Investigating time, strength, and duration of measures in controlling the spread of COVID-19 using a networked meta-population model

被引:20
作者
Zhang, Jiang [1 ]
Dong, Lei [2 ,3 ]
Zhang, Yanbo [4 ]
Chen, Xinyue [5 ]
Yao, Guiqing [6 ]
Han, Zhangang [1 ]
机构
[1] Beijing Normal Univ, Sch Syst Sci, Beijing 100875, Peoples R China
[2] Peking Univ, Sch Earth & Space Sci, Inst Remote Sensing & Geog Informat Syst, Beijing 100871, Peoples R China
[3] MIT, Senseable City Lab, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[4] Arizona State Univ, Sch Earth & Space Explorat, Tempe, AZ 85281 USA
[5] Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Peoples R China
[6] Univ Leicester, Dept Hlth Sci, Leicester LE1 7RH, Leics, England
基金
中国国家自然科学基金;
关键词
COVID-19; Meta-population epidemic model; Network dynamics; Intervention; CORONAVIRUS;
D O I
10.1007/s11071-020-05769-2
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Policy makers around the world are facing unprecedented challenges in making decisions on when and what degrees of measures should be implemented to tackle the COVID-19 pandemic. Here, using a nationwide mobile phone dataset, we developed a networked meta-population model to simulate the impact of intervention in controlling the spread of the virus in China by varying the effectiveness of transmission reduction and the timing of intervention start and relaxation. We estimated basic reproduction number and transition probabilities between health states based on reported cases. Our model demonstrates that both the time of initiating an intervention and its effectiveness had a very large impact on controlling the epidemic, and the current Chinese intense social distancing intervention has reduced the impact substantially but would have been even more effective had it started earlier. The optimal duration of the control measures to avoid resurgence was estimated to be 2 months, although would need to be longer under less effective controls.
引用
收藏
页码:1789 / 1800
页数:12
相关论文
共 44 条
  • [1] ANDERSON R M, 1991
  • [2] [Anonymous], 2020, People's Daily.
  • [3] Baidu, 2020, BAID MIGR PROJ
  • [4] Multiscale mobility networks and the spatial spreading of infectious diseases
    Balcan, Duygu
    Colizza, Vittoria
    Goncalves, Bruno
    Hu, Hao
    Ramasco, Jose J.
    Vespignani, Alessandro
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2009, 106 (51) : 21484 - 21489
  • [5] Natural Human Mobility Patterns and Spatial Spread of Infectious Diseases
    Belik, Vitaly
    Geisel, Theo
    Brockmann, Dirk
    [J]. PHYSICAL REVIEW X, 2011, 1 (01): : 1 - 5
  • [6] The Hidden Geometry of Complex, Network-Driven Contagion Phenomena
    Brockmann, Dirk
    Helbing, Dirk
    [J]. SCIENCE, 2013, 342 (6164) : 1337 - 1342
  • [7] Clinical Characteristics of Pregnant Women with Covid-19 in Wuhan, China
    Chen, Lian
    Li, Qin
    Zheng, Danni
    Jiang, Hai
    Wei, Yuan
    Zou, Li
    Feng, Ling
    Xiong, Guoping
    Sun, Guoqiang
    Wang, Haibo
    Zhao, Yangyu
    Qiao, Jie
    [J]. NEW ENGLAND JOURNAL OF MEDICINE, 2020, 382 (25)
  • [8] Chen R.T.Q., 2018, Advances in Neural Information Processing Systems, P6572
  • [9] China Central Television, 2020, WUH CUT INT TRAFF AI
  • [10] Chinazzi M, 2020, SCIENCE, V368, P395, DOI [10.1126/science.aba9757, 10.1101/2020.02.09.20021261]