Predicting COVID-19 Transmission to Inform the Management of Mass Events: Model-Based Approach.

ABSTRACT:

Background

Modelling COVID-19 transmission at live events and public gatherings is essential to controlling the probability of subsequent outbreaks and communicating to participants their personalized risk. Yet, despite the fast-growing body of literature on COVID-19 transmission dynamics, current risk models either neglect contextual information including vaccination rates or disease prevalence or do not attempt to quantitatively model transmission.

Objective

This paper attempted to bridge this gap by providing informative risk metrics for live public events, along with a measure of their uncertainty.

Methods

Building upon existing models, our approach ties together 3 main components: (1) reliable modelling of the number of infectious cases at the time of the event,

SUBMITTER: Donnat C 

PROVIDER: S-EPMC8638785 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature