Modeling shield immunity to reduce COVID-19 epidemic spread

被引:0
|
作者
Joshua S. Weitz
Stephen J. Beckett
Ashley R. Coenen
David Demory
Marian Dominguez-Mirazo
Jonathan Dushoff
Chung-Yin Leung
Guanlin Li
Andreea Măgălie
Sang Woo Park
Rogelio Rodriguez-Gonzalez
Shashwat Shivam
Conan Y. Zhao
机构
[1] Georgia Institute of Technology,School of Biological Sciences
[2] Georgia Institute of Technology,School of Physics
[3] Georgia Institute of Technology,Center for Microbial Dynamics and Infection
[4] Georgia Institute of Technology,Interdisciplinary Graduate Program in Quantitative Biosciences
[5] McMaster University,Department of Biology
[6] McMaster University,DeGroote Institute for Infectious Disease Research
[7] Princeton University,Department of Ecology and Evolutionary Biology
[8] Georgia Institute of Technology,School of Electrical and Computer Engineering
来源
Nature Medicine | 2020年 / 26卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
The COVID-19 pandemic has precipitated a global crisis, with more than 1,430,000 confirmed cases and more than 85,000 confirmed deaths globally as of 9 April 20201–4. Mitigation and suppression of new infections have emerged as the two predominant public health control strategies5. Both strategies focus on reducing new infections by limiting human-to-human interactions, which could be both socially and economically unsustainable in the long term. We have developed and analyzed an epidemiological intervention model that leverages serological tests6,7 to identify and deploy recovered individuals8 as focal points for sustaining safer interactions via interaction substitution, developing what we term ‘shield immunity’ at the population scale. The objective of a shield immunity strategy is to help to sustain the interactions necessary for the functioning of essential goods and services9 while reducing the probability of transmission. Our shield immunity approach could substantively reduce the length and reduce the overall burden of the current outbreak, and can work synergistically with social distancing. The present model highlights the value of serological testing as part of intervention strategies, in addition to its well-recognized roles in estimating prevalence10,11 and in the potential development of plasma-based therapies12–15.
引用
收藏
页码:849 / 854
页数:5
相关论文
共 50 条
  • [1] Modeling shield immunity to reduce COVID-19 epidemic spread
    Weitz, Joshua S.
    Beckett, Stephen J.
    Coenen, Ashley R.
    Demory, David
    Dominguez-Mirazo, Marian
    Dushoff, Jonathan
    Leung, Chung-Yin
    Li, Guanlin
    Magalie, Andreea
    Park, Sang Woo
    Rodriguez-Gonzalez, Rogelio
    Shivam, Shashwat
    Zhao, Conan Y.
    NATURE MEDICINE, 2020, 26 (06) : 849 - +
  • [2] Modeling shield immunity to reduce COVID-19 transmission in long-term care facilities
    Lucia-Sanz, Adriana
    Magalie, Andreea
    Rodriguez-Gonzalez, Rogelio
    Leung, Chung-Yin
    Weitz, Joshua S.
    ANNALS OF EPIDEMIOLOGY, 2023, 77 : 44 - 52
  • [3] Is spread of COVID-19 a chaotic epidemic?
    Jones, Andrew
    Strigul, Nikolay
    CHAOS SOLITONS & FRACTALS, 2021, 142
  • [4] Modeling the complete spatiotemporal spread of the COVID-19 epidemic in mainland China
    Hu, Bisong
    Ning, Pan
    Qiu, Jingyu
    Tao, Vincent
    Devlin, Adam Thomas
    Chen, Haiying
    Wang, Jinfeng
    Lin, Hui
    INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES, 2021, 110 : 247 - 257
  • [5] DYNAMICAL MODELING AND OPTIMAL CONTROL STRATEGIES TO REDUCE THE SPREAD OF COVID-19
    Karton, Widowati
    Rahmasari, Shafira m.
    Utomo, Robertus heri soelistyo
    Triyana, Eka
    COMMUNICATIONS IN MATHEMATICAL BIOLOGY AND NEUROSCIENCE, 2024,
  • [6] Early epidemic spread, percolation and Covid-19
    Oliveira, Goncalo
    JOURNAL OF MATHEMATICAL BIOLOGY, 2020, 81 (4-5) : 1143 - 1168
  • [7] Factors associated with the spread of the Covid-19 epidemic
    不详
    CONFINS-REVUE FRANCO-BRESILIENNE DE GEOGRAPHIE-REVISTA FRANCO-BRASILEIRA DE GEOGRAFIA, 2020, 46
  • [8] Early epidemic spread, percolation and Covid-19
    Gonçalo Oliveira
    Journal of Mathematical Biology, 2020, 81 : 1143 - 1168
  • [9] GeoSpread: An Epidemic Spread Modeling Tool for COVID-19 Using Mobility Data
    Schmedding, Anna
    Yang, Lishan
    Pinciroli, Riccardo
    Smirni, Evgenia
    ACM International Conference Proceeding Series, 2022, : 125 - 131
  • [10] Modeling and Visualizing the Dynamic Spread of Epidemic Diseases-The COVID-19 Case
    Zachilas, Loukas
    Benos, Christos
    APPLIEDMATH, 2024, 4 (01): : 1 - 19