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Discovering Spatio‐Temporal Models of the Spread of West Nile Virus

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  • Jennifer Orme‐Zavaleta
  • Jane Jorgensen
  • Bruce D'Ambrosio
  • Eric Altendorf
  • Philippe A. Rossignol

Abstract

Emerging infectious diseases are characterized by complex interactions among disease agents, vectors, wildlife, humans, and the environment.(1–3) Since the appearance of West Nile virus (WNV) in New York City in 1999, it has infected over 8,000 people in the United States, resulting in several hundred deaths in 46 contiguous states.(4) The virus is transmitted by mosquitoes and maintained in various bird reservoir hosts.(5) Its unexpected introduction, high morbidity, and rapid spread have left public health agencies facing severe time constraints in a theory‐poor environment, dependent largely on observational data collected by independent survey efforts and much uncertainty. Current knowledge may be expressed as a priori constraints on models learned from data. Accordingly, we applied a Bayesian probabilistic relational approach to generate spatially and temporally linked models from heterogeneous data sources. Using data collected from multiple independent sources in Maryland, we discovered the integrated context in which infected birds are plausible indicators for positive mosquito pools and human cases for 2001 and 2002.

Suggested Citation

  • Jennifer Orme‐Zavaleta & Jane Jorgensen & Bruce D'Ambrosio & Eric Altendorf & Philippe A. Rossignol, 2006. "Discovering Spatio‐Temporal Models of the Spread of West Nile Virus," Risk Analysis, John Wiley & Sons, vol. 26(2), pages 413-422, April.
    • Handle: RePEc:wly:riskan:v:26:y:2006:i:2:p:413-422
    DOI: 10.1111/j.1539-6924.2006.00738.x
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    References listed on IDEAS

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    1. Mark Borsuk & Robert Clemen & Lynn Maguire & Kenneth Reckhow, 2001. "Stakeholder Values and Scientific Modeling in the Neuse River Watershed," Group Decision and Negotiation, Springer, vol. 10(4), pages 355-373, July.
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    1. Leilei Pan & Lixu Qin & Simon X. Yang & Jiangping Shuai, 2008. "A Neural Network‐Based Method for Risk Factor Analysis of West Nile Virus," Risk Analysis, John Wiley & Sons, vol. 28(2), pages 487-496, April.
    2. Joseph W. Zabinski & Kelsey J. Pieper & Jacqueline MacDonald Gibson, 2018. "A Bayesian Belief Network Model Assessing the Risk to Wastewater Workers of Contracting Ebola Virus Disease During an Outbreak," Risk Analysis, John Wiley & Sons, vol. 38(2), pages 376-391, February.

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