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Optimal COVID-19 quarantine and testing strategies

Author

Listed:
  • Chad R. Wells

    (Yale School of Public Health)

  • Jeffrey P. Townsend

    (Yale School of Public Health
    Yale University
    Yale University
    Yale University)

  • Abhishek Pandey

    (Yale School of Public Health)

  • Seyed M. Moghadas

    (York University)

  • Gary Krieger

    (NewFields E&E
    University of Colorado Anschutz Medical Campus)

  • Burton Singer

    (University of Florida)

  • Robert H. McDonald

    (Group Health, Safety and Environment; BHP)

  • Meagan C. Fitzpatrick

    (Yale School of Public Health
    University of Maryland School of Medicine)

  • Alison P. Galvani

    (Yale School of Public Health
    Yale University)

Abstract

For COVID-19, it is vital to understand if quarantines shorter than 14 days can be equally effective with judiciously deployed testing. Here, we develop a mathematical model that quantifies the probability of post-quarantine transmission incorporating testing into travel quarantine, quarantine of traced contacts with an unknown time of infection, and quarantine of cases with a known time of exposure. We find that testing on exit (or entry and exit) can reduce the duration of a 14-day quarantine by 50%, while testing on entry shortens quarantine by at most one day. In a real-world test of our theory applied to offshore oil rig employees, 47 positives were obtained with testing on entry and exit to quarantine, of which 16 had tested negative at entry; preventing an expected nine offshore transmission events that each could have led to outbreaks. We show that appropriately timed testing can make shorter quarantines effective.

Suggested Citation

  • Chad R. Wells & Jeffrey P. Townsend & Abhishek Pandey & Seyed M. Moghadas & Gary Krieger & Burton Singer & Robert H. McDonald & Meagan C. Fitzpatrick & Alison P. Galvani, 2021. "Optimal COVID-19 quarantine and testing strategies," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20742-8
    DOI: 10.1038/s41467-020-20742-8
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    Cited by:

    1. Zhongxiang Chen & Zhiquan Shu & Xiuxiang Huang & Ke Peng & Jiaji Pan, 2021. "Modelling Analysis of COVID-19 Transmission and the State of Emergency in Japan," IJERPH, MDPI, vol. 18(13), pages 1-15, June.
    2. Zhou, Xin & Liao, Wenzhu, 2023. "Research on demand forecasting and distribution of emergency medical supplies using an agent-based model," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    3. Eslami, Keyvan & Lee, Hyunju, 2024. "Overreaction and the value of information in a pandemic," European Economic Review, Elsevier, vol. 161(C).
    4. Joren Raymenants & Caspar Geenen & Jonathan Thibaut & Klaas Nelissen & Sarah Gorissen & Emmanuel Andre, 2022. "Empirical evidence on the efficiency of backward contact tracing in COVID-19," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    5. Wang, Haiying & Moore, Jack Murdoch & Small, Michael & Wang, Jun & Yang, Huijie & Gu, Changgui, 2022. "Epidemic dynamics on higher-dimensional small world networks," Applied Mathematics and Computation, Elsevier, vol. 421(C).

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