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A COVID‐19 model for local authorities of the United Kingdom
Journal of the Royal Statistical Society: Series A (Statistics in Society) ; 185(S1), 2022.
Article in English | Web of Science | ID: covidwho-2193233
ABSTRACT
We propose a new framework to model the COVID-19 epidemic of the United Kingdom at the local authority level. The model fits within a general framework for semi-mechanistic Bayesian models of the epidemic based on renewal equations, with some important innovations, including a random walk modelling the reproduction number, incorporating information from different sources, including surveys to estimate the time-varying proportion of infections that lead to reported cases or deaths, and modelling the underlying infections as latent random variables. The model is designed to be updated daily using publicly available data. We envisage the model to be useful for now-casting and short-term projections of the epidemic as well as estimating historical trends. The model fits are available on a public website . The model is currently being used by the Scottish government to inform their interventions.

Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Journal of the Royal Statistical Society: Series A (Statistics in Society) Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Journal of the Royal Statistical Society: Series A (Statistics in Society) Year: 2022 Document Type: Article