A real-time forecasting and estimating system of West Nile virus: a case study of the 2023 WNV outbreak in Colorado, USA
West Nile virus (WNV) is a mosquito-borne arbovirus that remains a persistent public health challenge in the USA, with seasonal outbreaks that can lead to severe cases. In this study, we detail a real-time prediction system for WNV that incorporates an adapted compartment model to account for the transmission dynamics among birds, mosquitoes and humans, including asymptomatic cases and the influence of weather factors. Using data assimilation techniques, we generate weekly WNV case forecasts for Colorado in 2023, providing valuable insights for public health planning. Comparative analyses underscore the enhanced forecast accuracy achieved by integrating weather variables into our models.
Authors
- Caterina Scoglio (ORCID: https://orcid.org/0000-0003-4486-9229)
- Lee W. Cohnstaedt (ORCID: https://orcid.org/0000-0002-7885-081X)
- Chunlin Yi (ORCID: https://orcid.org/0000-0002-1050-9770)
Institutions
- Agricultural Research Service (US)
- United States Department of Agriculture (US)
- Kansas State University (US)
Publication Details
- Journal
- Royal Society Open Science
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1098/rsos.240513
- Citations
- 1
- Primary Topic
- Mosquito-borne diseases and control
- Type
- article
- Field-Weighted Citation Impact
- 0.54
Funders
- National Science Foundation
- U.S. Department of Agriculture
- National Natural Science Foundation of China
- National Institutes of Health
- National Institute of Food and Agriculture
- Biotechnology and Biological Sciences Research Council