Decision analysis support for evaluating transmission risk of COVID-19 in places where people gather.

Background: The coronavirus diseases 2019 (COVID-19) pandemic has presented an unprecedented public health challenge. Prior to vaccination, non-pharmaceutical interventions, including closures, were necessary to help control the epidemic. With the arrival of variants of concern and insufficient population vaccination coverage, ongoing evaluation of transmission risk in settings and the use of non-pharmaceutical interventions are necessary to help control the epidemic.

A model of COVID-19 propagation based on a gamma subordinated negative binomial branching process.

We build a parsimonious Crump-Mode-Jagers continuous time branching process of COVID-19 propagation based on a negative binomial process subordinated by a gamma subordinator. By focusing on the stochastic nature of the process in small populations, our model provides decision making insight into mitigation strategies as an outbreak begins. Our model accommodates contact tracing and isolation, allowing for comparisons between different types of intervention.