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A COVID-19 model for local authorities of the United Kingdom.
Mishra, Swapnil; Scott, James A; Laydon, Daniel J; Zhu, Harrison; Ferguson, Neil M; Bhatt, Samir; Flaxman, Seth; Gandy, Axel.
Afiliação
  • Mishra S; MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA) Imperial College London London UK.
  • Scott JA; Department of Mathematics Imperial College London London UK.
  • Laydon DJ; MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA) Imperial College London London UK.
  • Zhu H; Department of Mathematics Imperial College London London UK.
  • Ferguson NM; MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA) Imperial College London London UK.
  • Bhatt S; MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA) Imperial College London London UK.
  • Flaxman S; Department of Mathematics Imperial College London London UK.
  • Gandy A; Department of Mathematics Imperial College London London UK.
J R Stat Soc Ser A Stat Soc ; 185(Suppl 1): S86-S95, 2022 Nov.
Article em En | MEDLINE | ID: mdl-38607865
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 https//imperialcollegelondon.github.io/covid19local. The model is currently being used by the Scottish government to inform their interventions.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article