Bayesian spatial modelling of localised SARS-CoV-2 transmission through mobility networks across England.

ABSTRACT: In the early phases of growth, resurgent epidemic waves of SARS-CoV-2 incidence have been characterised by localised outbreaks. Therefore, understanding the geographic dispersion of emerging variants at the start of an outbreak is key for situational public health awareness. Using telecoms data, we derived mobility networks describing the movement patterns between local authorities in England, which we have used to inform the spatial structure of a Bayesian BYM2 model. Surge testing interventions can result in spatio-temporal sampling bias, and we account for this by extending the BYM2 model to include a random effect for each timepoint in a given area. Simulated-scenario modelling and real-world analyses of each variant that became dominant in England were conducted using our BYM2 model a

SUBMITTER: Ward T 

PROVIDER: S-EPMC10756685 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature