Research

Our research on West Nile virus (WNV) in the Northern Great Plains has explored the entomological and environmental factors that influence the risk of WNV transmission to humans. Amplification of the virus in spring and early summer determines the infection rate in vector mosquito populations, and the infection rate is, in turn, a key predictor of the risk of WNV transmission to humans (Wittry 2009). The spatial and temporal distributions of the vector mosquitoes and bird hosts, and consequently the risk of disease in humans, are strongly influenced by a variety of environmental factors including temperature, precipitation, vegetation, soils, and land use (Wimberly et al. 2008Chuang et al. 2011Wimberly et al. 2014). These relationships can be quantified using mathematical models and applied to develop maps of WNV risk and forecast the probability of future WNV outbreaks (Chuang and Wimberly 2012Chuang et al. 2012aChuang et al. 2012b, Liu et al. 2015). Current research is focused on improving these predictive models by incorporating multiple sources of information from mosquito monitoring, epidemiological surveillance of human cases, and environmental data from earth observing satellites.

Journal Articles and Book Chapters

 

  1. Wimberly, M. C., M. B. Hildreth, S. P. Boyte, E. Lindquist, and L. Kightlinger. 2008. Ecological niche of the 2003 West Nile virus epidemic in the northern Great Plains of the United States. PLoS One 3: e3744.
  2. Wey, C. L., J. Griesse, L. Kightlinger, and M. C. Wimberly. 2009. Geographic variability in geocoding success for West Nile virus cases in South Dakota, USA. Health & Place 15: 1108-1114.
  3. Chuang, T. Hildreth, M. B., VanRoekel, D. L., and M. C. Wimberly. 2011. Weather and land cover influences on mosquito populations in Sioux Falls, South Dakota. Journal of Medical Entomology 48: 669-679.
  4. Wimberly M.C., E. J. Lindquist, and C. L. Wey. 2011. Analysis of the 2002 Equine West Nile Virus outbreak in South Dakota using GIS and spatial statistics, Pages 191-206 In: GIS Applications in Agriculture, Volume 3: Invasive Species (Ed. Clay S.A.). CRC Press, Boca Raton, FL.
  5. Chuang, T., Hockett, C. W., Kightlinger, L., and M. C. Wimberly. 2012a. Landscape-level spatial patterns of West Nile virus risk in the northern Great Plains. American Journal of Tropical Medicine and Hygiene 86: 724-731.
  6. Chuang T., G. M. Henebry, J. S. Kimball, D. L. VanRoekel, M. B. Hildreth, and M. C. Wimberly.2012b. Satellite microwave remote sensing for environmental modeling of mosquito population dynamics. Remote Sensing of Environment 125: 147-156.
  7. Chuang T., and M. C. Wimberly. 2012. Remote Sensing of Climatic Anomalies and West Nile Virus Incidence in the Northern Great Plains of the United States. PLOS One 7:e46882.
  8. Wimberly, M. C., P. Giacomo, L. Kightlinger, and M. B. Hildreth. 2013. Spatio-temporal epidemiology of human West Nile virus disease in South Dakota . International Journal of Environmental Research and Public Health 10: 5584-5602.
  9. Wimberly, M. C., A. Lamsal, P. Giacomo, and T. Chuang. 2014. Regional variation of climatic influences on West Nile virus outbreaks in the United States. American Journal of Tropical Medicine and Hygiene. 91: 677-684.
  10. Liu, Y., J. Hu, I. Snell-Feikema, M. S. VanBemmel, A. Lamsal, M. C. Wimberly. 2015. Software to facilitate remote sensing data access for disease early warning systems. Environmental Modelling and Software 74: 238-246.
  11. Davis J. K., Vincent G., Hildreth M. B., Kightlinger L., Carlson C., and M. C. Wimberly. Integrating Environmental Monitoring and Mosquito Surveillance to Predict Vector-borne Disease: Prospective Forecasts of a West Nile Virus Outbreak. PLOS Currents Outbreaks. 2017 May 23 . Edition 1. doi: 10.1371/currents.outbreaks.90e80717c4e67e1a830f17feeaaf85de.

 

Theses and Dissertations

 

  1. Wittry, M. J. 2009. Temporal Patterns Affecting Mosquito Transmission of West Nile virus to Humans in South Dakota. M.S. Thesis, Biology & Microbiology, South Dakota State University.
  2. Lamsal, A. 2011. Evaluating Geospatial Visualization Methods for West Nile Virus Risk Mapping. M.S. Thesis, Geography, South Dakota State University.
  3. Friesz, A M. 2012. Effects of Bird Community Structure on West Nile Virus incidence in the Northern Great Plains. M.S. Thesis, Geography, South Dakota State University.