Outbreaks in care homes may lead to substantial disease burden if not mitigated.
Outbreaks in care homes may lead to substantial disease burden if not mitigated.
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DOI：
10.1098/rstb.2020.0269
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发表时间：
2021-07-19
期刊：
影响因子：
--
通讯作者：
University of Manchester COVID-19 Modelling Group and the Public Health England Modelling Team
中科院分区：
文献类型：
--
作者：
Hall I;Lewkowicz H;Webb L;House T;Pellis L;Sedgwick J;Gent N;University of Manchester COVID-19 Modelling Group and the Public Health England Modelling Team
2020年3月初，英国养老院报告的新冠肺炎疫情数量迅速上升。由于疗养院居民的并存疾病增加，因此新冠肺炎结果更差，因此我们必须了解这种增加及其未来的影响。我们演示了SIS模型的使用，其中每个疗养院都是一个感染单元，能够要么对疫情敏感(S)，要么处于活跃的疫情(I)。我们使用广义加性模型来逼近养老院疫情增长率的趋势，并发现与增长率恒定的模型相比，增长率与当前养老院疫情数量成正比的模型的拟合度要更好。使用从依赖于疫情的增长率中发现的参数，我们预测，在没有干预的情况下，英国养老院将有73%的疫情流行，这是一个合理的最坏情况规划假设。本文是“影响英国早期新冠肺炎疫情应对的模型”主题的一部分。
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’.
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影响因子：
19
作者：
Ganyani, Tapiwa;Kremer, Cecile;Hens, Niel
通讯作者：
Hens, Niel
DOI：
10.1098/rstb.2020.0264
发表时间：
2021-07-19
期刊：
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
影响因子：
--
作者：
Pellis L;Scarabel F;Stage HB;Overton CE;Chappell LHK;Fearon E;Bennett E;Lythgoe KA;House TA;Hall I;University of Manchester COVID-19 Modelling Group
通讯作者：
University of Manchester COVID-19 Modelling Group
影响因子：
4.2
作者：
Finnie, T. J. R.;Copley, V. R.;Leach, S.
通讯作者：
Leach, S.
影响因子：
8.8
作者：
Mizumoto, Kenji;Chowell, Gerardo
通讯作者：
Chowell, Gerardo