Infectious disease surveillance needs for the United States: lessons from Covid-19

Area of Science:

• Public Health
• Epidemiology
• Infectious Disease Surveillance

Background:

• The COVID-19 pandemic underscored critical deficiencies in existing infectious disease surveillance and forecasting systems.
• Effective public health guidance and policy rely on robust data for understanding and managing disease spread.

Purpose of the Study:

• To define the requirements for an effective infectious disease surveillance system capable of supporting pandemic decision-making.
• To identify essential data types and elements needed for surveillance, transmission modeling, and public health actions.
• To explore strategies for ensuring data availability and promoting health equity in surveillance efforts.

Main Methods:

• Review of lessons learned from the COVID-19 pandemic in the U.S.
• Analysis of data requirements for informing public health decisions at various governmental levels (state, territorial, local, tribal).
• Examination of data needs for calibrating transmission-dynamic models.

Main Results:

• Identification of specific data types and elements crucial for pandemic surveillance and response.
• Defined range of decisions requiring surveillance data and the necessary data inputs.
• Consideration of actions to ensure data availability and enhance health equity.

Conclusions:

• Strengthening infectious disease surveillance and modeling is essential for evidence-based public health policy.
• A comprehensive approach to data collection and utilization is necessary for effective pandemic preparedness and response.
• Improving surveillance systems can contribute to achieving greater health equity.