Disaster & Emergency Management, School of Administrative Studies and Advanced Disaster, Emergency and Rapid-response Simulation, York University, Toronto, Canada.
Department of Mathematics & Statistics, University of Guelph, Guelph, Ontario, Canada.
BMC Public Health. 2021 Jan 12;21(1):125. doi: 10.1186/s12889-020-10153-1.
School testing for SARS-CoV-2 infection has become an important policy and planning issue as schools were reopened after the summer season and as the COVID-19 pandemic continues. Decisions to test or not to test and, if testing, how many tests, how often and for how long, are complex decisions that need to be taken under uncertainty and conflicting pressures from various stakeholders.
We have developed an agent-based model and simulation tool that can be used to analyze the outcomes and effectiveness of different testing strategies and scenarios in schools with various number of classrooms and class sizes. We have applied a modified version of a standard SEIR disease transmission model that includes symptomatic and asymptomatic infectious populations, and that incorporates feasible public health measures. We also incorporated a pre-symptomatic phase for symptomatic cases. Every day, a random number of students in each class are tested. If they tested positive, they are placed in self-isolation at home when the test results are provided. Last but not least, we have included options to allow for full testing or complete self-isolation of a classroom with a positive case.
We present sample simulation results for parameter values based on schools and disease related information, in the Province of Ontario, Canada. The findings show that testing can be an effective method in controlling the SARS-CoV-2 infection in schools if taken frequently, with expedited test results and self-isolation of infected students at home.
Our findings show that while testing cannot eliminate the risk and has its own challenges, it can significantly control outbreaks when combined with other measures, such as masks and other protective measures.
随着夏季学期结束后学校重新开学，以及 COVID-19 大流行的持续，对 SARS-CoV-2 感染进行学校检测已成为一项重要的政策和规划问题。是否进行检测以及如果进行检测，检测多少、多久以及多少次，都是在不确定和来自各方利益相关者的压力下做出的复杂决策。
我们开发了一个基于代理的模型和模拟工具，可用于分析不同的测试策略和场景在具有不同教室数量和班级规模的学校中的结果和效果。我们对标准 SEIR 疾病传播模型进行了修改，纳入了有症状和无症状的感染人群，并纳入了可行的公共卫生措施。我们还纳入了有症状病例的预症状期。每天，每个班级的随机数量的学生接受检测。如果他们的检测结果呈阳性，则在收到检测结果时在家中进行自我隔离。最后但并非最不重要的是，我们还纳入了对阳性病例进行全班检测或完全自我隔离的选项。
我们根据安大略省加拿大的学校和疾病相关信息展示了参数值的模拟结果。研究结果表明，如果频繁进行检测，并加快检测结果和在家中隔离感染学生，检测可以成为控制学校中 SARS-CoV-2 感染的有效方法。
我们的研究结果表明，虽然检测不能消除风险，并且有其自身的挑战，但结合其他措施（如口罩和其他保护措施），它可以显著控制疫情爆发。
