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Agent-based modelling of reactive vaccination of workplaces and schools against COVID-19

Author

Listed:
  • Benjamin Faucher

    (Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique)

  • Rania Assab

    (Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique)

  • Jonathan Roux

    (Univ Rennes, EHESP, CNRS, ARENES—UMR 6051)

  • Daniel Levy-Bruhl

    (Santé Publique France)

  • Cécile Tran Kiem

    (Université de Paris, UMR2000, CNRS
    Sorbonne Université)

  • Simon Cauchemez

    (Université de Paris, UMR2000, CNRS)

  • Laura Zanetti

    (Haute Autorité de Santé)

  • Vittoria Colizza

    (Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique
    Tokyo Institute of Technology)

  • Pierre-Yves Boëlle

    (Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique)

  • Chiara Poletto

    (Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique)

Abstract

With vaccination against COVID-19 stalled in some countries, increasing vaccine accessibility and distribution could help keep transmission under control. Here, we study the impact of reactive vaccination targeting schools and workplaces where cases are detected, with an agent-based model accounting for COVID-19 natural history, vaccine characteristics, demographics, behavioural changes and social distancing. In most scenarios, reactive vaccination leads to a higher reduction in cases compared with non-reactive strategies using the same number of doses. The reactive strategy could however be less effective than a moderate/high pace mass vaccination program if initial vaccination coverage is high or disease incidence is low, because few people would be vaccinated around each case. In case of flare-ups, reactive vaccination could better mitigate spread if it is implemented quickly, is supported by enhanced test-trace-isolate and triggers an increased vaccine uptake. These results provide key information to plan an adaptive vaccination rollout.

Suggested Citation

  • Benjamin Faucher & Rania Assab & Jonathan Roux & Daniel Levy-Bruhl & Cécile Tran Kiem & Simon Cauchemez & Laura Zanetti & Vittoria Colizza & Pierre-Yves Boëlle & Chiara Poletto, 2022. "Agent-based modelling of reactive vaccination of workplaces and schools against COVID-19," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29015-y
    DOI: 10.1038/s41467-022-29015-y
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    References listed on IDEAS

    as
    1. Juan Yang & Valentina Marziano & Xiaowei Deng & Giorgio Guzzetta & Juanjuan Zhang & Filippo Trentini & Jun Cai & Piero Poletti & Wen Zheng & Wei Wang & Qianhui Wu & Zeyao Zhao & Kaige Dong & Guangjie , 2021. "Despite vaccination, China needs non-pharmaceutical interventions to prevent widespread outbreaks of COVID-19 in 2021," Nature Human Behaviour, Nature, vol. 5(8), pages 1009-1020, August.
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