School of Environmental Sciences, University of Guelph, Guelph, ON, Canada, N1G 2W1.
School of Environmental Sciences, University of Guelph, Guelph, ON, Canada, N1G 2W1.
Epidemics. 2022 Jun;39:100557. doi: 10.1016/j.epidem.2022.100557. Epub 2022 Apr 6.
Simulation models from the early COVID-19 pandemic highlighted the urgency of applying non-pharmaceutical interventions (NPIs), but had limited empirical data. Here we use data from 2020-2021 to retrospectively model the impact of NPIs in Ontario, Canada. Our model represents age groups and census divisions in Ontario, and is parameterized with epidemiological, testing, demographic, travel, and mobility data. The model captures how individuals adopt NPIs in response to reported cases. We compare a scenario representing NPIs introduced within Ontario (closures of workplaces/schools, reopening of schools/workplaces with NPIs in place, individual-level NPI adherence) to counterfactual scenarios wherein alternative strategies (e.g. no closures, reliance on individual NPI adherence) are adopted to ascertain the extent to which NPIs reduced cases and deaths. Combined school/workplace closure and individual NPI adoption reduced the number of deaths in the best-case scenario for the case fatality rate (CFR) from 178548 [CI: 171845, 185298] to 3190 [CI: 3095, 3290] in the Spring 2020 wave. In the Fall 2020/Winter 2021 wave, the introduction of NPIs in workplaces/schools reduced the number of deaths from 20183 [CI: 19296, 21057] to 4102 [CI: 4075, 4131]. Deaths were several times higher in the worst-case CFR scenario. Each additional 9-16 (resp. 285-578) individuals who adopted NPIs in the first wave prevented one additional infection (resp., death). Our results show that the adoption of NPIs prevented a public health catastrophe. A less comprehensive approach, employing only closures or individual-level NPI adherence, would have resulted in a large number of cases and deaths.
从早期 COVID-19 大流行的模拟模型中突出强调了实施非药物干预(NPI)的紧迫性,但这些模型的经验数据有限。在这里,我们使用 2020-2021 年的数据来回顾性模拟加拿大安大略省的 NPI 影响。我们的模型代表了安大略省的年龄组和普查分区,并使用流行病学、检测、人口统计学、旅行和流动性数据进行参数化。该模型捕捉了个人如何针对报告的病例采取 NPI。我们将代表在安大略省引入的 NPI 的情景(工作场所/学校关闭、重新开放学校/工作场所并实施 NPI、个人 NPI 坚持)与替代策略(例如不关闭、依赖个人 NPI 坚持)的反事实情景进行比较,以确定 NPI 减少病例和死亡的程度。在春季 2020 波中,综合学校/工作场所关闭和个人 NPI 采用将病例死亡率(CFR)的最佳情况下的死亡人数从 178548[CI:171845,185298]减少到 3190[CI:3095,3290]。在 2020 年秋季/2021 年冬季波中,工作场所/学校的 NPI 引入将死亡人数从 20183[CI:19296,21057]减少到 4102[CI:4075,4131]。在最坏情况下的 CFR 情景中,死亡人数要高得多。在第一波中每增加 9-16(分别为 285-578)个人采取 NPI,就可以预防一次额外的感染(分别为,死亡)。我们的结果表明,NPI 的采用避免了公共卫生灾难。采用仅关闭或个人 NPI 坚持的方法,则会导致大量病例和死亡。