Foundations and Trends® in Technology, Information and Operations Management > Vol 19 > Issue 2–3

Testing as a Control Mechanism for Emerging Epidemics

By Ujjal Kumar Mukherjee, Gies College of Business, University of Illinois Urbana-Champaign, USA and Carle Illinois College of Medicine, University of Illinois Urbana-Champaign, USA, ukm@illinois.edu | Sebastian Souyris, Lally School of Management, Rensselaer Polytechnic Institute, USA, souyrs@rpi.edu | Anton Ivanov, Gies College of Business, University of Illinois Urbana-Champaign, USA, antoniva@illinois.edu

 
Suggested Citation
Ujjal Kumar Mukherjee, Sebastian Souyris and Anton Ivanov (2025), "Testing as a Control Mechanism for Emerging Epidemics", Foundations and Trends® in Technology, Information and Operations Management: Vol. 19: No. 2–3, pp 383-430. http://dx.doi.org/10.1561/0200000116-10

Publication Date: 12 Mar 2025
© 2025 U. K. Mukherjee et al.
 
Subjects
Econometric models,  Models for count data
 
Keywords
Epidemics, testing, SIR models, quarantine, lockdowns, vaccination
 

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In this article:
1. Introduction
2. Epidemic Modeling Incorporating Testing, Lockdowns, and Vaccination
3. Model Analysis
4. Testing Capacity Allocation Models
5. Data and Analysis
6. Conclusion
References

Abstract

In this study, we discuss the role of testing, along with other control measures, as a mitigation mechanism for emerging epidemics. We present several models that incorporate testing along with quarantine policies, lockdowns, and vaccination as control mechanisms for epidemics. We also present a model for data-driven prediction and allocation of test kits to a network of connected locations. This study will provide important modeling strategies and policy pointers for formulating testing policies for the control of epidemics.

DOI:10.1561/0200000116-10

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ISBN: 978-1-63828-464-2
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Table of contents:
Preface
1. #ThisisPublicHealth—The Seed of an Idea That Has Grown Into a Forest of Possibilities
2. Budget Allocations for Public Health Procurement
3. A Data-Driven Approach to Optimize Surgical Instrument Trays
4. Decision Intelligence for Healthcare Decarbonization
5. Unveiling the Data Potential - Navigating the Data Revolution for Improved Patient Care
6. Revolutionizing Healthcare: A Comprehensive Examination of Telemedicine’s Journey, Hurdles, and Future Frontiers
7. Leveraging Social Media for COVID-19 Response: Insights from a Data Competition
8. Key Lessons from the COVID-19 Pandemic
9. Barriers to Seeking Mental Health Care in Rural Communities: An Empirical Exploration in Minnesota and Wisconsin
10. Testing as a Control Mechanism for Emerging Epidemics
11. Changes in Consumers’ Shopping Channel Preferences Impacted by COVID-19 Pandemic

Lessons from the Pandemic for Healthcare Operations

Lessons from the Pandemic for Healthcare Operations delves into the lessons learned from the COVID-19 pandemic that can be applied to the post-pandemic world to enhance efficiency, equity, and fairness in healthcare operations. It emphasizes the importance of preparedness in combating future pandemics or public health disasters, regardless of when or where they may occur. This work offers a unique perspective through which to view the evolving outlines of healthcare delivery, policy, and research. This is illustrated using several real-world experiences, empirical studies, and forward-looking insights. The contributions fall under three broad themes: the management of policies and funding in healthcare, the role of data and data-driven research, and accessible healthcare services during and after the pandemic.

 
TOM-116-10

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Foundations and Trends® in Technology, Information and Operations Management, Volume 19, Issue 2-3 Special Issue: Lessons from the Pandemic for Healthcare Operations
See the other articles that are also part of this special issue.