Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545 USA.
Community Interventions for Infection Control Unit, Centers for Disease Control and Prevention, Atlanta, GA 30329 USA.
Epidemics. 2019 Sep;28:100348. doi: 10.1016/j.epidem.2019.100348. Epub 2019 Jun 12.
We used individual-based computer simulation models at community, regional and national levels to evaluate the likely impact of coordinated pre-emptive school dismissal policies during an influenza pandemic. Such policies involve three key decisions: when, over what geographical scale, and how long to keep schools closed. Our evaluation includes uncertainty and sensitivity analyses, as well as model output uncertainties arising from variability in serial intervals and presumed modifications of social contacts during school dismissal periods. During the period before vaccines become widely available, school dismissals are particularly effective in delaying the epidemic peak, typically by 4-6 days for each additional week of dismissal. Assuming the surveillance is able to correctly and promptly diagnose at least 5-10% of symptomatic individuals within the jurisdiction, dismissals at the city or county level yield the greatest reduction in disease incidence for a given dismissal duration for all but the most severe pandemic scenarios considered here. Broader (multi-county) dismissals should be considered for the most severe and fast-spreading (1918-like) pandemics, in which multi-month closures may be necessary to delay the epidemic peak sufficiently to allow for vaccines to be implemented.
我们使用基于个体的计算机模拟模型，在社区、地区和国家层面上评估在流感大流行期间协调采取先发制人的学校停课政策的可能影响。这些政策涉及三个关键决策：何时、在多大的地理范围内以及关闭学校的时间长短。我们的评估包括不确定性和敏感性分析，以及由于在学校停课期间间隔时间和假定的社会接触变化而产生的模型输出不确定性。在疫苗广泛可用之前，学校停课在延迟疫情高峰期方面特别有效，每次额外停课一周，通常可将高峰期推迟 4-6 天。假设监测能够正确和及时地诊断出管辖范围内至少 5-10%的有症状个体，那么在考虑到的所有大流行情景中，除了最严重的情况外，对于给定的停课时间，市级或县级的停课可最大程度地降低疾病发病率。对于最严重和传播速度最快的（类似于 1918 年的）大流行，应考虑更广泛的（多县）停课，可能需要数月的停课时间，以便使疫情高峰期足够延迟，从而能够实施疫苗接种。
