Spatial Analysis of West Nile Virus: Rapid Risk Assessment of an Introduced Vector-Borne Zoonosis

Abstract

The distribution of human risk for West Nile virus was determined by spatial analysis of the initial case distribution for the New York City area in 1999 using remote sensing and geographic information system technologies. Cluster analysis revealed the presence of a statistically significant grouping of cases, which also indicates the area of probable virus introduction. Within the cluster, habitat suitability for potentially infective adult mosquitoes was measured by the amount of vegetation cover using satellite imagery. Logistic regression analysis revealed satellite-derived vegetation abundance to be significantly and positively associated with the presence of human cases. The logistic model was used to estimate the spatial distribution of human risk for West Nile virus throughout New York City. Accuracy of the resulting risk map was cross-validated using virus-positive mosquito sample sites. These new epidemiological methods aid in rapid entry point identification and spatial prediction of human risk of infection for introduced vector-borne pathogens.

Regional Differences in the Association Between Land Cover and West Nile Virus Disease Incidence in Humans in the United States

“…27 In this study, we used 14 land cover classes 15 to characterize the landscape in different regions of the United States. West of the Mississippi River, the main mosquito vector of WNV is Cx.…”

Ecologic Factors Associated with West Nile Virus Transmission, Northeastern United States

“…The spatial resolution of human surveillance data did not allow for fi ner evaluation of within-urban associations. Brownstein et al linked human WNV cases to greenness indices in urban areas and found an optimal vegetation index associated with higher human cases (35). Brown et al found an environmental separation of bridge and enzootic vectors; bridge vectors occurred in areas with vegetation that might be associated with residential areas within a city (36).…”

Modeling the Spatial Distribution of Mosquito Vectors for West Nile Virus in Connecticut, USA

“…Logistic regression modeling has been extensively used to formalize the relationship between environmental factors and the pres-ence/absence of vectors (Brownstein et al 2003, Dumonteil and Gourbiere 2004, Thomson et al 1999) and incidence of vector-borne diseases in humans (Brooker et al 2001, Elnaiem et al 2003, King et al 2004, Lindsay and Thomas 2000, Thompson et al 1996 and to quantify the amount of potential habitat. In this study, we did not use presence/absence but rather high/low mosquito abundance as the response variable.…”

“…An alternative approach is to use landscape variables derived from remote sensing satellites as predictors, with or without incorporating the effects of spatial dependence. Pertinent examples include vectors of Eastern equine encephalomyelitis (Moncayo et al 2000), tick vectors of Lyme disease (Brownstein et al 2003, Guerra et al 2001, Kitron et al 1996, sand fly vectors of leishmaniasis (Cross et al 1996, Elnaiem et al 2003, Miranda et al 1998, Thomson et al 1999, tse-tse fly vectors of African trypanosomiasis (Kitron et al 1996, Rogers 2000, and mosquito vectors of malaria (Beck et al 1994, Diuk-Wasser et al 2004, Thomson et al 1996, Wood et al 1991a,b, 1992. Of these models, however, only a few have been validated with an independent dataset (Beck et al 1997, Brownstein et al 2004).…”