Epidemiological impact of revoking mask-wearing recommendation on COVID-19 transmission in Tokyo, Japan

IF 8.8 3区 医学 Q1 Medicine Infectious Disease Modelling Pub Date : 2024-08-10 DOI:10.1016/j.idm.2024.08.002
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Abstract

Despite the global implementation of COVID-19 mitigation measures, the disease continues to maintain transmission. Although mask wearing became one of the key measures for preventing the transmission of COVID-19 early in the pandemic period, many countries have relaxed the mandatory or recommended wearing of masks. The objective of the present study was to estimate the epidemiological impact of removing the mask-wearing recommendation in Japan. We developed a model to assess the consequences of declining mask-wearing coverage after the government revoked its recommendation in February 2023. The declining mask-wearing coverage was estimated using serial cross-sectional data, and a mathematical model was devised to determine the age-specific incidence of COVID-19 using the observed case count in Tokyo from week of October 3, 2022 to October 30, 2023. We explored model-based counterfactual scenarios to measure hypothetical situations in which the mask-wearing coverage decreases or increases relative to the observed coverage. The results show that mask-wearing coverage declined from 97% to 69% by the week of October 30, 2023, and that if the mask-wearing recommendation had continued, 427 lives could have been saved in Tokyo. If the mask-wearing coverage had declined to 25% of the observed level, the model suggests there might have been 1587 additional deaths. Thus, revoking the mask-wearing recommendation had a substantial epidemiological impact. In future pandemics, our proposed approach could provide a real-time quantification of the effects of relaxing countermeasures.

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取消戴口罩建议对日本东京 COVID-19 传播的流行病学影响
尽管 COVID-19 减缓措施已在全球范围内实施,但该疾病仍在继续传播。尽管在大流行初期,佩戴口罩已成为预防 COVID-19 传播的关键措施之一,但许多国家已放松了强制或建议佩戴口罩的规定。本研究的目的是估计日本取消戴口罩建议的流行病学影响。我们建立了一个模型来评估政府于 2023 年 2 月取消戴口罩建议后口罩佩戴率下降的后果。我们利用序列横截面数据对戴口罩覆盖率下降进行了估计,并设计了一个数学模型,利用 2022 年 10 月 3 日至 2023 年 10 月 30 日这一周在东京观察到的病例数来确定 COVID-19 的特定年龄发病率。我们探索了基于模型的反事实情景,以衡量戴口罩覆盖率相对于观察到的覆盖率减少或增加的假设情况。结果表明,到 2023 年 10 月 30 日这一周,佩戴口罩的覆盖率从 97% 降至 69%,如果继续推荐佩戴口罩,东京可能会挽救 427 条生命。如果佩戴口罩的覆盖率下降到观察到的水平的 25%,模型显示可能会增加 1587 例死亡。因此,取消佩戴口罩的建议会对流行病学产生重大影响。在未来的大流行病中,我们提出的方法可以实时量化放松对策的效果。
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来源期刊
Infectious Disease Modelling
Infectious Disease Modelling Mathematics-Applied Mathematics
CiteScore
17.00
自引率
3.40%
发文量
73
审稿时长
17 weeks
期刊介绍: Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.
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