The Artificial University: Decision Support for Universities in the COVID-19 Era
Joint Authors
Wildman, Wesley J.
Diallo, Saikou Y.
Hodulik, George
Page, Andrew
Tolk, Andreas
Gondal, Neha
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-30
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Operating universities under pandemic conditions is a complex undertaking.
The Artificial University (TAU) responds to this need.
TAU is a configurable, open-source computer simulation of a university using a contact network based on publicly available information about university classes, residences, and activities.
This study evaluates health outcomes for an array of interventions and testing protocols in an artificial university of 6,500 students, faculty, and staff.
Findings suggest that physical distancing and centralized contact tracing are most effective at reducing infections, but there is a tipping point for compliance below which physical distancing is less effective.
If student compliance is anything short of high, it helps to have separate buildings for quarantining infected students, thereby gracefully increasing compliance.
Hybrid in-person and online classes and closing fitness centers do not significantly change cumulative infections but do significantly decrease the number of the infected at any given time, indicating strategies for “flattening the curve” to protect limited resources.
Supplementing physical distancing with centralized contact tracing decreases infected individuals by an additional 14%; boosting frequency of testing for student-facing staff yields a further 7% decrease.
A trade-off exists between increasing the sheer number of infection tests and targeting testing for key nodes in the contact network (i.e., student-facing staff).
There are significant advantages to getting and acting on test results quickly.
The costs and benefits to universities of these findings are discussed.
Artificial universities can be an important decision support tool for universities, generating useful policy insights into the challenges of operating universities under pandemic conditions.
American Psychological Association (APA)
Wildman, Wesley J.& Diallo, Saikou Y.& Hodulik, George& Page, Andrew& Tolk, Andreas& Gondal, Neha. 2020. The Artificial University: Decision Support for Universities in the COVID-19 Era. Complexity،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1142624
Modern Language Association (MLA)
Wildman, Wesley J.…[et al.]. The Artificial University: Decision Support for Universities in the COVID-19 Era. Complexity No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1142624
American Medical Association (AMA)
Wildman, Wesley J.& Diallo, Saikou Y.& Hodulik, George& Page, Andrew& Tolk, Andreas& Gondal, Neha. The Artificial University: Decision Support for Universities in the COVID-19 Era. Complexity. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1142624
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142624