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Article

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

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Disaster and Emergency Management Area, School of Administrative Studies, York University, Toronto, ON M3J 1P3, Canada
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Decision Sciences Area, School of Administrative Studies, York University, Toronto, ON M3J 1P3, Canada
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Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada
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Advanced Disaster, Emergency, and Rapid Response Simulation (ADERSIM), York University, Toronto, ON M3J 1P3, Canada
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Authors to whom correspondence should be addressed.
Academic Editors: Keun Ho Ryu and Nipon Theera-Umpon
Int. J. Environ. Res. Public Health 2022, 19(5), 2635; https://doi.org/10.3390/ijerph19052635
Received: 10 January 2022 / Revised: 15 February 2022 / Accepted: 20 February 2022 / Published: 24 February 2022
(This article belongs to the Topic Artificial Intelligence in Healthcare)
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. View Full-Text
Keywords: COVID-19; long-term care facilities; agent-based modeling; disease modeling; contact matrix COVID-19; long-term care facilities; agent-based modeling; disease modeling; contact matrix
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MDPI and ACS Style

Asgary, A.; Blue, H.; Solis, A.O.; McCarthy, Z.; Najafabadi, M.; Tofighi, M.A.; Wu, J. Modeling COVID-19 Outbreaks in Long-Term Care Facilities Using an Agent-Based Modeling and Simulation Approach. Int. J. Environ. Res. Public Health 2022, 19, 2635. https://doi.org/10.3390/ijerph19052635

AMA Style

Asgary A, Blue H, Solis AO, McCarthy Z, Najafabadi M, Tofighi MA, Wu J. Modeling COVID-19 Outbreaks in Long-Term Care Facilities Using an Agent-Based Modeling and Simulation Approach. International Journal of Environmental Research and Public Health. 2022; 19(5):2635. https://doi.org/10.3390/ijerph19052635

Chicago/Turabian Style

Asgary, Ali, Hudson Blue, Adriano O. Solis, Zachary McCarthy, Mahdi Najafabadi, Mohammad Ali Tofighi, and Jianhong Wu. 2022. "Modeling COVID-19 Outbreaks in Long-Term Care Facilities Using an Agent-Based Modeling and Simulation Approach" International Journal of Environmental Research and Public Health 19, no. 5: 2635. https://doi.org/10.3390/ijerph19052635

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