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Open Access Methodology

Spatio-temporal analysis of the relationship between WNV dissemination and environmental variables in Indianapolis, USA

Hua Liu1*, Qihao Weng2 and David Gaines3

Author affiliations

1 Department of Political Science and Geography, Old Dominion University, Norfolk, Virginia 23529, USA

2 Center for Urban and Environmental Change, Department of Geography, Indiana State University, Terre Haute, Indiana 34709, USA

3 Office of Epidemiology, Virginia Department of Health, Richmond, Virginia 23219, USA

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Citation and License

International Journal of Health Geographics 2008, 7:66  doi:10.1186/1476-072X-7-66

Published: 18 December 2008

Abstract

Background

This study developed a multi-temporal analysis on the relationship between West Nile Virus (WNV) dissemination and environmental variables by using an integrated approach of remote sensing, GIS, and statistical techniques. WNV mosquito cases in seven months (April-October) of the six years (2002–2007) were collected in Indianapolis, USA. Epidemic curves were plotted to identify the temporal outbreaks of WNV. Spatial-temporal analysis and k-mean cluster analysis were further applied to determine the high-risk areas. Finally, the relationship between environmental variables and WNV outbreaks were examined by using Discriminant Analysis.

Results

The results show that the WNV epidemic curve reached its peak in August for all years in the study area except in 2007, where the peak was reached in July. WNV dissemination started from the central longitudinal corridor of the city and spread out to the east and west. Different years and seasons had different high-risk areas, but the southwest and southeast corners show the highest risk for WNV infection due to their high percentages of agriculture and water sources.

Conclusion

Major environmental factors contributing to the outbreak of WNV in Indianapolis were the percentages of agriculture and water, total length of streams, and total size of wetlands. This study provides important information for urban public health prevention and management. It also contributes to the optimization of mosquito control and arrangement of future sampling efforts.