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The COVID-19 pandemic has highlighted the need to upgrade systems forinfectious disease surveillance and forecasting and modeling of the spread ofinfection, both of which inform evidence-based public health guidance andpolicies. Here, we discuss requirements for an effective surveillance system tosupport decision making during a pandemic, drawing on the lessons of COVID-19in the U.S., while looking to jurisdictions in the U.S. and beyond to learnlessons about the value of specific data types. In this report, we define therange of decisions for which surveillance data are required, the data elementsneeded to inform these decisions and to calibrate inputs and outputs oftransmission-dynamic models, and the types of data needed to inform decisionsby state, territorial, local, and tribal health authorities. We define actionsneeded to ensure that such data will be available and consider the contributionof such efforts to improving health equity.

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