Physics & Chemistry of Materials, Los Alamos National Laboratory, USA.
Information Systems & Modeling, Los Alamos National Laboratory, USA; Center for Nonlinear Studies, Los Alamos National Laboratory, USA.
Epidemics. 2022 Dec;41:100632. doi: 10.1016/j.epidem.2022.100632. Epub 2022 Sep 21.
School-age children play a key role in the spread of airborne viruses like influenza due to the prolonged and close contacts they have in school settings. As a result, school closures and other non-pharmaceutical interventions were recommended as the first line of defense in response to the novel coronavirus pandemic (COVID-19).
We used an agent-based model that simulates communities across the United States including daycares, primary, and secondary schools to quantify the relative health outcomes of reopening schools for the period of August 15, 2020 to April 11, 2021. Our simulation was carried out in early September 2020 and was based on the latest (at the time) Centers for Disease Control and Prevention (CDC)'s Pandemic Planning Scenarios released in May 2020. We explored different reopening scenarios including virtual learning, in-person school, and several hybrid options that stratify the student population into cohorts in order to reduce exposure and pathogen spread.
Scenarios where cohorts of students return to school in non-overlapping formats, which we refer to as hybrid scenarios, resulted in significant decreases in the percentage of symptomatic individuals with COVID-19, by as much as 75%. These hybrid scenarios have only slightly more negative health impacts of COVID-19 compared to implementing a 100% virtual learning scenario. Hybrid scenarios can significantly avert the number of COVID-19 cases at the national scale-approximately between 28 M and 60 M depending on the scenario-over the simulated eight-month period. We found the results of our simulations to be highly dependent on the number of workplaces assumed to be open for in-person business, as well as the initial level of COVID-19 incidence within the simulated community.
In an evolving pandemic, while a large proportion of people remain susceptible, reducing the number of students attending school leads to better health outcomes; part-time in-classroom education substantially reduces health risks.
由于学龄儿童在学校环境中长时间且密切接触，他们在传播流感等空气传播病毒方面起着关键作用。因此，学校关闭和其他非药物干预措施被建议作为应对新型冠状病毒大流行（COVID-19）的第一道防线。
我们使用基于代理的模型来模拟美国各地的社区，包括日托、小学和中学，以量化 2020 年 8 月 15 日至 2021 年 4 月 11 日期间重新开放学校的相对健康结果。我们的模拟是在 2020 年 9 月初进行的，基于当时在 2020 年 5 月发布的最新疾病控制与预防中心（CDC）大流行规划情景。我们探索了不同的重新开放情景，包括虚拟学习、面对面学校以及几种分层学生人群的混合选项，以减少接触和病原体传播。
我们称之为混合情景的学生群体以非重叠格式返回学校的情景导致 COVID-19 有症状个体的百分比显著下降，最高可达 75%。与实施 100%虚拟学习情景相比，这些混合情景对 COVID-19 的健康影响略大。混合情景可以显著减少全国范围内 COVID-19 病例的数量，在模拟的八个月期间，大约在 2800 万至 6000 万之间，具体取决于情景。我们发现，我们的模拟结果高度依赖于假设为现场办公的工作场所数量，以及模拟社区中 COVID-19 初始发病率。
在不断演变的大流行中，尽管很大一部分人仍然易受感染，但减少上学的学生人数会带来更好的健康结果；部分课堂教育可显著降低健康风险。
