Predictive Mapping of Human Risk for West Nile Virus (WNV) Based on Environmental and Socioeconomic Factors
2011

Mapping Human Risk for West Nile Virus in Suffolk County, NY

Sample size: 200 publication 10 minutes Evidence: moderate

Author Information

Author(s): Ilia Rochlin, David Turbow, Frank Gomez, Dominick V. Ninivaggi, Scott R. Campbell

Primary Institution: Suffolk County Vector Control

Hypothesis

Can environmental and socioeconomic factors predict the risk of West Nile Virus (WNV) in humans?

Conclusion

The study developed a predictive map showing that areas with higher education levels and habitat fragmentation are at greater risk for WNV infection.

Supporting Evidence

  • 89% of WNV human cases from 2005-2010 occurred near high-risk areas predicted by the model.
  • The model identified middle-class suburban neighborhoods as having the highest WNV risk.
  • Statistical analysis showed significant associations between WNV risk and socioeconomic factors.

Takeaway

This study made a map to show where people are more likely to get sick from West Nile Virus based on things like where they live and how educated they are.

Methodology

The study used a case-control design with logistic regression modeling to analyze environmental and socioeconomic factors affecting WNV risk.

Potential Biases

Potential biases include reliance on public data and the ecological fallacy due to aggregated data.

Limitations

The model's accuracy may be affected by changes in environmental and socioeconomic factors over time and potential biases in data collection.

Participant Demographics

The study focused on residents of Suffolk County, NY, with a population of approximately 1.4 million.

Statistical Information

P-Value

<0.001

Confidence Interval

1.18-1.57

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1371/journal.pone.0023280

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