Multiple Models for Outbreak Decision Support in the Face of Uncertainty.

Significance During infectious disease outbreaks, uncertainty hinders our ability to forecast dynamics and to make critical decisions about management. Motivated by the COVID-19 pandemic, leading agencies have initiated efforts to prepare for future outbreaks, for example, the US Centers for Disease Control and Prevention’s National Center for Forecasting and Outbreak Analytics and the WHO’s Hub for Pandemic and Epidemic Intelligence were recently inaugurated. Critically, such efforts need to inform policy as well as provide insight into expected disease dynamics. We present a validated case study from early in the pandemic, drawing on recommendations to minimize cognitive biases and incorporate decision theory, to illustrate how a policy-focused process could work for urgent, important, time-sensitive outbreak decision making in the face of uncertainty.