Capacitated SIR Model with an Application to COVID-19 Testing

41 Pages Posted: 22 Sep 2020 Last revised: 2 Sep 2022

See all articles by Ningyuan Chen

Ningyuan Chen

University of Toronto - Rotman School of Management

Ming Hu

University of Toronto - Rotman School of Management

Chaoyu Zhang

University of Toronto - Rotman School of Management

Date Written: September 14, 2020

Abstract

The classical SIR model and its variants have seen great success in understanding and predicting infectious diseases' spread. To better capture the COVID-19 outbreak, we extend the SIR model to incorporate the limited testing capacity and account for asymptomatic people. Building on the SIR model, we impose a testing capacity and differentiate the infected people into symptomatic and asymptomatic types. Using this capacitated SIR model, we show first- and second-order structural properties of one measure---the fraction of uninfected people---with respect to the testing capacity, testing accuracy, testing turnaround time, and contact tracing accuracy. Moreover, we study how to allocate limited testing capacity over time and across people with and without symptoms, and how to prioritize among the testing methods that have a different testing capacity, accuracy, and turnaround time. Moreover, using the COVID-19 data, we develop a sliding-window method to identify the non-stationarity of the model parameters and predict future infections.
The analytical results provide critical insights on managing testing capacities at both the strategic and operational levels. Moreover, the estimation results show that our parsimonious model can still have a strong predictive power.

Note: Ethical approval statement: Our research only involves information freely available in the public domain without contact with any individuals.

Funding: None to declare

Declaration of Interest: None to declare

Keywords: COVID-19, testing capacity, compartmental model, SIR, structural result

JEL Classification: I18

Suggested Citation

Chen, Ningyuan and Hu, Ming and Zhang, Chaoyu, Capacitated SIR Model with an Application to COVID-19 Testing (September 14, 2020). Available at SSRN: https://ssrn.com/abstract=3692751 or http://dx.doi.org/10.2139/ssrn.3692751

Ningyuan Chen (Contact Author)

University of Toronto - Rotman School of Management ( email )

Ming Hu

University of Toronto - Rotman School of Management ( email )

105 St. George st
Toronto, ON M5S 3E6
Canada
416-946-5207 (Phone)

HOME PAGE: http://ming.hu

Chaoyu Zhang

University of Toronto - Rotman School of Management ( email )

105 St. George Street
Toronto, Ontario M5S 3E6 M5S1S4
Canada

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