Outbreak dynamics of COVID-19 in China and the United States

被引:0
|
作者
Mathias Peirlinck
Kevin Linka
Francisco Sahli Costabal
Ellen Kuhl
机构
[1] Stanford University,Departments of Mechanical Engineering and Bioengineering
[2] Pontificia Universidad Catolica de Chile,Department of Mechanical and Metallurgical Engineering, School of Engineering and Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences
关键词
Coronavirus; COVID-19; Epidemiology modeling; SEIR model; Network model;
D O I
暂无
中图分类号
学科分类号
摘要
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\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$n=30$$\end{document} 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\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$n=50$$\end{document} 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.
引用
收藏
页码:2179 / 2193
页数:14
相关论文
共 50 条
  • [31] Quantifying human mobility behaviour changes during the COVID-19 outbreak in the United States
    Yixuan Pan
    Aref Darzi
    Aliakbar Kabiri
    Guangchen Zhao
    Weiyu Luo
    Chenfeng Xiong
    Lei Zhang
    Scientific Reports, 10
  • [32] Generalized k-means in GLMs with applications to the outbreak of COVID-19 in the United States
    Zhang, Tonglin
    Lin, Ge
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2021, 159
  • [33] COVID-19 pandemic in the United States
    Bergquist, Savannah
    Otten, Thomas
    Sarich, Nick
    HEALTH POLICY AND TECHNOLOGY, 2020, 9 (04) : 623 - 638
  • [34] Quantifying human mobility behaviour changes during the COVID-19 outbreak in the United States
    Pan, Yixuan
    Darzi, Aref
    Kabiri, Aliakbar
    Zhao, Guangchen
    Luo, Weiyu
    Xiong, Chenfeng
    Zhang, Lei
    SCIENTIFIC REPORTS, 2020, 10 (01)
  • [35] COVID-19 and Leisure in the United States
    Anderson, Stephen
    WORLD LEISURE JOURNAL, 2020, 62 (04) : 352 - 356
  • [36] COVID-19 and cancer in the United States
    Grob, Sydney
    Mucci, Lorelei A.
    EPIDEMIOLOGIA & PREVENZIONE, 2020, 44 (5-6): : 26 - 27
  • [37] The United States Responds to COVID-19
    Todd, Betsy
    AMERICAN JOURNAL OF NURSING, 2020, 120 (05) : 15 - 15
  • [38] Successful containment of COVID-19: the WHO-Report on the COVID-19 outbreak in China
    Salzberger, Bernd
    Glueck, Thomas
    Ehrenstein, Boris
    INFECTION, 2020, 48 (02) : 151 - 153
  • [39] Successful containment of COVID-19: the WHO-Report on the COVID-19 outbreak in China
    Bernd Salzberger
    Thomas Glück
    Boris Ehrenstein
    Infection, 2020, 48 : 151 - 153
  • [40] Outbreak analysis with a logistic growth model shows COVID-19 suppression dynamics in China
    Zou, Yi
    Pan, Stephen
    Zhao, Peng
    Han, Lei
    Wang, Xiaoxiang
    Hemerik, Lia
    Knops, Johannes
    van der Werf, Wopke
    PLOS ONE, 2020, 15 (06):