End-of-outbreak declarations are an important component of outbreak response as they indicate that public health and social interventions may be relaxed or lapsed. The present study aimed to assess end-of-outbreak probabilities for clusters of coronavirus disease 2019 (COVID-19) cases detected during the first wave of the COVID-19 pandemic in Japan.
(less transmission on average) and larger k (lower risk of superspreading) will be in effect and end-of-outbreak determinations can be declared with greater confidence. The application of end-of-outbreak probabilities can help distinguish between local extinction and low levels of transmission, and communicating these end-of-outbreak probabilities can help inform public health decision-making with relation to the appropriate use of resources.
>1) leads to greater uncertainty in the probability estimates.
We computed a statistical model for end-of-outbreak determination that accounted for the reporting delay for new cases. Four clusters representing different social contexts and time points during the first wave of the epidemic were selected and their end-of-outbreak probabilities were evaluated.