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加拿大安大略省 COVID-19 传播及其在人群中缓解策略的数学建模。

Mathematical modelling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada.

机构信息

Dalla Lana School of Public Health (Tuite, Fisman), University of Toronto, Ont.; Department of Population Medicine (Greer), University of Guelph, Guelph, Ont.

出版信息

CMAJ. 2020 May 11;192(19):E497-E505. doi: 10.1503/cmaj.200476. Epub 2020 Apr 8.

Abstract

BACKGROUND

Physical-distancing interventions are being used in Canada to slow the spread of severe acute respiratory syndrome coronavirus 2, but it is not clear how effective they will be. We evaluated how different nonpharmaceutical interventions could be used to control the coronavirus disease 2019 (COVID-19) pandemic and reduce the burden on the health care system.

METHODS

We used an age-structured compartmental model of COVID-19 transmission in the population of Ontario, Canada. We compared a base case with limited testing, isolation and quarantine to scenarios with the following: enhanced case finding, restrictive physical-distancing measures, or a combination of enhanced case finding and less restrictive physical distancing. Interventions were either implemented for fixed durations or dynamically cycled on and off, based on projected occupancy of intensive care unit (ICU) beds. We present medians and credible intervals from 100 replicates per scenario using a 2-year time horizon.

RESULTS

We estimated that 56% (95% credible interval 42%-63%) of the Ontario population would be infected over the course of the epidemic in the base case. At the epidemic peak, we projected 107 000 (95% credible interval 60 760-149 000) cases in hospital (non-ICU) and 55 500 (95% credible interval 32 700-75 200) cases in ICU. For fixed-duration scenarios, all interventions were projected to delay and reduce the height of the epidemic peak relative to the base case, with restrictive physical distancing estimated to have the greatest effect. Longer duration interventions were more effective. Dynamic interventions were projected to reduce the proportion of the population infected at the end of the 2-year period and could reduce the median number of cases in ICU below current estimates of Ontario's ICU capacity.

INTERPRETATION

Without substantial physical distancing or a combination of moderate physical distancing with enhanced case finding, we project that ICU resources would be overwhelmed. Dynamic physical distancing could maintain health-system capacity and also allow periodic psychological and economic respite for populations.

摘要

背景

加拿大正在采取保持社交距离的干预措施来减缓严重急性呼吸综合征冠状病毒 2 的传播,但尚不清楚这些措施的效果如何。我们评估了不同的非药物干预措施如何用于控制 2019 年冠状病毒病(COVID-19)大流行并减轻卫生保健系统的负担。

方法

我们使用了加拿大安大略省人群中 COVID-19 传播的年龄结构隔室模型。我们将有限的检测、隔离和检疫的基本情况与以下情况进行了比较:增强病例发现、限制保持社交距离的措施或增强病例发现和限制较少的保持社交距离的组合。干预措施要么是固定持续时间实施,要么根据重症监护病房(ICU)床位的预计占用情况循环开/关。我们在 2 年的时间范围内,对每个方案的 100 次重复进行中位数和可信区间分析。

结果

我们估计,在基本情况下,安大略省将有 56%(95%可信区间 42%-63%)的人口在流行期间感染。在流行高峰期,我们预计将有 107000 例(95%可信区间 60760-149000)住院(非 ICU)和 55500 例(95%可信区间 32700-75200)在 ICU。对于固定持续时间的方案,所有干预措施都预计将延迟和降低流行高峰期的高峰,限制保持社交距离的措施估计效果最大。干预措施持续时间越长效果越好。动态干预措施预计将减少在 2 年期间结束时感染的人口比例,并可能将 ICU 病例的中位数数量降低到安大略省 ICU 容量的当前估计值以下。

解释

如果没有大量的保持社交距离或中等程度的保持社交距离与增强病例发现相结合,我们预计 ICU 资源将不堪重负。动态保持社交距离可以维持卫生保健系统的能力,还可以为人群提供定期的心理和经济缓解。

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