Department of Epidemiology, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA.
School of Engineering at Mathematical Sciences, La Trobe University - Bundoora Campus, Melbourne, Victoria, Australia.
BMJ Open. 2021 Mar 2;11(3):e044644. doi: 10.1136/bmjopen-2020-044644.
Since its onset, the COVID-19 pandemic has caused significant morbidity and mortality worldwide, with particularly severe outcomes in healthcare institutions and congregate settings. To mitigate spread, healthcare systems have been cohorting patients to limit contacts between uninfected patients and potentially infected patients or healthcare workers (HCWs). A major challenge in managing the pandemic is the presence of currently asymptomatic/presymptomatic individuals capable of transmitting the virus, who could introduce COVID-19 into uninfected cohorts. The optimal combination of personal protective equipment (PPE), testing and other approaches to prevent these events is unclear, especially in light of ongoing limited resources.
Using stochastic simulations with a susceptible-exposed-infected-recovered dynamic model, we quantified and compared the impacts of PPE use, patient and HCWs surveillance testing and subcohorting strategies.
In the base case without testing or PPE, the healthcare system was rapidly overwhelmed, and became a net contributor to the force of infection. We found that effective use of PPE by both HCWs and patients could prevent this scenario, while random testing of apparently asymptomatic/presymptomatic individuals on a weekly basis was less effective. We also found that even imperfect use of PPE could provide substantial protection by decreasing the force of infection. Importantly, we found that creating smaller patient/HCW-interaction subcohorts can provide additional resilience to outbreak development with limited resources.
These findings reinforce the importance of ensuring adequate PPE supplies even in the absence of testing and provide support for strict subcohorting regimens to reduce outbreak potential in healthcare institutions.
自 COVID-19 大流行以来,它已在全球范围内造成了大量的发病率和死亡率,在医疗机构和聚集场所的后果尤为严重。为了减轻传播,医疗系统已经对患者进行了分组,以限制未感染患者和潜在感染患者或医护人员(HCW)之间的接触。管理大流行的一个主要挑战是目前无症状/出现症状前的个体能够传播病毒,他们可能会将 COVID-19 引入未感染的人群中。目前尚不清楚预防这些事件的最佳个人防护设备(PPE)、检测和其他方法的组合,特别是在资源持续有限的情况下。
使用具有易感性-暴露性-感染性-恢复性动态模型的随机模拟,我们量化并比较了 PPE 使用、患者和 HCW 监测测试以及亚群划分策略的影响。
在没有测试或 PPE 的基本情况下,医疗系统迅速不堪重负,并成为感染源的净贡献者。我们发现,HCW 和患者有效使用 PPE 可以防止这种情况发生,而每周对明显无症状/出现症状前的个体进行随机测试则效果较差。我们还发现,即使 PPE 的使用不完美,也可以通过降低感染源来提供大量保护。重要的是,我们发现创建较小的患者/HCW 交互亚群可以在资源有限的情况下为爆发发展提供额外的弹性。
这些发现强化了即使在没有测试的情况下,也要确保充足的 PPE 供应的重要性,并为严格的亚群划分方案提供支持,以降低医疗机构爆发的可能性。