Analysis of the risk and pre-emptive control of viral outbreaks accounting for within-host dynamics: SARS-CoV-2 as a case study

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  • Hart, William S.
    Mathematical Institute, University of Oxford; lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University
  • Park, Hyeongki
    lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University
  • Jeong, Yong Dam
    lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University; Department of Mathematics, Pusan National University
  • 吉村, 雷輝
    lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University; Department of Scientific Computing, Pukyong National University
  • Yoshimura, Raiki
    lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University
  • Thompson, Robin N.
    Mathematical Institute, University of Oxford; Mathematics Institute, University of Warwick; Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick
  • 岩見, 真吾
    lnterdisciplinary Biology Laboratory, Division of Natural Science, Graduate School of Science, Nagoya University; Institute of Mathematics for Industry, Kyushu University; Institute for the Advanced Study of Human Biology, Kyoto University; Interdisciplinary Theoretical and Mathematical Sciences Program, RIKEN; NEXT- Ganken Program, Japanese Foundation for Cancer Research; Science Groove Inc.

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説明

In the era of living with COVID-19, the risk of localised SARS-CoV-2 outbreaks remains. Here, we develop a multiscale modelling framework for estimating the local outbreak risk for a viral disease (the probability that a major outbreak results from a single case introduced into the population), accounting for within-host viral dynamics. Compared to population-level models previously used to estimate outbreak risks, our approach enables more detailed analysis of how the risk can be mitigated through pre-emptive interventions such as antigen testing. Considering SARS-CoV-2 as a case study, we quantify the within-host dynamics using data from individuals with omicron variant infections. We demonstrate that regular antigen testing reduces, but may not eliminate, the outbreak risk, depending on characteristics of local transmission. In our baseline analysis, daily antigen testing reduces the outbreak risk by 45% compared to a scenario without antigen testing. Additionally, we show that accounting for heterogeneity in within-host dynamics between individuals affects outbreak risk estimates and assessments of the impact of antigen testing. Our results therefore highlight important factors to consider when using multiscale models to design pre-emptive interventions against SARS-CoV-2 and other viruses.

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詳細情報 詳細情報について

  • CRID
    1050579289345173376
  • ISSN
    10916490
    00278424
  • HANDLE
    2433/285496
  • 本文言語コード
    en
  • 資料種別
    journal article
  • データソース種別
    • IRDB
    • OpenAIRE

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