Liu Quan-Hui, Zhang Juanjuan, Peng Cheng, Litvinova Maria, Huang Shudong, Poletti Piero, Trentini Filippo, Guzzetta Giorgio, Marziano Valentina, Zhou Tao, Viboud Cecile, Bento Ana I, Lv Jiancheng, Vespignani Alessandro, Merler Stefano, Yu Hongjie, Ajelli Marco
College of Computer Science, Sichuan University, Chengdu, China.
School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
medRxiv. 2021 Apr 23:2021.04.18.21255683. doi: 10.1101/2021.04.18.21255683.
There are contrasting results concerning the effect of reactive school closure on SARS-CoV-2 transmission. To shed light on this controversy, here we develop a data-driven computational model of SARS-CoV-2 transmission to investigate mechanistically the effect on COVID-19 outbreaks of school closure strategies based on syndromic surveillance and antigen screening of students. We found that by reactively closing classes based on syndromic surveillance, SARS-CoV-2 infections are reduced by no more than 13.1% (95%CI: 8.6%-20.2 %), due to the low probability of timely symptomatic case identification among the young population. We thus investigated an alternative triggering mechanism based on repeated screening of students using antigen tests. Should population-level social distancing measures unrelated to schools enable maintaining the reproduction number ( ) at 1.3 or lower, an antigen-based screening strategy is estimated to fully prevent COVID-19 outbreaks in the general population. Depending on the contribution of schools to transmission, this strategy can either prevent COVID-19 outbreaks for up to 1.9 or to at least greatly reduce outbreak size in very conservative scenarios about school contribution to transmission. Moving forward, the adoption of antigen-based screenings in schools could be instrumental to limit COVID-19 burden while vaccines continue to roll out through 2021, especially in light of possible continued emergence of SARS-CoV-2 variants.
关于反应性学校关闭对SARS-CoV-2传播的影响，存在相互矛盾的结果。为了阐明这一争议，我们在此开发了一个数据驱动的SARS-CoV-2传播计算模型，以从机制上研究基于学生症状监测和抗原筛查的学校关闭策略对COVID-19疫情的影响。我们发现，通过基于症状监测进行反应性停课，SARS-CoV-2感染最多减少13.1%（95%置信区间：8.6%-20.2%），这是因为在年轻人群中及时识别有症状病例的概率较低。因此，我们研究了一种基于对学生反复进行抗原检测的替代触发机制。如果与学校无关的人群层面的社会距离措施能够使再生数（ ）维持在1.3或更低，那么基于抗原的筛查策略估计可完全预防普通人群中的COVID-19疫情。根据学校对传播的贡献，在关于学校对传播贡献的非常保守的情况下，该策略要么可预防COVID-19疫情长达1.9个月，要么至少能大幅减小疫情规模。展望未来，在2021年疫苗持续推出的过程中，尤其是考虑到SARS-CoV-2变体可能持续出现的情况下，在学校采用基于抗原的筛查可能有助于减轻COVID-19负担。
