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Modelling the effectiveness of an isolation strategy for managing mpox outbreaks with variable infectiousness profiles

Author

Listed:
  • Yong Dam Jeong

    (Nagoya University
    Pusan National University)

  • William S. Hart

    (Nagoya University
    University of Oxford)

  • Robin N. Thompson

    (University of Oxford)

  • Masahiro Ishikane

    (National Centre for Global Health and Medicine)

  • Takara Nishiyama

    (Nagoya University)

  • Hyeongki Park

    (Nagoya University)

  • Noriko Iwamoto

    (National Centre for Global Health and Medicine)

  • Ayana Sakurai

    (National Centre for Global Health and Medicine)

  • Michiyo Suzuki

    (National Centre for Global Health and Medicine)

  • Kazuyuki Aihara

    (The University of Tokyo)

  • Koichi Watashi

    (National Institute of Infectious Diseases)

  • Eline Op de Coul

    (National Institute for Public Health and the Environment (RIVM))

  • Norio Ohmagari

    (National Centre for Global Health and Medicine)

  • Jacco Wallinga

    (National Institute for Public Health and the Environment (RIVM)
    Leiden University Medical Center (LUMC))

  • Shingo Iwami

    (Nagoya University
    The University of Tokyo
    Kyushu University
    Kyoto University)

  • Fuminari Miura

    (National Institute for Public Health and the Environment (RIVM)
    Ehime University)

Abstract

The global outbreak of mpox in 2022 and subsequent sporadic outbreaks in 2023 highlighted the importance of nonpharmaceutical interventions such as case isolation. Individual variations in viral shedding dynamics may lead to either premature ending of isolation for infectious individuals, or unnecessarily prolonged isolation for those who are no longer infectious. Here, we developed a modeling framework to characterize heterogeneous mpox infectiousness profiles – specifically, when infected individuals cease to be infectious – based on viral load data. We examined the potential effectiveness of three different isolation rules: a symptom-based rule (the current guideline in many countries) and rules permitting individuals to stop isolating after either a fixed duration or following tests that indicate that they are no longer likely to be infectious. Our analysis suggests that the duration of viral shedding ranges from 23 to 50 days between individuals. The risk of infected individuals ending isolation too early was estimated to be 8.8% (95% CI: 6.7–10.5) after symptom clearance and 5.4% (95% CI: 4.1–6.7) after 3 weeks of isolation. While these results suggest that the current standard practice for ending isolation is effective, we found that unnecessary isolation following the infectious period could be reduced by adopting a testing-based rule.

Suggested Citation

  • Yong Dam Jeong & William S. Hart & Robin N. Thompson & Masahiro Ishikane & Takara Nishiyama & Hyeongki Park & Noriko Iwamoto & Ayana Sakurai & Michiyo Suzuki & Kazuyuki Aihara & Koichi Watashi & Eline, 2024. "Modelling the effectiveness of an isolation strategy for managing mpox outbreaks with variable infectiousness profiles," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51143-w
    DOI: 10.1038/s41467-024-51143-w
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    References listed on IDEAS

    as
    1. Yong Dam Jeong & Keisuke Ejima & Kwang Su Kim & Woo Joohyeon & Shoya Iwanami & Yasuhisa Fujita & Il Hyo Jung & Kazuyuki Aihara & Kenji Shibuya & Shingo Iwami & Ana I. Bento & Marco Ajelli, 2022. "Designing isolation guidelines for COVID-19 patients with rapid antigen tests," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Thomas Ash & Antonio M. Bento & Daniel Kaffine & Akhil Rao & Ana I. Bento, 2022. "Disease-economy trade-offs under alternative epidemic control strategies," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    3. Kuhn, E. & Lavielle, M., 2005. "Maximum likelihood estimation in nonlinear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 1020-1038, June.
    4. Thomas Ash & Antonio M. Bento & Daniel Kaffine & Akhil Rao & Ana I. Bento, 2022. "Author Correction: Disease-economy trade-offs under alternative epidemic control strategies," Nature Communications, Nature, vol. 13(1), pages 1-1, December.
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