperature and precipitation as explanatory variables. External validation showed that the model without the space covariate correctly classified 95% of the sites with the rodent and 70% of the sites without it; the model including the spatial term correctly classified 100% of the sites with the rodent and 70% of the sites without it. A secondary model included days with frost and percent cover by bare soil as explanatory variables. O. longicaudatus was recorded in 97% of sites in the High Andean–Subantarctic regions, 65% of sites in the Monte–Espinal–Patagonian regions, and 0% of sites in the Pampean region.Oligoryzomys longicaudatus (Cricetidae: Sigmodontinae) in Argentina and used generalized linear models to model the probability of the presence of this reservoir as a function of environmental variables. The variables used in the multiple logistic regression were temperature, precipitation, evapotranspiration, altitude, tree cover, grass cover, bare soil cover, and distance to rivers, to water bodies, and to roads; 2 phytogeographic classifications also were included. Spatial autocorrelation was considered in the model by including a spatial dependence covariate. The best model included temperature and precipitation as explanatory variables. External validation showed that the model without the space covariate correctly classified 95% of the sites with the rodent and 70% of the sites without it; the model including the spatial term correctly classified 100% of the sites with the rodent and 70% of the sites without it. A secondary model included days with frost and percent cover by bare soil as explanatory variables. O. longicaudatus was recorded in 97% of sites in the High Andean–Subantarctic regions, 65% of sites in the Monte–Espinal–Patagonian regions, and 0% of sites in the Pampean region.(Cricetidae: Sigmodontinae) in Argentina and used generalized linear models to model the probability of the presence of this reservoir as a function of environmental variables. The variables used in the multiple logistic regression were temperature, precipitation, evapotranspiration, altitude, tree cover, grass cover, bare soil cover, and distance to rivers, to water bodies, and to roads; 2 phytogeographic classifications also were included. Spatial autocorrelation was considered in the model by including a spatial dependence covariate. The best model included temperature and precipitation as explanatory variables. External validation showed that the model without the space covariate correctly classified 95% of the sites with the rodent and 70% of the sites without it; the model including the spatial term correctly classified 100% of the sites with the rodent and 70% of the sites without it. A secondary model included days with frost and percent cover by bare soil as explanatory variables. O. longicaudatus was recorded in 97% of sites in the High Andean–Subantarctic regions, 65% of sites in the Monte–Espinal–Patagonian regions, and 0% of sites in the Pampean region.O. longicaudatus was recorded in 97% of sites in the High Andean–Subantarctic regions, 65% of sites in the Monte–Espinal–Patagonian regions, and 0% of sites in the Pampean region.