School of Mathematical Sciences, Dalian University of Technology, 116024, Dalian, China.
School of Control Science and Engineering, Dalian University of Technology, 116024, Dalian, China.
BMC Infect Dis. 2022 Jul 27;22(1):648. doi: 10.1186/s12879-022-07636-4.
During the early stage of the COVID-19 pandemic, many countries implemented non-pharmaceutical interventions (NPIs) to control the transmission of SARS-CoV-2, the causative pathogen of COVID-19. Among those NPIs, stay-at-home and quarantine measures were widely adopted and enforced. Understanding the effectiveness of stay-at-home and quarantine measures can inform decision-making and control planning during the ongoing COVID-19 pandemic and for future disease outbreaks.
In this study, we use mathematical models to evaluate the impact of stay-at-home and quarantine measures on COVID-19 spread in four cities that experienced large-scale outbreaks in the spring of 2020: Wuhan, New York, Milan, and London. We develop a susceptible-exposed-infected-removed (SEIR)-type model with components of self-isolation and quarantine and couple this disease transmission model with a data assimilation method. By calibrating the model to case data, we estimate key epidemiological parameters before lockdown in each city. We further examine the impact of stay-at-home and quarantine rates on COVID-19 spread after lockdown using counterfactual model simulations.
Results indicate that self-isolation of susceptible population is necessary to contain the outbreak. At a given rate, self-isolation of susceptible population induced by stay-at-home orders is more effective than quarantine of SARS-CoV-2 contacts in reducing effective reproductive numbers [Formula: see text]. Variation in self-isolation and quarantine rates can also considerably affect the duration of outbreaks, attack rates and peak timing. We generate counterfactual simulations to estimate effectiveness of stay-at-home and quarantine measures. Without these two measures, the cumulative confirmed cases could be much higher than reported numbers within 40 days after lockdown in Wuhan, New York, Milan, and London.
Our findings underscore the essential role of stay-at-home orders and quarantine of SARS-CoV-2 contacts during the early phase of the pandemic.
在 COVID-19 大流行早期，许多国家实施了非药物干预（NPIs）措施来控制 SARS-CoV-2 的传播，SARS-CoV-2 是 COVID-19 的病原体。这些非药物干预措施中，居家和隔离措施被广泛采用和执行。了解居家和隔离措施的有效性可以为当前 COVID-19 大流行期间的决策和控制规划以及未来的疾病爆发提供信息。
在这项研究中，我们使用数学模型评估了居家和隔离措施对 2020 年春季四个经历大规模疫情爆发的城市（武汉、纽约、米兰和伦敦）中 COVID-19 传播的影响。我们开发了一个具有自我隔离和检疫组件的易感-暴露-感染-清除（SEIR）型模型，并将该疾病传播模型与数据同化方法相结合。通过将模型校准到病例数据，我们估计了每个城市在封锁前的关键流行病学参数。我们进一步通过反事实模型模拟研究了封锁后居家和隔离率对 COVID-19 传播的影响。
结果表明，易感人群的自我隔离是控制疫情的必要条件。在给定的居家隔离率下，居家令下的易感人群自我隔离比 SARS-CoV-2 接触者的隔离更能有效降低有效繁殖数 [Formula: see text]。自我隔离和检疫率的变化也会对疫情持续时间、发病率和峰值时间产生显著影响。我们生成了反事实模拟来估计居家和隔离措施的有效性。如果没有这两种措施，在武汉、纽约、米兰和伦敦封锁后 40 天内，累计确诊病例可能比报告的数字高出许多。
我们的研究结果强调了在大流行早期实施居家令和 SARS-CoV-2 接触者隔离的重要作用。
