Disaster and Emergency Management Area, School of Administrative Studies, York University, Toronto, ON M3J 1P3, Canada.
Decision Sciences Area, School of Administrative Studies, York University, Toronto, ON M3J 1P3, Canada.
Int J Environ Res Public Health. 2022 Feb 24;19(5):2635. doi: 10.3390/ijerph19052635.
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.
老年人，尤其是那些有预先存在健康问题的人，在 COVID-19 大流行期间面临不成比例的更高风险。长期护理机构的居民受到疫情的严重影响，居民死亡人数远远超过一般人群。为了更好地了解 COVID-19 等传染病如何在长期护理机构传播，我们开发了一种基于代理的模拟工具，该工具使用了从这些类型的设施以前的感染控制研究中改编的接触矩阵。该矩阵考虑了代表长期护理机构中个人角色的七种不同代理类型之间平均每天不同的接触次数。将模拟结果与加拿大安大略省一些长期护理机构的实际 COVID-19 疫情进行了比较。我们的分析表明，该模拟工具能够在少于 0.1 的死亡率变化的情况下，在 50 天后预测居民死亡人数。我们利用该模拟工具对感染控制措施的有效性进行了建模和预测。我们发现，要减少居民死亡人数，个人防护设备的有效性必须超过 50%。我们还发现，对长期护理机构不到 10%的人口进行每日随机 COVID-19 检测，将使居民死亡人数减少 75%以上。结果还表明，结合几种感染控制措施将带来更有效的结果。
