估计学校关闭对74个国家的COVID-19动态的影响:模型分析
Romain Ragonnet1, Angus E Hughes1, David S Shipman1
1School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
PLoS medicine
|January 21, 2025
概括
在COVID-19期间学校关闭在大多数国家减少了医疗负担,但在一些国家增加了死亡率. 数学建模揭示了病毒传播和人口统计学的各种影响,强调需要细微的政策.
科学领域:
- 流行病学 流行病学
- 数学建模的数学建模
- 公共卫生政策 公共卫生政策
背景情况:
- 在2019年冠状病毒疾病 (COVID-19) 流行期间,学校关闭是主要策略.
- 关闭学校对病毒传播,死亡率和医疗保健菌株的影响仍然不清楚.
- 传统的观察性研究在评估这些广泛影响方面存在局限性.
研究的目的:
- 用数学建模量化学校关闭对全球COVID-19流行病的影响.
- 为了比较模拟的流行病结果,并没有学校关闭从2020-2022.
- 分析严重急性呼吸系统综合征冠状病毒2 (SARS-CoV-2) 感染,死亡和医院占用率的影响.
主要方法:
- 一个数学模型模拟了74个国家的COVID-19流行病,整合了2020-2022年的数据和学校关闭时间表.
- 一个反事实场景假设学校在整个研究期间保持开放.
- 模拟将SARS-CoV-2感染,死亡和医院占用压力与不同场景进行了比较.
主要成果:
- 学校关闭导致研究 (2020-2022) 大多数国家中适度至显著的负担减轻.
- 在97%的国家,高峰医院占用压力下降,降幅高达89% (巴西),但在一些国家增加 (印度尼西亚,19%).
- 在大多数国家,COVID-19死亡人数下降了 (例如,泰国减少了73%) 但在12%增加了 (例如,英国增加了7%),这与免疫力学变化和变种影响有关.
结论:
- 学校关闭对COVID-19动态产生了微妙的影响,在大多数国家减少了影响,但在少数国家造成了负面结果.
- 关键机制包括人口免疫力和感染人口结构的变化,特别是在变种激增期间.
- 研究结果强调了在未来的公共卫生政策决策中需要考虑变异性不可预测性和人口变化.
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