Journal Article

Geographic Prediction of Human Onset of West Nile Virus Using Dead Crow Clusters: An Evaluation of Year 2002 Data in New York State

Glen D. Johnson, Millicent Eidson, Kathryn Schmit, April Ellis and Martin Kulldorff

in American Journal of Epidemiology

Published on behalf of Johns Hopkins Bloomberg School of Public Health

Volume 163, issue 2, pages 171-180
Published in print January 2006 | ISSN: 0002-9262
Published online November 2005 | e-ISSN: 1476-6256 | DOI: http://dx.doi.org/10.1093/aje/kwj023
Geographic Prediction of Human Onset of West Nile Virus Using Dead Crow Clusters: An Evaluation of Year 2002 Data in New York State

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The risk of becoming a West Nile virus case in New York State, excluding New York City, was evaluated for persons whose town of residence was proximal to spatial clusters of dead American crows (Corvus brachyrhynchos). Weekly clusters were delineated for June–October 2002 by using both the binomial spatial scan statistic and kernel density smoothing. The relative risk of a human case was estimated for different spatial-temporal exposure definitions after adjusting for population density and age distribution using Poisson regression, adjusting for week and geographic region, and conducting Cox proportional hazards modeling, where the week that a human case was identified was treated as the failure time and baseline hazard was stratified by region. The risk of becoming a West Nile virus case was positively associated with living in towns proximal to dead crow clusters. The highest risk was consistently for towns associated with a cluster in the current or prior 1–2 weeks. Weaker, but positive associations were found for towns associated with a cluster in just the 1–2 prior weeks, indicating an ability to predict onset in a timely fashion.

Keywords: arboviruses; geographic information systems; Poisson distribution; population surveillance; proportional hazards models; space-time clustering; West Nile virus; zoonoses; WNV, West Nile virus

Journal Article.  5528 words.  Illustrated.

Subjects: Public Health and Epidemiology

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