West Nile virus (WNV) is a virus transmitted by infected Culex spp that can produce asymptomatic infections and neuroinvasive disease in humans and selected animals. According to the World Health Organization, WNV cases have been reported across Africa, Europe, North America, the Middle East, and West Asia. In order to address this global health challenge, integrated vector management has traditionally provided a decision-making framework to coordinate vector control strategies, health promotion activities, and capacity building. Moving forward, innovative data and technology, such as the use of Earth observations, can complement current fieldwork strategies related to integrated vector management.
In the United States, the Northern Great Plains is a high-risk geographic region for WNV transmission. Of the 50 states, South Dakota has the highest reported long-term incidence of WNV neuroinvasive disease. As part of a NASA Health and Air Quality Applications project, Michael Wimberly (University of Oklahoma) and his team aimed to develop a WNV early warning system in South Dakota. Using data from Land Data Assimilation Systems (NLDAS) daily weather, long-range weather forecasts, mosquito infections, and human WNV cases, his team developed computer code for the Arbovirus Monitoring and Prediction (ArboMAP) system. ArboMAP combines meteorological data access via Google Earth Engine with modeling and automated report generation tools implemented with the R programming software. Released in January 2019, this code is freely available via GitHub and is currently being applied for WNV forecasting in South Dakota and other neighboring states.
