Modeling COVID-19 Outbreaks in Long-Term Care Facilities Using an Agent-Based Modeling and Simulation Approach

Ali Asgary, Hudson Blue, Adriano O. Solis, Zachary McCarthy, Mahdi Najafabadi, Mohammad Ali Tofighi and Jianhong Wu
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Ali Asgary: Disaster and Emergency Management Area, School of Administrative Studies, York University, Toronto, ON M3J 1P3, Canada
Hudson Blue: Disaster and Emergency Management Area, School of Administrative Studies, York University, Toronto, ON M3J 1P3, Canada
Adriano O. Solis: Decision Sciences Area, School of Administrative Studies, York University, Toronto, ON M3J 1P3, Canada
Zachary McCarthy: Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada
Mahdi Najafabadi: Advanced Disaster, Emergency, and Rapid Response Simulation (ADERSIM), York University, Toronto, ON M3J 1P3, Canada
Mohammad Ali Tofighi: Advanced Disaster, Emergency, and Rapid Response Simulation (ADERSIM), York University, Toronto, ON M3J 1P3, Canada
Jianhong Wu: Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada

IJERPH, 2022, vol. 19, issue 5, 1-16

Abstract: The elderly, especially those individuals with pre-existing health problems, have been disproportionally at a higher risk during the COVID-19 pandemic. Residents of long-term care facilities have been gravely affected by the pandemic and resident death numbers have been far above those of the general population. To better understand how infectious diseases such as COVID-19 can spread through long-term care facilities, we developed an agent-based simulation tool that uses a contact matrix adapted from previous infection control research in these types of facilities. This matrix accounts for the average distinct daily contacts between seven different agent types that represent the roles of individuals in long-term care facilities. The simulation results were compared to actual COVID-19 outbreaks in some of the long-term care facilities in Ontario, Canada. Our analysis shows that this simulation tool is capable of predicting the number of resident deaths after 50 days with a less than 0.1 variation in death rate. We modeled and predicted the effectiveness of infection control measures by utilizing this simulation tool. We found that to reduce the number of resident deaths, the effectiveness of personal protective equipment must be above 50%. We also found that daily random COVID-19 tests for as low as less than 10% of a long-term care facility’s population will reduce the number of resident deaths by over 75%. The results further show that combining several infection control measures will lead to more effective outcomes.

Keywords: COVID-19; long-term care facilities; agent-based modeling; disease modeling; contact matrix (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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