J13.8 Ecological Forecasting of West Nile Virus Outbreaks in a High-risk Area of the North-central United States

Tuesday, 12 January 2016: 5:15 PM
Room 228/229 ( New Orleans Ernest N. Morial Convention Center)
Michael C. Wimberly, South Dakota State University, Brookings, SD; and C. L. Merkord, L. Kightlinger, G. Vincent, and M. B. Hildreth

West Nile virus (WNV) is the most widespread and important mosquito-borne pathogen in North America. Since its emergence in the western hemisphere in 1999, human WNV disease has continued to exhibit recurrent outbreaks. Perplexingly, the incidence of this tropical disease has been highest in the cold-temperate climates of the Northern Great Plains (NGP). The spatial and temporal distributions of the vector mosquitoes and bird hosts, and consequently the risk of disease in humans, are strongly influenced by temperature, precipitation, vegetation, soils, and land use. We have utilized satellite remote sensing to map these environmental factors through time and develop models of disease risk. Outbreak years in South Dakota were preceded by warm winters, and WNV cases were most likely to occur during the hottest weeks of summer. Hot spots of persistent WNV transmission within the state were associated with rural land cover as well as patterns of physiography and climate. These models are currently being integrated into the South Dakota Mosquito Early Warning system (SDMIS), an automated WNV outbreak detection system that integrates remotely-sensed environmental indicators with vector abundance and infection data from a statewide mosquito surveillance network. The major goal of this effort is to leverage global environmental monitoring datasets to provide up-to-date, locally relevant information that can improve the effectiveness of mosquito control and disease prevention activities. This system was implemented for the first time during the summer of 2015. We will review the outcomes of this implementation, including the underlying influences of temperature on WNV risk, a preliminary statewide WNV risk map, and dynamic risk predictions made during the 2015 WNV season. Lessons learned as well as plans for future years will be discussed.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner