University Operations During a Pandemic: A Flexible Decision Analysis Toolkit
Himanshu Kharkwal, Dakota Olson, Jiali Huang, Abhiraj Mohan, Ankur, Mani, Jaideep Srivastava

TL;DR
This paper introduces a flexible simulation toolkit combining agent-based modeling and network science to help universities and organizations make informed decisions about campus operations during pandemics.
Contribution
It presents a novel, detailed simulation system that models social contacts and infection spread, enabling tailored decision analysis for pandemic management in educational settings.
Findings
The system accurately models social contact patterns in university settings.
Case study demonstrates effective decision impact assessment.
Toolkit adaptable for various organizational types.
Abstract
Modeling infection spread during pandemics is not new, with models using past data to tune simulation parameters for predictions. These help understand the healthcare burden posed by a pandemic and respond accordingly. However, the problem of how college/university campuses should function during a pandemic is new for the following reasons:(i) social contact in colleges are structured and can be engineered for chosen objectives, (ii) the last pandemic to cause such societal disruption was over 100 years ago, when higher education was not a critical part of society, (ii) not much was known about causes of pandemics, and hence effective ways of safe operations were not known, and (iii) today with distance learning, remote operation of an academic institution is possible. Our approach is unique in presenting a flexible simulation system, containing a suite of model libraries, one for each…
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