Abstract：
The movement of populations between locations and activities can result in complex transmission dynamics, posing significant challenges in controlling infectious diseases like COVID-19. Notably, networks of care homes create an ecosystem where staff and visitor movement acts as a vector for disease transmission, contributing to the heightened risk for their vulnerable communities. Care homes in the UK were disproportionately affected by the first wave of the COVID-19 pandemic, accounting for almost half of COVID-19 deaths during the period of 6th March - 15th June 2020 and so there is a pressing need to explore modelling approaches suitable for such systems. We develop a generic compartmental Susceptible - Exposed - Infectious - Recovered - Dead (SEIRD) metapopulation model, with care home residents, care home workers, and the general population modelled as subpopulations, interacting on a network describing their mixing habits. We illustrate the model application by analysing the spread of COVID-19 over the first wave of the COVID-19 pandemic in the NHS Lothian health board, Scotland. We explicitly model the outbreak\'s reproduction rate and care home visitation level over time for each subpopulation and execute a data fit and sensitivity analysis, focusing on parameters responsible for inter-subpopulation mixing: staff-sharing, staff shift patterns and visitation. The results from our sensitivity analysis show that restricting staff sharing between homes and staff interaction with the general public would significantly mitigate the disease burden. Our findings indicate that protecting care home staff from disease, coupled with reductions in staff-sharing across care homes and expedient cancellations of visitations, can significantly reduce the size of outbreaks in care home settings.
摘要：
人口在地点和活动之间的移动会导致复杂的传播动态，在控制COVID-19等传染病方面构成重大挑战。值得注意的是,疗养院网络创造了一个生态系统，工作人员和访客的流动充当疾病传播的媒介，加剧了他们脆弱社区的风险。英国的养老院受到第一波COVID-19大流行的影响不成比例，占2020年3月6日至6月15日期间COVID-19死亡人数的近一半，因此迫切需要探索适合此类系统的建模方法。我们开发了一个通用的隔室易感-暴露-感染-恢复-死亡（SEIRD）群体模型，有养老院的居民，养老院的工作人员,一般人口被建模为亚种群，在描述他们混合习惯的网络上互动。我们通过分析NHS洛锡安卫生委员会第一波COVID-19大流行期间COVID-19的传播来说明模型的应用，苏格兰。我们明确地对每个亚群随时间的爆发率和护理家庭访视水平进行建模，并执行数据拟合和敏感性分析，侧重于负责亚种群间混合的参数：工作人员共享，员工轮班模式和访问。我们敏感性分析的结果表明，限制员工在家庭之间的共享以及员工与公众的互动将显着减轻疾病负担。我们的研究结果表明，保护养老院工作人员免受疾病侵害，加上养老院工作人员分担的减少和便利地取消探视，可以显着减少养老院环境中爆发的规模。
