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Predicting risk of West Nile virus (WNV) human transmission in Suffolk County, New York based on environmental and socioeconomic factors

Posted on:2011-01-31Degree:Ph.DType:Dissertation
University:TUI UniversityCandidate:Rochlin, IliaFull Text:PDF
GTID:1444390002964475Subject:Biology
Abstract/Summary:PDF Full Text Request
West Nile virus (WNV) is an emerging mosquito-borne pathogen of public health importance worldwide. Environmental and socioeconomic factors can significantly influence WNV human transmission risk by altering the likelihood of exposure to infected mosquito vectors. This study utilized a case-control approach based on geographic location to explore the association between the risk of vector-borne WNV and habitat, landscape, virus activity, and socioeconomic parameters in Suffolk County, NY. Eco-epidemiology conceptual framework was applied through Geographic Information Systems (GIS) to develop a logistic regression model to investigate factors predictive of the presence of acute WNV human cases at geographic household locations in 2000-04. Positive associations with WNV risk in the model included the following environmental factors: natural vegetation (p = .051) and road (p = .031) fragmentation, wetlands (p = .046), and geographic proximity to WNV mosquito activity (p = .001). Environmental factors negatively associated with WNV human risk included woody wetlands ( p = .001), groundwater recharge basins (p = .087), and proximity to tidal wetlands (p < .001). Among socioeconomic factors, proportion of population with college education was positively predictive of WNV risk (p < .001), while household income ( p < .033) and senior households (p < .001) had a negative association with WNV risk. Two additional factors, wetland fragmentation and vacant housing, were not statistically significant at p < .1, but improved the model's accuracy.;The resulting WNV risk map was verified with a 2005-08 WNV human case dataset. The 2000-04 dataset's risk map sensitivity of 89% was significantly higher than 55% for the 2005-08 dataset (p = .031). However, higher proportion of WNV human cases (>90%) were located inside or in close proximity to the high risk areas than expected by chance (p = .023).;This study contributed to a better understanding of factors associated with WNV human risk generating a sub-county level epidemiological map, which is expected to enhance WNV surveillance and control efforts. The novel approach employed herein may be implemented by other municipal, local, or state public health agencies to improve geographic risk estimates for vector-borne diseases based on a small number of acute human cases.
Keywords/Search Tags:WNV, Risk, Human, Factors, Environmental, Virus, Geographic
PDF Full Text Request
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