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Key Factors Influencing the Incidence of West Nile Virus in Burleigh County, North Dakota

Author

Listed:
  • Hiroko Mori

    (Environmental Science Graduate Program, The Ohio State University, Columbus, OH 43210, USA)

  • Joshua Wu

    (College of Public Health, The Ohio State University, Columbus, OH 43210, USA)

  • Motomu Ibaraki

    (School of Earth Sciences, The Ohio State University, Columbus, OH 43210, USA)

  • Franklin W. Schwartz

    (School of Earth Sciences, The Ohio State University, Columbus, OH 43210, USA)

Abstract

The city of Bismarck, North Dakota has one of the highest numbers of West Nile Virus (WNV) cases per population in the U.S. Although the city conducts extensive mosquito surveillance, the mosquito abundance alone may not fully explain the occurrence of WNV. Here, we developed models to predict mosquito abundance and the number of WNV cases, independently, by statistically analyzing the most important climate and virus transmission factors. An analysis with the mosquito model indicated that the mosquito numbers increase during a warm and humid summer or after a severely cold winter. In addition, river flooding decreased the mosquito numbers. The number of WNV cases was best predicted by including the virus transmission rate, the mosquito numbers, and the mosquito feeding pattern. This virus transmission rate is a function of temperature and increases significantly above 20 °C. The correlation coefficients ( r ) were 0.910 with the mosquito-population model and 0.620 with the disease case model. Our findings confirmed the conclusions of other work on the importance of climatic variables in controlling the mosquito numbers and contributed new insights into disease dynamics, especially in relation to extreme flooding. It also suggested a new prevention strategy of initiating insecticides not only based on mosquito numbers but also 10-day forecasts of unusually hot weather.

Suggested Citation

  • Hiroko Mori & Joshua Wu & Motomu Ibaraki & Franklin W. Schwartz, 2018. "Key Factors Influencing the Incidence of West Nile Virus in Burleigh County, North Dakota," IJERPH, MDPI, vol. 15(9), pages 1-19, September.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:1928-:d:167811
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    References listed on IDEAS

    as
    1. Bryan V. Giordano & Kevin W. Turner & Fiona F. Hunter, 2018. "Geospatial Analysis and Seasonal Distribution of West Nile Virus Vectors (Diptera: Culicidae) in Southern Ontario, Canada," IJERPH, MDPI, vol. 15(4), pages 1-18, March.
    2. Chen-Chih Chen & Tasha Epp & Emily Jenkins & Cheryl Waldner & Philip S. Curry & Catherine Soos, 2013. "Modeling Monthly Variation of Culex tarsalis (Diptera: Culicidae) Abundance and West Nile Virus Infection Rate in the Canadian Prairies," IJERPH, MDPI, vol. 10(7), pages 1-19, July.
    3. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    4. Bree Cummins & Ricardo Cortez & Ivo M Foppa & Justin Walbeck & James M Hyman, 2012. "A Spatial Model of Mosquito Host-Seeking Behavior," PLOS Computational Biology, Public Library of Science, vol. 8(5), pages 1-13, May.
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