Individual-based modeling of COVID-19 transmission in college communities

Durward Cator; Qimin Huang; Anirban Mondal; Martial Ndeffo-Mbah; David Gurarie; Durward Cator; Qimin Huang; Anirban Mondal; Martial Ndeffo-Mbah; David Gurarie

doi:10.3934/mbe.2022646

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 12: 13861-13877. doi: 10.3934/mbe.2022646

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Individual-based modeling of COVID-19 transmission in college communities

1.
Department of Electrical and Computer Engineering, Texas A & M University, College Station, TX 77840, USA
2.
Department of Mathematics, Applied Mathematics, and Statistics, Case Western Reserve University, Cleveland, OH 44106, USA
3.
Department of Veterinary and Integrative Biosciences, College of Veterinary and Biomedical Sciences, Texas A & M University, College Station, TX 77840, USA
4.
Center for Global Health and Diseases, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
^#Joint last authors

Received: 30 June 2022 Revised: 23 August 2022 Accepted: 01 September 2022 Published: 20 September 2022

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.
- COVID-19,
- individual-based model,
- non-pharmaceutical interventions,
- vaccine,
- college
Citation: Durward Cator, Qimin Huang, Anirban Mondal, Martial Ndeffo-Mbah, David Gurarie. Individual-based modeling of COVID-19 transmission in college communities[J]. Mathematical Biosciences and Engineering, 2022, 19(12): 13861-13877. doi: 10.3934/mbe.2022646

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Abstract

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.

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