Exploring a targeted approach for public health capacity restrictions during COVID-19 using a new computational model

Ashley N Micuda; Mark R Anderson; Irina Babayan; Erin Bolger; Logan Cantin; Gillian Groth; Ry Pressman-Cyna; Charlotte Z Reed; Noah J Rowe; Mehdi Shafiee; Benjamin Tam; Marie C Vidal; Tianai Ye; Ryan D Martin

doi:10.1016/j.idm.2024.01.001

Exploring a targeted approach for public health capacity restrictions during COVID-19 using a new computational model

Infect Dis Model. 2024 Jan 12;9(1):234-244. doi: 10.1016/j.idm.2024.01.001. eCollection 2024 Mar.

Authors

Ashley N Micuda^{1

2}, Mark R Anderson¹, Irina Babayan¹, Erin Bolger^{3

4}, Logan Cantin⁵, Gillian Groth⁶, Ry Pressman-Cyna¹, Charlotte Z Reed³, Noah J Rowe¹, Mehdi Shafiee^{1

7

8}, Benjamin Tam^{1

9}, Marie C Vidal¹⁰, Tianai Ye¹, Ryan D Martin¹

Affiliations

¹ Department of Physics, Engineering Physics & Astronomy, Queen's University, Kingston, ON, Canada.
² Department of Medical Biophysics, Western University, London, ON, Canada.
³ Department of Mathematics and Statistics, Queen's University, Kingston, ON, Canada.
⁴ Department of Biology, Queen's University, Kingston, ON, Canada.
⁵ School of Computing, Queen's University, Kingston, ON, Canada.
⁶ Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada.
⁷ Department of Electrical and Computer Engineering, Nazarbayev University, Nur-Sultan, Kazakhstan.
⁸ Energetic Cosmos Laboratory, Nazarbayev University, Nur-Sultan, Kazakhstan.
⁹ Department of Physics, University of Oxford, Oxford, United Kingdom.
¹⁰ Department of Physics, Stanford University, Stanford, CA, United States.

Abstract

This work introduces the Queen's University Agent-Based Outbreak Outcome Model (QUABOOM). This tool is an agent-based Monte Carlo simulation for modelling epidemics and informing public health policy. We illustrate the use of the model by examining capacity restrictions during a lockdown. We find that public health measures should focus on the few locations where many people interact, such as grocery stores, rather than the many locations where few people interact, such as small businesses. We also discuss a case where the results of the simulation can be scaled to larger population sizes, thereby improving computational efficiency.

Keywords: Agent-based epidemic modelling; Basic reproductive number; COVID-19; Monte-carlo; Public health; Small business capacity restrictions.