A hybrid stochastic model and its Bayesian identification for infectious disease screening in a university campus with application to massive COVID-19 screening at the University of Liege.

ABSTRACT: Amid the COVID-19 pandemic, universities are implementing various prevention and mitigation measures. Identifying and isolating infectious individuals by using screening testing is one such a measure that can contribute to reducing spread. Here, we propose a hybrid stochastic model for infectious disease transmission in a university campus with screening testing and its surrounding community. Based on a compartmental modeling strategy, this hybrid stochastic model represents the evolution of the infectious disease and its transmission using continuous-time stochastic dynamics, and it represents the screening testing as discrete stochastic events. We also develop, in a Bayesian framework, the identification of parameters of this hybrid stochastic model, including transmission rates. These p

SUBMITTER: Arnst M 

PROVIDER: S-EPMC8925303 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature