Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples

Area of Science:

• Public Health
• Epidemiology
• Infectious Disease Modeling

Background:

• Infectious disease forecasting is crucial for predicting seasonal epidemics and future pandemics.
• Accurate forecasts enhance public health preparedness and mitigation efforts.

Purpose of the Study:

• To provide an overview of infectious disease forecasting.
• To highlight applications in public health decision-making.
• To discuss developing best practices for forecast methodology, applications, and communication.

Main Methods:

• Utilizing the Centers for Disease Control and Prevention (CDC) influenza forecasting challenges as a case study.
• Examining collaborative challenges for forecasting influenza-like illness (ILI) timing, intensity, and trajectory.
• Reviewing additional efforts in state-level and hospitalization forecasts for influenza and other infectious diseases.

Main Results:

• Understanding forecast methodology, interpretation, and past performance is essential for integration into public health decision-making.
• CDC's collaborative challenges have advanced influenza forecasting since 2013-14.
• Ongoing initiatives aim to improve forecasting for various infectious diseases.

Conclusions:

• Collaborative forecasting efforts, exemplified by the CDC's influenza challenges, are vital for advancing infectious disease forecasting science.
• Continued development of best practices will enhance the utility of forecasts in public health.