Individual-based modeling of COVID-19 transmission in college communities
Mathematical Biosciences and Engineering
; 19(12):13861-13877, 2022.
Article
in English
| Scopus | ID: covidwho-2066722
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. ©2022 the Author(s)
college; COVID-19; individual-based model; non-pharmaceutical interventions; vaccine; Disease control; Sensitivity analysis; Transmissions; Vaccines; Behavioral risks; College campus; Economic challenges; Educational systems; Health economics; Individual-based modelling; Risk factors; Socio-economics
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Observational study
/
Prognostic study
/
Qualitative research
Topics:
Vaccines
Language:
English
Journal:
Mathematical Biosciences and Engineering
Year:
2022
Document Type:
Article
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