Department of Mathematics, University of Manchester, Manchester, UK.
The Alan Turing Institute, London, UK.
Philos Trans R Soc Lond B Biol Sci. 2021 Jul 19;376(1829):20200269. doi: 10.1098/rstb.2020.0269. Epub 2021 May 31.
The number of COVID-19 outbreaks reported in UK care homes rose rapidly in early March of 2020. Owing to the increased co-morbidities and therefore worse COVID-19 outcomes for care home residents, it is important that we understand this increase and its future implications. We demonstrate the use of an SIS model where each nursing home is an infective unit capable of either being susceptible to an outbreak (S) or in an active outbreak (I). We use a generalized additive model to approximate the trend in growth rate of outbreaks in care homes and find the fit to be improved in a model where the growth rate is proportional to the number of current care home outbreaks compared with a model with a constant growth rate. Using parameters found from the outbreak-dependent growth rate, we predict a 73% prevalence of outbreaks in UK care homes without intervention as a reasonable worst-case planning assumption. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.
2020 年 3 月初,英国养老院报告的 COVID-19 疫情迅速增加。由于养老院居民的合并症增加,因此 COVID-19 结果更差,因此了解这种增加及其未来影响非常重要。我们展示了使用 SIS 模型的情况,在该模型中,每个疗养院都是一个具有传染性的单位,要么容易受到疫情爆发(S)的影响,要么处于疫情爆发(I)中。我们使用广义加性模型来近似养老院疫情增长率的趋势,并发现与具有恒定增长率的模型相比,将增长率与当前养老院疫情数量成正比的模型拟合度得到改善。使用从疫情相关增长率中找到的参数,我们预测如果不进行干预,英国养老院的疫情流行率将达到 73%,这是一个合理的最坏情况规划假设。本文是“塑造英国 COVID-19 大流行早期应对措施的建模”专题的一部分。