Individual-based modeling of COVID-19 transmission in college communities
Individual-based modeling of COVID-19 transmission in college communities
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DOI：
10.3934/mbe.2022646
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发表时间：
2022-01-01
影响因子：
2.6
通讯作者：
Gurarie, David
中科院分区：
文献类型：
--
作者：
Huang, Qimin;Ndeffo-Mbah, Martial;Gurarie, David
持续的COVID-19疫情在美国各地造成重大的公共卫生及社会经济挑战。其中包括对教育系统的挑战，大学管理人员正在努力解决如何减轻疾病在大学校园中传播的风险和问题。为了帮助应对这一挑战，我们开发了一个灵活的计算框架，以模拟COVID-19在住宿大学校园中的传播和控制。该模型框架考虑了社会互动、活动、环境和行为风险因素、疾病进展和控制干预措施的异质性。在没有和有干预措施的情况下，如接种疫苗，隔离有症状的病例和检测，缓解战略的疾病传播的贡献进行了探讨。我们表明，即使疫苗接种覆盖率很高（90%），大学校园仍然可能经历相当大的疫情。爆发的规模因潜在的环境和社会行为风险因素而异。用检疫和大规模检测补充疫苗接种对预防或减轻疫情至关重要。虽然我们的定量结果可能是暂时的，我们的模型假设，敏感性分析证实了其定性性质的鲁棒性。
The ongoing COVID-19 pandemic has created major public health and socio-economic challenges across the United States. Among them are challenges to the educational system where college administrators are struggling with the questions of how to mitigate the risk and spread of diseases on their college campus. To help address this challenge, we developed a flexible computational framework to model the spread and control of COVID-19 on a residential college campus. The modeling framework accounts for heterogeneity in social interactions, activities, environmental and behavioral risk factors, disease progression, and control interventions. The contribution of mitigation strategies to disease transmission was explored without and with interventions such as vaccination, quarantine of symptomatic cases, and testing. We show that even with high vaccination coverage (90%) college campuses may still experience sizable outbreaks. The size of the outbreaks varies with the underlying environmental and socio-behavioral risk factors. Complementing vaccination with quarantine and mass testing was shown to be paramount for preventing or mitigating outbreaks. Though our quantitative results are likely provisional on our model assumptions, sensitivity analysis confirms the robustness of their qualitative nature.