Abstract
We propose a new modeling framework for evaluating the risk of disease transmission during a pandemic in small-scale settings driven by stochasticity in the arrival and service processes, that is, congestion-prone confined-space service facilities. We propose a novel metric, system-specific basic reproduction rate, inspired by the “basic reproduction rate” concept from epidemiology, which measures the transmissibility of infectious diseases. We derive our metric for various queueing models of service facilities by leveraging a novel queueing-theoretic notion: sojourn time overlaps. We showcase how our metric can be used to explore the efficacy of a variety of interventions aimed at curbing the spread of disease inside service facilities. Specifically, we focus on some prevalent interventions employed during the COVID-19 pandemic: limiting the occupancy of service facilities, protecting high-risk customers (via prioritization or designated time windows), and increasing the service speed (or limiting patronage duration). We discuss a variety of directions for adapting our transmission model to incorporate some more nuanced features of disease transmission, including heterogeneity in the population immunity level, varying levels of mask usage, and spatial considerations in disease transmission.
| Original language | English (US) |
|---|---|
| Journal | Production and Operations Management |
| DOIs | |
| State | Accepted/In press - 2022 |
| Externally published | Yes |
Bibliographical note
Funding Information:The authors are grateful to the editors of this special issue, the senior editor, and the two anonymous referees for their comments and suggestions, which helped improve this paper.
Publisher Copyright:
© 2022 Production and Operations Management Society.
Keywords
- COVID-19 pandemic
- basic reproduction rate
- disease transmission
- queueing theory
- service systems
