CarePredict, Plantation, FL, United States.
Icahn School of Medicine at Mount Sinai, New York, NY, United States.
JMIR Public Health Surveill. 2020 Aug 25;6(3):e20828. doi: 10.2196/20828.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can spread rapidly in nursing homes and long-term care (LTC) facilities. Symptoms-based screening and manual contact tracing have limitations that render them ineffective for containing the viral spread in LTC facilities. Symptoms-based screening alone cannot identify asymptomatic people who are infected, and the viral spread is too fast in confined living quarters to be contained by slow manual contact tracing processes.
We describe the development of a digital contact tracing system that LTC facilities can use to rapidly identify and contain asymptomatic and symptomatic SARS-CoV-2 infected contacts. A compartmental model was also developed to simulate disease transmission dynamics and to assess system performance versus conventional methods.
We developed a compartmental model parameterized specifically to assess the coronavirus disease (COVID-19) transmission in LTC facilities. The model was used to quantify the impact of asymptomatic transmission and to assess the performance of several intervention groups to control outbreaks: no intervention, symptom mapping, polymerase chain reaction testing, and manual and digital contact tracing.
Our digital contact tracing system allows users to rapidly identify and then isolate close contacts, store and track infection data in a respiratory line listing tool, and identify contaminated rooms. Our simulation results indicate that the speed and efficiency of digital contact tracing contributed to superior control performance, yielding up to 52% fewer cases than conventional methods.
Digital contact tracing systems show promise as an effective tool to control COVID-19 outbreaks in LTC facilities. As facilities prepare to relax restrictions and reopen to outside visitors, such tools will allow them to do so in a surgical, cost-effective manner that controls outbreaks while safely giving residents back the life they once had before this pandemic hit.
严重急性呼吸系统综合症冠状病毒 2（SARS-CoV-2）在疗养院和长期护理（LTC）机构中传播迅速。基于症状的筛查和手动接触者追踪存在局限性，无法有效控制 LTC 机构中的病毒传播。仅基于症状的筛查无法识别无症状感染者，而且在封闭的居住环境中，病毒传播速度太快，无法通过缓慢的手动接触者追踪过程来控制。
我们描述了一种数字接触者追踪系统的开发，LTC 机构可以使用该系统快速识别和控制无症状和有症状的 SARS-CoV-2 感染接触者。还开发了一个隔间模型来模拟疾病传播动态，并评估系统性能与传统方法相比的效果。
我们开发了一个特定参数化的隔间模型，用于评估 LTC 设施中冠状病毒病（COVID-19）的传播。该模型用于量化无症状传播的影响，并评估几种干预组控制疫情爆发的效果：无干预、症状映射、聚合酶链反应测试以及手动和数字接触者追踪。
我们的数字接触者追踪系统允许用户快速识别并隔离密切接触者，在呼吸清单工具中存储和跟踪感染数据，并识别污染的房间。我们的模拟结果表明，数字接触者追踪的速度和效率有助于控制性能的提高，与传统方法相比，可减少多达 52%的病例。
数字接触者追踪系统显示出作为控制 LTC 机构 COVID-19 疫情爆发的有效工具的潜力。随着设施准备放宽限制并重新向外部访客开放，这些工具将使它们能够以安全、具有成本效益的方式进行，在控制疫情爆发的同时，让居民恢复大流行前的生活。
