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
  • [21] Mathematical Modeling for Spread and Control of COVID-19
    Yang B.
    Yu Z.
    Cai Y.
    Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University, 2021, 55 (11): : 162 - 172
  • [22] Modeling COVID-19 spread in small colleges
    Bahl, Riti
    Eikmeier, Nicole
    Fraser, Alexandra
    Junge, Matthew
    Keesing, Felicia
    Nakahata, Kukai
    Reeves, Lily
    PLOS ONE, 2021, 16 (08):
  • [23] PolSIRD: Modeling Epidemic Spread Under Intervention PoliciesAnalyzing the First Wave of COVID-19 in the USA
    Nitin Kamra
    Yizhou Zhang
    Sirisha Rambhatla
    Chuizheng Meng
    Yan Liu
    Journal of Healthcare Informatics Research, 2021, 5 : 231 - 248
  • [24] Reciprocal association between voting and the epidemic spread of COVID-19: observational and dynamic modeling study
    Zeitoun, Jean-David
    Faron, Matthieu
    Manternach, Sylvain
    Fourquet, Jerome
    Lavielle, Marc
    Lefevre, Jeremie H.
    EUROPEAN JOURNAL OF PUBLIC HEALTH, 2021, 31 (06): : 1265 - 1270
  • [25] The challenges of modeling and forecasting the spread of COVID-19
    Bertozzi, Andrea L.
    Franco, Elisa
    Mohler, George
    Short, Martin B.
    Sledge, Daniel
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2020, 117 (29) : 16732 - 16738
  • [26] Mathematical Modelling of an Epidemic Based on Covid-19 Spread Functions
    Molodetska, Kateryna
    Tymonin, Yuriy
    IDDM 2021: INFORMATICS & DATA-DRIVEN MEDICINE: PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON INFORMATICS & DATA-DRIVEN MEDICINE (IDDM 2021), 2021, 3038 : 77 - 85
  • [27] Impact of media reports on the early spread of COVID-19 epidemic
    Yan, Qinling
    Tang, Yingling
    Yan, Dingding
    Wang, Jiaying
    Yang, Linqian
    Yang, Xinpei
    Tang, Sanyi
    JOURNAL OF THEORETICAL BIOLOGY, 2020, 502
  • [28] Is visiting Qom spread CoVID-19 epidemic in the Middle East?
    Al-Rousan, N.
    Al-Najjar, H.
    EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES, 2020, 24 (10) : 5813 - 5818
  • [29] Equation for epidemic spread with the quarantine measures: application to COVID-19
    Trigger, S. A.
    Czerniawski, E. B.
    PHYSICA SCRIPTA, 2020, 95 (10)
  • [30] Discovering Correlations between the COVID-19 Epidemic Spread and Climate
    Lin, Shaofu
    Fu, Yu
    Jia, Xiaofeng
    Ding, Shimin
    Wu, Yongxing
    Huang, Zhou
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2020, 17 (21) : 1 - 14