Luo Xiao-Feng, Feng Shanshan, Yang Junyuan, Peng Xiao-Long, Cao Xiaochun, Zhang Juping, Yao Meiping, Zhu Huaiping, Li Michael Y, Wang Hao, Jin Zhen
Department of Mathematics, North University of China, Taiyuan, Shanxi, 030051, China.
Complex System Research Center, Shanxi University, Taiyuan, 030006, Shanxi, China.
Infect Dis Model. 2021;6:643-663. doi: 10.1016/j.idm.2021.04.001. Epub 2021 Apr 10.
Nonpharmaceutical interventions (NPIs), particularly contact tracing isolation and household quarantine, play a vital role in effectively bringing the Coronavirus Disease 2019 (COVID-19) under control in China. The pairwise model, has an inherent advantage in characterizing those two NPIs than the classical well-mixed models. Therefore, in this paper, we devised a pairwise epidemic model with NPIs to analyze COVID-19 outbreak in China by using confirmed cases during February 3rd-22nd, 2020. By explicitly incorporating contact tracing isolation and family clusters caused by household quarantine, our model provided a good fit to the trajectory of COVID-19 infections. We calculated the reproduction number = 1.345 (95 CI: 1.230 - 1.460) for Hubei province and = 1.217 (95 CI: 1.207 - 1.227) for China (except Hubei). We also estimated the peak time of infections, the epidemic duration and the final size, which are basically consistent with real observation. We indicated by simulation that the traced high-risk contacts from incubated to susceptible decrease under NPIs, regardless of infected cases. The sensitivity analysis showed that reducing the exposure of the susceptible and increasing the clustering coefficient bolster COVID-19 control. With the enforcement of household quarantine, the reproduction number and the epidemic prevalence declined effectively. Furthermore, we obtained the resumption time of work and production in China (except Hubei) on 10th March and in Hubei at the end of April 2020, respectively, which is broadly in line with the actual time. Our results may provide some potential lessons from China on the control of COVID-19 for other parts of the world.
非药物干预措施（NPIs），尤其是接触者追踪隔离和家庭隔离，在中国有效控制2019年冠状病毒病（COVID-19）方面发挥了至关重要的作用。与经典的均匀混合模型相比，成对模型在描述这两种非药物干预措施方面具有内在优势。因此，在本文中，我们设计了一个包含非药物干预措施的成对流行病模型，利用2020年2月3日至22日的确诊病例来分析中国的COVID-19疫情爆发情况。通过明确纳入接触者追踪隔离和家庭隔离导致的家庭聚集情况，我们的模型很好地拟合了COVID-19感染轨迹。我们计算出湖北省的再生数(R_0 = 1.345)（95%置信区间：1.230 - 1.460），中国（不包括湖北）的再生数(R_0 = 1.217)（95%置信区间：1.207 - 1.227）。我们还估计了感染的峰值时间、疫情持续时间和最终规模，这些结果与实际观察基本一致。我们通过模拟表明，在非药物干预措施下，无论感染病例如何，从潜伏期追踪到的高风险接触者转变为易感者的数量都会减少。敏感性分析表明，减少易感者的暴露并提高聚集系数有助于控制COVID-19。随着家庭隔离措施的实施，再生数和疫情流行率有效下降。此外，我们分别得出中国（不包括湖北）于2020年3月10日以及湖北于2020年4月底恢复工作和生产的时间，这与实际时间大致相符。我们的结果可能为世界其他地区控制COVID-19提供一些来自中国的潜在经验教训。
