Abstract
West Nile Virus has quickly become a serious problem in the United States (US). Its extremely rapid diffusion throughout the country argues for a better understanding of its geographic dimensions. Both 2003 and 2004 percentages of deaths by numbers of reported human cases, for the 48 coterminous US states, are analyzed with a range of spatial statistical models, seeking to furnish a fuller appreciation of the variety of models available to researchers interested in analytical disease mapping. Comparative results indicate that no single spatial statistical model specification furnishes a preferred description of these data, although normal approximations appear to furnish some questionable implications. Findings also suggest several possible future research topics.
Highlights
West Nile Virus (WNV [1,2]), first isolated in the West Nile District of Uganda in 1937, is a flavivirus transmitted by a mosquito vector, with a general incubation period of 2–14 days following a bite by an infected mosquito, and is closely related to the St
0.226 0.122 because of its simplicity, and because it is able to sense the presence of a mixture of positive and negative spatial autocorrelation components latent in the geographic distribution of WNV deaths
This model feature is not shared by the more conventional specifications. These findings suggest the following research hypothesis: spatial autocorrelation contained in a disease map has its negative components fade, and its positive components strengthen, through time
Summary
West Nile Virus (WNV [1,2]), first isolated in the West Nile District of Uganda in 1937, is a flavivirus transmitted by a mosquito vector, with a general incubation period of 2–14 days following a bite by an infected mosquito, and is closely related to the St. Once WNV appears in an area, infected people begin to die, with human deaths and cases becoming a geographic quantification of choice In response to this public health problem, by 2002 CDC was releasing numbers of cases and of deaths, for US states; today these data are being released for US counties. An analysis of the numbers of deaths attributable to WNV standardized by the corresponding number of reported cases (i.e., percentage data) for 2003 (overall 2.7%) and 2004 (overall 3.6%), by state (see Figure 2), reveals the presence of weak-to-negligible spatial autocorrelation (see Tables 2 and 3). The spatial filter generalized linear model has residuals that contain only trace negative spatial autocorrelation, furnishes a respectable description of these data, lacks overdispersion, and provides predicted and observed values that are well matched for 2003 and overestimated for 2004. The discrepancies between specification results emphasize differences in modeling assumptions, error structure, and detailed treatment of latent spatial autocorrelation, resulting in different nuances and idiosyncrasies of the data being highlighted
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