About Flu Forecasting

Background

Influenza (flu) places a significant disease burden on the U.S. population, but the magnitude and timing of flu activity vary from season to season, making the annual impact of flu uncertain at the beginning of each season. Flu forecasting can help decrease that uncertainty by predicting in advance when and where increases in flu activity will occur.

Unlike CDC's traditional influenza surveillance systems, which measure flu activity while it is occurring, flu forecasting offers the possibility of looking into the future and better planning ahead for changes, such as increases in flu-related hospital admissions or emergency department visits.

About CDC's flu forecasting efforts

CDC's efforts with forecasting began in 2013 with the "Predict the Influenza Season Challenge," a competition that encouraged academic and private-sector researchers to forecast the 2013–2014 flu season. Since then, CDC has collaborated each flu season with researchers on flu forecasting. Participating teams use a variety of data sources and modeling approaches to submit forecasts of near and short-term (e.g., 2 weeks ahead) flu activity. CDC works with forecasting teams and public health partners to identify forecasting targets, evaluate forecast performance, and improve the utility of forecasts for public health decision-making.

Currently, CDC coordinates forecasts of laboratory-confirmed influenza hospital admissions and the percentage of emergency department visits associated with flu each week during the influenza season. These forecasts are based on data reported to CDC's NHSN (National Healthcare Safety Network) and NSSP (National Syndromic Surveillance Program), respectively. Prior to the 2021-2022 season, flu hospitalization forecasts were based on FluSurv-NET data. FluSight has evolved over time as new data sources, forecasting methods, and public health needs have emerged.

How flu forecasts can be used

Flu forecasts can be used to communicate and prepare for changes in flu activity, such as increases in hospitalizations. When forecasts accurately predict flu activity, more effective planning of public health responses to seasonal flu epidemics and future flu pandemics is possible. Flu forecasts can inform messaging to health care providers regarding:

• antiviral treatment allocation,
• preparation for an influx of flu-related emergency department visits or hospitalizations,
• informing the distribution and placement of health care staff, hospital beds and treatment resources.

Forecasting, in conjunction with surveillance and other resources, can help inform public health planning, including preparing for increased demand on health care systems, communicating with health care providers and the public, and promoting prevention and treatment strategies, such as conveying the importance of flu vaccination prior to forecasted increases in flu activity.

Collaborating to understand and improve forecasts

While significant progress has been made in the years following the initial competition, forecasting flu activity remains challenging. Flu viruses are constantly changing, and every flu season tends to be different from the one before it. CDC and participating teams collaborate to identify the best data, methods, and practices for forecasting to support the advancement of the science of flu forecasting and improve its ability to inform public health action.

After each flu season, CDC conducts formal evaluations of flu forecast performance to support the continuous improvement of forecasts. These collaborations are critical to developing a network of forecasters providing results that public health officials can use to guide their work. Over the past decade, the network of FluSight forecasters has grown substantially, with roughly 30 teams contributing forecasts during each week of the 2025-26 influenza season.

FluSight also collaborates directly with state and local partners. In 2017, FluSight began working closely with the Council for State and Territorial Epidemiologists to routinely bring together public health partners and forecasters to

• review forecasting approaches,
• discuss the accuracy of forecasts,
• identify overall challenges and successes, and
• plan for future seasons, such as the additions of new forecasting targets.

Through this collaboration, FluSight also generates a weekly ensemble (aggregation of forecasts from contributing models). Ensembles have been shown to be more robust in their performance than individual models across multiple seasons [Hines et al. 2026, Mathis et al. 2024, FluSight season evaluations].

Selected FluSight publications

• Hines, A.G., Mathis, S.M., Johansson, M.A., Reed, C., Biggerstaff, M. and Borchering, R.K., 2026. A Decade of CDC FluSight Influenza Forecasting. medRxiv, pp.2026-06.
• Davis, J.T., Kaur, G., Hines, A., Ben-Nun, M., Venkatramanan, S., Brooks, L., Mathis, S., Ajelli, M., Litvinova, M., Kummer, A.G. and Ventura, P.C., 2026. Multi-season evaluation and analysis of categorical trend forecasts of influenza hospital admissions in the United States. medRxiv, pp.2026-08.
• Mathis, S.M., Webber, A.E., León, T.M., Murray, E.L., Sun, M., White, L.A., Brooks, L.C., Green, A., Hu, A.J., Rosenfeld, R. and Shemetov, D., 2024. Evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations. Nature Communications, 15(1), p.6289.
• Flu Forecasting Past Season Evaluations | FluSight | CDC

Learn more about forecasting

Behind the Model: Short-term Forecasts to Estimate the Hospital Burden of COVID-19

Modeling Handbook

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