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Economic Conditions Predict Prevalence of West Nile Virus

Overview of attention for article published in PLOS ONE, November 2010
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Title
Economic Conditions Predict Prevalence of West Nile Virus
Published in
PLOS ONE, November 2010
DOI 10.1371/journal.pone.0015437
Pubmed ID
Authors

Ryan J. Harrigan, Henri A. Thomassen, Wolfgang Buermann, Robert F. Cummings, Matthew E. Kahn, Thomas B. Smith

Abstract

Understanding the conditions underlying the proliferation of infectious diseases is crucial for mitigating future outbreaks. Since its arrival in North America in 1999, West Nile virus (WNV) has led to population-wide declines of bird species, morbidity and mortality of humans, and expenditures of millions of dollars on treatment and control. To understand the environmental conditions that best explain and predict WNV prevalence, we employed recently developed spatial modeling techniques in a recognized WNV hotspot, Orange County, California. Our models explained 85-95% of the variation of WNV prevalence in mosquito vectors, and WNV presence in secondary human hosts. Prevalence in both vectors and humans was best explained by economic variables, specifically per capita income, and by anthropogenic characteristics of the environment, particularly human population and neglected swimming pool density. While previous studies have shown associations between anthropogenic change and pathogen presence, results show that poorer economic conditions may act as a direct surrogate for environmental characteristics related to WNV prevalence. Low-income areas may be associated with higher prevalence for a number of reasons, including variations in property upkeep, microhabitat conditions conducive to viral amplification in both vectors and hosts, host community composition, and human behavioral responses related to differences in education or political participation. Results emphasize the importance and utility of including economic variables in mapping spatial risk assessments of disease.

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Geographical breakdown

Country Count As %
United States 7 6%
Switzerland 2 2%
Canada 2 2%
Italy 1 <1%
Egypt 1 <1%
French Polynesia 1 <1%
Unknown 100 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 22%
Student > Master 20 18%
Student > Ph. D. Student 16 14%
Student > Bachelor 11 10%
Student > Doctoral Student 11 10%
Other 22 19%
Unknown 9 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 39%
Medicine and Dentistry 14 12%
Environmental Science 14 12%
Veterinary Science and Veterinary Medicine 5 4%
Economics, Econometrics and Finance 3 3%
Other 18 16%
Unknown 16 14%