Climatic/Weather Influences on Annual Caseload and Seasonal Timing of West Nile Virus

NOAA’s environmental prediction mission has applied atmosphere/ocean/earth-system prediction models to guide decisions across many applications including transportation, public safety, energy, water supply, and many others. NOAA and the U.S. Centers for Disease Control and Prevention (CDC) have strengthened their collaboration towards a future goal of improving predictions of environmentally-driven health problems, including mosquito-borne diseases such as West Nile virus (WNV) disease. WNV is the leading cause of mosquito-borne illness in the continental United States and can result in severe neuroinvasive disease. Since its introduction into the country in 1999, the disease has become endemic, causing >28,000 reported severe neuroinvasive disease cases and >2,600 reported deaths. WNV forecasting presents a tremendous challenge because of complex interactions between environmental factors and biological processes. Forecasts of WNV disease burden at various spatial and temporal scales are not yet reliable enough for effective deployment of targeted public health preparations. CDC and NOAA are working toward an effective national-scale WNV prediction capability. Toward this goal and to assess potential but widely varying weather-climate drivers of WNV burden across the United States, we combined high-resolution statistically downscaled gridded near-surface meteorological data with WNV case data provided by the CDC ArboNET national surveillance system. Disease caseload and environmental variables of interest (e.g., 2-m air temperature, precipitation, Palmer Drought Severity Index) were aggregated onto a spatially uniform hexagonal grid and analyzed at a regional level to identify critical weather-climate anomalies (over periods of a week to months) and thresholds that impact both the timing of seasonal cycle and total annual neuroinvasive disease cases. Upcoming work aims to build upon this analysis by projecting identified empirical relationships onto short-term and subseasonal-to-seasonal weather forecasts to increase the lead time of WNV forecasts. The NOAA-CDC collaboration links scientific understanding of physical and biological processes toward this difficult forecast problem.