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对新冠无关联病例的特征描述及对接触者追踪措施的意义:监测数据的回顾性分析。

Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance Data.

机构信息

Centre for Health Systems and Policy Research, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, Hong Kong.

MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.

出版信息

JMIR Public Health Surveill. 2021 Nov 16;7(11):e30968. doi: 10.2196/30968.

Abstract

BACKGROUND

Contact tracing and intensive testing programs are essential for controlling the spread of COVID-19. However, conventional contact tracing is resource intensive and may not result in the tracing of all cases due to recall bias and cases not knowing the identity of some close contacts. Few studies have reported the epidemiological features of cases not identified by contact tracing ("unlinked cases") or described their potential roles in seeding community outbreaks.

OBJECTIVE

For this study, we characterized the role of unlinked cases in the epidemic by comparing their epidemiological profile with the linked cases; we also estimated their transmission potential across different settings.

METHODS

We obtained rapid surveillance data from the government, which contained the line listing of COVID-19 confirmed cases during the first three waves in Hong Kong. We compared the demographics, history of chronic illnesses, epidemiological characteristics, clinical characteristics, and outcomes of linked and unlinked cases. Transmission potentials in different settings were assessed by fitting a negative binomial distribution to the observed offspring distribution.

RESULTS

Time interval from illness onset to hospital admission was longer among unlinked cases than linked cases (median 5.00 days versus 3.78 days; P<.001), with a higher proportion of cases whose condition was critical or serious (13.0% versus 8.2%; P<.001). The proportion of unlinked cases was associated with an increase in the weekly number of local cases (P=.049). Cluster transmissions from the unlinked cases were most frequently identified in household settings, followed by eateries and workplaces, with the estimated probability of cluster transmissions being around 0.4 for households and 0.1-0.3 for the latter two settings.

CONCLUSIONS

The unlinked cases were positively associated with time to hospital admission, severity of infection, and epidemic size-implying a need to design and implement digital tracing methods to complement current conventional testing and tracing. To minimize the risk of cluster transmissions from unlinked cases, digital tracing approaches should be effectively applied in high-risk socioeconomic settings, and risk assessments should be conducted to review and adjust the policies.

摘要

背景

接触者追踪和强化检测计划对于控制 COVID-19 的传播至关重要。然而,传统的接触者追踪需要大量资源,并且由于回忆偏差和病例不知道一些密切接触者的身份,可能无法追踪到所有病例。很少有研究报告过未通过接触者追踪识别的病例(“未关联病例”)的流行病学特征,也没有描述它们在引发社区暴发方面的潜在作用。

目的

在这项研究中,我们通过将未关联病例的流行病学特征与关联病例进行比较,来描述未关联病例在疫情中的作用;我们还估计了它们在不同环境中的传播潜力。

方法

我们从政府获得了快速监测数据,其中包含香港前三次疫情期间 COVID-19 确诊病例的详细清单。我们比较了关联病例和未关联病例的人口统计学特征、慢性病史、流行病学特征、临床特征和结局。通过对观察到的后代分布拟合负二项分布来评估不同环境中的传播潜力。

结果

未关联病例从发病到住院的时间间隔长于关联病例(中位数 5.00 天比 3.78 天;P<.001),且病情严重或危急的比例更高(13.0%比 8.2%;P<.001)。未关联病例的比例与本地病例每周数量的增加有关(P=.049)。未关联病例的集群传播主要发生在家庭环境中,其次是餐馆和工作场所,家庭环境中集群传播的估计概率约为 0.4,后两者约为 0.1-0.3。

结论

未关联病例与住院时间、感染严重程度和疫情规模呈正相关,这意味着需要设计和实施数字追踪方法来补充当前的常规检测和追踪。为了最大限度地减少未关联病例引发集群传播的风险,应在高风险的社会经济环境中有效应用数字追踪方法,并进行风险评估以审查和调整政策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2465/8598156/4ea22cf0cccb/publichealth_v7i11e30968_fig1.jpg

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