Browse by author
Lookup NU author(s): Dr Alis Prusokiene
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2025. The Author(s). BACKGROUND: West Nile virus (WNV) is the most common cause of mosquito-borne disease in the continental USA, with an average of ~1200 severe, neuroinvasive cases reported annually from 2005 to 2021 (range 386-2873). Despite this burden, efforts to forecast WNV disease to inform public health measures to reduce disease incidence have had limited success. Here, we analyze forecasts submitted to the 2022 WNV Forecasting Challenge, a follow-up to the 2020 WNV Forecasting Challenge. METHODS: Forecasting teams submitted probabilistic forecasts of annual West Nile virus neuroinvasive disease (WNND) cases for each county in the continental USA for the 2022 WNV season. We assessed the skill of team-specific forecasts, baseline forecasts, and an ensemble created from team-specific forecasts. We then characterized the impact of model characteristics and county-specific contextual factors (e.g., population) on forecast skill. RESULTS: Ensemble forecasts for 2022 anticipated a season at or below median long-term WNND incidence for nearly all (> 99%) counties. More counties reported higher case numbers than anticipated by the ensemble forecast median, but national caseload (826) was well below the 10-year median (1386). Forecast skill was highest for the ensemble forecast, though the historical negative binomial baseline model and several team-submitted forecasts had similar forecast skill. Forecasts utilizing regression-based frameworks tended to have more skill than those that did not and models using climate, mosquito surveillance, demographic, or avian data had less skill than those that did not, potentially due to overfitting. County-contextual analysis showed strong relationships with the number of years that WNND had been reported and permutation entropy (historical variability). Evaluations based on weighted interval score and logarithmic scoring metrics produced similar results. CONCLUSIONS: The relative success of the ensemble forecast, the best forecast for 2022, suggests potential gains in community ability to forecast WNV, an improvement from the 2020 Challenge. Similar to the previous challenge, however, our results indicate that skill was still limited with general underprediction despite a relative low incidence year. Potential opportunities for improvement include refining mechanistic approaches, integrating additional data sources, and considering different approaches for areas with and without previous cases.
Author(s): Harp RD, Holcomb KM, Retkute R, Prusokiene A, Prusokas A, Ertem Z, Ajelli M, Kummer AG, Litvinova M, Merler S, Piontti APY, Poletti P, Vespignani A, Wilke ABB, Zardini A, Smith KH, Armstrong P, DeFelice N, Keyel A, Shepard J, Smith R, Tyre A, Humphreys J, Cohnstaedt LW, Hosseini S, Scoglio C, Gorris ME, Barnard M, Moser SK, Spencer JA, McCarter MSJ, Lee C, Nolan MS, Barker CM, Staples JE, Nett RJ, Johansson MA
Publication type: Article
Publication status: Published
Journal: Parasites & Vectors
Year: 2025
Volume: 18
Issue: 1
Online publication date: 23/04/2025
Acceptance date: 17/03/2025
Date deposited: 13/05/2025
ISSN (electronic): 1756-3305
Publisher: BioMed Central Ltd
URL: https://doi.org/10.1186/s13071-025-06767-2
DOI: 10.1186/s13071-025-06767-2
Data Access Statement: CDC ArboNET data for WNV cases are publicly available at https://www.cdc.gov/west-nile-virus/data-maps/historic-data.html. The datasets used for this study, as well as analysis coding scripts, are available in the WNV-forecast-data-2022 GitHub repository, https://github.com/cdcepi/WNV-forecast-data-2022/.
PubMed id: 40269898
Altmetrics provided by Altmetric
