Outbreak dynamics of COVID-19 in China and the United States
Outbreak dynamics of COVID-19 in China and the United States
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DOI：
10.1007/s10237-020-01332-5
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发表时间：
2020-04-27
影响因子：
3.5
通讯作者：
Kuhl, Ellen
中科院分区：
文献类型：
--
作者：
Peirlinck, Mathias;Linka, Kevin;Kuhl, Ellen
于二零二零年三月十一日，世界卫生组织宣布2019冠状病毒病COVID-19为全球大流行病。在前所未有的集体努力中，目前正在全世界收集大量数据，以估计这一流行病对卫生系统和全球经济的直接和长期影响。然而，该疾病的确切时间轴、其可传播性以及缓解策略的效果仍不完全清楚。在这里，我们将全球网络模型与本地流行病SEIR模型相结合，以量化中国和美国的COVID-19疫情动态。对于中国的暴发，在n=30个省，我们发现潜伏期为2.56 +/- 0.72天，接触期为1.47 +/- 0.32天，传染期为17.82 +/- 2.95天。我们假设潜伏期和传染期是疾病特异性的，而接触期是行为特异性的，并且可以在不同的省、州或国家之间变化。对于美国暴发的早期阶段，在n=50个州，我们采用了来自中国的疾病特异性值，发现接触期为3.38 +/- 0.69天。我们的网络模型预测，如果没有今天实施的大规模政治缓解策略，美国将面临5.30 +/- 0.95的基本繁殖数，并在2020年5月10日达到全国疫情高峰，感染人数为300万。我们的研究结果表明，数学建模可以帮助估计疫情动态，并提供成功的爆发控制的决策指南。我们预计，我们的模型将成为一个有价值的工具，用于估计疫苗接种的潜力，并量化放松政治措施的影响，包括对低风险人群或整个人群的全面封锁，庇护所和旅行限制。
On March 11, 2020, the World Health Organization declared the coronavirus disease 2019, COVID-19, a global pandemic. In an unprecedented collective effort, massive amounts of data are now being collected worldwide to estimate the immediate and long-term impact of this pandemic on the health system and the global economy. However, the precise timeline of the disease, its transmissibility, and the effect of mitigation strategies remain incompletely understood. Here we integrate a global network model with a local epidemic SEIR model to quantify the outbreak dynamics of COVID-19 in China and the United States. For the outbreak in China, in n=30 provinces, we found a latent period of 2.56 +/- 0.72 days, a contact period of 1.47 +/- 0.32 days, and an infectious period of 17.82 +/- 2.95 days. We postulate that the latent and infectious periods are disease-specific, whereas the contact period is behavior-specific and can vary between different provinces, states, or countries. For the early stages of the outbreak in the United States, in n=50 states, we adopted the disease-specific values from China and found a contact period of 3.38 +/- 0.69 days. Our network model predicts that-without the massive political mitigation strategies that are in place today-the United States would have faced a basic reproduction number of 5.30 +/- 0.95 and a nationwide peak of the outbreak on May 10, 2020 with 3 million infections. Our results demonstrate how mathematical modeling can help estimate outbreak dynamics and provide decision guidelines for successful outbreak control. We anticipate that our model will become a valuable tool to estimate the potential of vaccination and quantify the effect of relaxing political measures including total lockdown, shelter in place, and travel restrictions for low-risk subgroups of the population or for the population as a whole.