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社区和校园 COVID-19 风险不确定性在大学重新开放情景下:基于模型的分析。

Community and Campus COVID-19 Risk Uncertainty Under University Reopening Scenarios: Model-Based Analysis.

机构信息

Healthcare Systems Engineering Institute, Northeastern University, Boston, MA, United States.

出版信息

JMIR Public Health Surveill. 2021 Apr 7;7(4):e24292. doi: 10.2196/24292.

Abstract

BACKGROUND

Significant uncertainty has existed about the safety of reopening college and university campuses before the COVID-19 pandemic is better controlled. Moreover, little is known about the effects that on-campus students may have on local higher-risk communities.

OBJECTIVE

We aimed to estimate the range of potential community and campus COVID-19 exposures, infections, and mortality under various university reopening plans and uncertainties.

METHODS

We developed campus-only, community-only, and campus × community epidemic differential equations and agent-based models, with inputs estimated via published and grey literature, expert opinion, and parameter search algorithms. Campus opening plans (spanning fully open, hybrid, and fully virtual approaches) were identified from websites and publications. Additional student and community exposures, infections, and mortality over 16-week semesters were estimated under each scenario, with 10% trimmed medians, standard deviations, and probability intervals computed to omit extreme outliers. Sensitivity analyses were conducted to inform potential effective interventions.

RESULTS

Predicted 16-week campus and additional community exposures, infections, and mortality for the base case with no precautions (or negligible compliance) varied significantly from their medians (4- to 10-fold). Over 5% of on-campus students were infected after a mean of 76 (SD 17) days, with the greatest increase (first inflection point) occurring on average on day 84 (SD 10.2 days) of the semester and with total additional community exposures, infections, and mortality ranging from 1-187, 13-820, and 1-21 per 10,000 residents, respectively. Reopening precautions reduced infections by 24%-26% and mortality by 36%-50% in both populations. Beyond campus and community reproductive numbers, sensitivity analysis indicated no dominant factors that interventions could primarily target to reduce the magnitude and variability in outcomes, suggesting the importance of comprehensive public health measures and surveillance.

CONCLUSIONS

Community and campus COVID-19 exposures, infections, and mortality resulting from reopening campuses are highly unpredictable regardless of precautions. Public health implications include the need for effective surveillance and flexible campus operations.

摘要

背景

在 COVID-19 疫情得到更好控制之前,重新开放大学校园的安全性存在很大的不确定性。此外,对于在校学生可能对当地高风险社区产生的影响知之甚少。

目的

我们旨在估计在各种大学重新开放计划和不确定性下,校园内和社区内潜在的 COVID-19 暴露、感染和死亡人数的范围。

方法

我们开发了仅校园、仅社区和校园×社区的传染病微分方程和基于代理的模型,输入通过已发表和灰色文献、专家意见和参数搜索算法进行估计。从网站和出版物中确定了校园开放计划(涵盖完全开放、混合和完全虚拟方法)。在每种情况下,估计了 16 周学期内额外的学生和社区暴露、感染和死亡人数,并计算了 10%修剪中位数、标准差和概率区间,以排除极端异常值。进行了敏感性分析以确定潜在的有效干预措施。

结果

在没有预防措施(或可忽略的合规性)的情况下,预测的 16 周校园和额外社区暴露、感染和死亡人数与其中位数(4-10 倍)差异很大。在平均 76 天(标准差 17 天)后,有超过 5%的在校学生感染,最大的增长(第一个拐点)平均发生在学期的第 84 天(标准差 10.2 天),额外的社区暴露、感染和死亡人数分别为每 10000 名居民 1-187、13-820 和 1-21。在两个群体中,重新开放的预防措施将感染减少了 24%-26%,将死亡率降低了 36%-50%。除了校园和社区繁殖数外,敏感性分析表明,干预措施无法主要针对减少结果的幅度和可变性的主导因素,这表明全面的公共卫生措施和监测的重要性。

结论

无论采取何种预防措施,重新开放校园导致的社区和校园 COVID-19 暴露、感染和死亡人数都具有高度的不可预测性。公共卫生的影响包括需要有效的监测和灵活的校园运营。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a86/8030657/4f067da9cb70/publichealth_v7i4e24292_fig1.jpg

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