RESUMEN
The appearance and spread of West Nile virus (WNv) in North America represent a recent example of how mosquito-borne diseases can develop in new settings. Understanding the epidemiological, biological, and geographical aspects of WNv is critical to developing a greater understanding of how newly emerging, migrating, or evolving vector-borne infectious disease can develop globally. To aid in the allocation of resources that mitigate future outbreaks and to better understand the geographic nature of WNv in the North American prairies, we employ spatial and nonspatial modeling methods to predict municipal-level risk of human WNv infection rates. We use data based on a combination of routinely collected electronic data sources. Our findings suggest general agreement between spatial and nonspatial approaches, and results are consistent with seroprevalence-based estimates. We suggest that spatial models based on administrative data can offer estimates of relative risk in human populations at less cost, and in a timelier manner than estimates based on serology specimens.
Asunto(s)
Control de Enfermedades Transmisibles/métodos , Fiebre del Nilo Occidental/epidemiología , Fiebre del Nilo Occidental/transmisión , Animales , Simulación por Computador , Culicidae , Geografía , Humanos , América del Norte/epidemiología , Estudios Seroepidemiológicos , Estadística como Asunto , Fiebre del Nilo Occidental/virologíaRESUMEN
BACKGROUND: This paper applies a method for modelling the spatial variation of West Nile virus (WNv) in humans using bird, environmental and human testing data. METHODS: We used data collected from 503 Alberta municipalities. In order to manage the effects of residual spatial autocorrelation, we used generalized linear mixed models (GLMM) to model the incidence of infection. RESULTS: There were 275 confirmed cases of WNv in the 2003 calendar year in Alberta. Our spatial model indicates that living in the grasslands natural region and levels of human testing are significant positive predictors of WNv; living in an urban area is a significant negative predictor. CONCLUSION: Infected bird data contribute little to our model. The variability of West Nile virus incidence in Alberta may be partly confounded by the variations in the rate of testing in different parts of the province. However, variation in infection is also associated with known environmental risk factors. Our findings are consistent with existing knowledge of WNv in North America.