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Remote Sensing of Climatic Anomalies and West Nile Virus Incidence in the Northern Great Plains of the United States

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  • Ting-Wu Chuang
  • Michael C Wimberly

Abstract

The northern Great Plains (NGP) of the United States has been a hotspot of West Nile virus (WNV) incidence since 2002. Mosquito ecology and the transmission of vector-borne disease are influenced by multiple environmental factors, and climatic variability is an important driver of inter-annual variation in WNV transmission risk. This study applied multiple environmental predictors including land surface temperature (LST), the normalized difference vegetation index (NDVI) and actual evapotranspiration (ETa) derived from Moderate-Resolution Imaging Spectroradiometer (MODIS) products to establish prediction models for WNV risk in the NGP. These environmental metrics are sensitive to seasonal and inter-annual fluctuations in temperature and precipitation, and are hypothesized to influence mosquito population dynamics and WNV transmission. Non-linear generalized additive models (GAMs) were used to evaluate the influences of deviations of cumulative LST, NDVI, and ETa on inter-annual variations of WNV incidence from 2004–2010. The models were sensitive to the timing of spring green up (measured with NDVI), temperature variability in early spring and summer (measured with LST), and moisture availability from late spring through early summer (measured with ETa), highlighting seasonal changes in the influences of climatic fluctuations on WNV transmission. Predictions based on these variables indicated a low WNV risk across the NGP in 2011, which is concordant with the low case reports in this year. Environmental monitoring using remote-sensed data can contribute to surveillance of WNV risk and prediction of future WNV outbreaks in space and time.

Suggested Citation

  • Ting-Wu Chuang & Michael C Wimberly, 2012. "Remote Sensing of Climatic Anomalies and West Nile Virus Incidence in the Northern Great Plains of the United States," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-10, October.
  • Handle: RePEc:plo:pone00:0046882
    DOI: 10.1371/journal.pone.0046882
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    References listed on IDEAS

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    1. Senay, G.B. & Budde, M.E. & Verdin, J.P., 2011. "Enhancing the Simplified Surface Energy Balance (SSEB) approach for estimating landscape ET: Validation with the METRIC model," Agricultural Water Management, Elsevier, vol. 98(4), pages 606-618, February.
    2. Roger J. Marshall, 1991. "Mapping Disease and Mortality Rates Using Empirical Bayes Estimators," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 40(2), pages 283-294, June.
    3. David J. Rogers & Sarah E. Randolph & Robert W. Snow & Simon I. Hay, 2002. "Satellite imagery in the study and forecast of malaria," Nature, Nature, vol. 415(6872), pages 710-715, February.
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    1. Luong Thi Nguyen & Huy Xuan Le & Dong Thanh Nguyen & Ha Quang Ho & Ting-Wu Chuang, 2020. "Impact of Climate Variability and Abundance of Mosquitoes on Dengue Transmission in Central Vietnam," IJERPH, MDPI, vol. 17(7), pages 1-16, April.
    2. Alexander E. Platonov & Vladimir A. Tolpin & Kristina A. Gridneva & Anton V. Titkov & Olga V. Platonova & Nadezhda M. Kolyasnikova & Luca Busani & Giovanni Rezza, 2014. "The Incidence of West Nile Disease in Russia in Relation to Climatic and Environmental Factors," IJERPH, MDPI, vol. 11(2), pages 1-22, January.
    3. Michael C. Wimberly & Paolla Giacomo & Lon Kightlinger & Michael B. Hildreth, 2013. "Spatio-Temporal Epidemiology of Human West Nile Virus Disease in South Dakota," IJERPH, MDPI, vol. 10(11), pages 1-19, October.
    4. Kevin A. Caillouët & Charles W. Robertson & David C. Wheeler & Nicholas Komar & Lesley P. Bulluck, 2013. "Vector Contact Rates on Eastern Bluebird Nestlings Do Not Indicate West Nile Virus Transmission in Henrico County, Virginia, USA," IJERPH, MDPI, vol. 10(12), pages 1-14, November.
    5. Johnny A. Uelmen & Charles Brokopp & Jonathan Patz, 2020. "A 15 Year Evaluation of West Nile Virus in Wisconsin: Effects on Wildlife and Human Health," IJERPH, MDPI, vol. 17(5), pages 1-24, March.

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