Deckart Christine, Stich Heribert
Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie - IBE, Ludwig-Maximilians-Universität München, München (Bayern), Deutschland.
Pettenkofer School of Public Health, München (Bayern), Deutschland.
Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2024 Nov;67(11):1306-1314. doi: 10.1007/s00103-024-03956-9. Epub 2024 Sep 30.
The rapid global spread of the SARS-CoV‑2 virus during the COVID-19 pandemic led to widespread non-pharmaceutical interventions, such as school closures, to curb infections. This study investigates the influence of school closures on the number of new infections to reduce the existing knowledge gap in this area.
The effect of school closures starting on 16 December 2020, was quantified using COVID-19 infection data from the district and city of Landshut in Bavaria between November 2020 and January 2021. An interrupted time series (ITS) analysis was performed to analyze daily new infections among 6-18 year olds and the entire population in the region before and after the school closures using a negative binomial regression model.
The analysis showed that the trend of daily new COVID-19 infections among 6-18 year olds significantly decreased after the school closures (incidence rate ratio (IRR) 0.93; 95% confidence interval (CI): 0.89-0.96; p < 0.001). This was also true for the entire study population (IRR 0.95; 95% CI: 0.93-0.97; p < 0.001).
In the context of various concurrent measures to contain the COVID-19 pandemic, the study provides evidence for a significant association between school closures and reduced COVID-19 infections. By optimizing the existing incomplete evidence base on the role of school closures in pandemic control, this finding can support involved stakeholders and contribute to strengthening future approaches to pandemic prevention.
在新冠疫情期间，严重急性呼吸综合征冠状病毒2（SARS-CoV-2）病毒在全球迅速传播，导致了广泛的非药物干预措施，如学校关闭，以遏制感染。本研究调查学校关闭对新感染病例数的影响，以缩小该领域现有的知识差距。
利用2020年11月至2021年1月巴伐利亚州兰茨胡特地区和城市的新冠病毒感染数据，对2020年12月16日开始的学校关闭的影响进行了量化。采用中断时间序列（ITS）分析，使用负二项回归模型分析学校关闭前后该地区6至18岁儿童和全体人群的每日新增感染情况。
分析表明，学校关闭后，6至18岁儿童中新冠病毒每日新增感染趋势显著下降（发病率比（IRR）为0.93；95%置信区间（CI）：0.89-0.96；p<0.001）。整个研究人群的情况也是如此（IRR为0.95；95%CI：0.93-0.97；p<0.001）。
在为控制新冠疫情而采取的各种并行措施的背景下，本研究为学校关闭与新冠病毒感染减少之间的显著关联提供了证据。通过优化现有的关于学校关闭在疫情防控中作用的不完整证据基础，这一发现可以为相关利益攸关方提供支持，并有助于加强未来的疫情预防方法。
