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全基因组测序方法在英格兰的代表性:理解 SARS-CoV-2 感染相关不平等现象的重要性。

Representativeness of whole-genome sequencing approaches in England: the importance for understanding inequalities associated with SARS-CoV-2 infection.

机构信息

COVID-19 National Epidemiology Cell, UKHSA, London, UK.

COVID-19 Vaccines and Epidemiology Division, Public Health Programmes, Clinical and Public Health Group, UKHSA, London, UK.

出版信息

Epidemiol Infect. 2023 Sep 20;151:e169. doi: 10.1017/S0950268823001541.

Abstract

Whole-genome sequencing (WGS) information has played a crucial role in the SARS-CoV-2 (COVID-19) pandemic by providing evidence about variants to inform public health policy. The purpose of this study was to assess the representativeness of sequenced cases compared with all COVID-19 cases in England, between March 2020 and August 2021, by demographic and socio-economic characteristics, to evaluate the representativeness and utility of these data in epidemiological analyses. To achieve this, polymerase chain reaction (PCR)-confirmed COVID-19 cases were extracted from the national laboratory system and linked with WGS data. During the study period, over 10% of COVID-19 cases in England had WGS data available for epidemiological analysis. With sequencing capacity increasing throughout the period, sequencing representativeness compared to all reported COVID-19 cases increased over time, allowing for valuable epidemiological analyses using demographic and socio-economic characteristics, particularly during periods with emerging novel SARS-CoV-2 variants. This study demonstrates the comprehensiveness of England's sequencing throughout the COVID-19 pandemic, rapidly detecting variants of concern, and enabling representative epidemiological analyses to inform policy.

摘要

全基因组测序 (WGS) 信息在 SARS-CoV-2(COVID-19)大流行中发挥了至关重要的作用,为了解变体提供了证据,从而为公共卫生政策提供信息。本研究的目的是评估 2020 年 3 月至 2021 年 8 月期间,与英国所有 COVID-19 病例相比,测序病例在人口统计学和社会经济特征方面的代表性,以评估这些数据在流行病学分析中的代表性和实用性。为此,从国家实验室系统中提取聚合酶链反应 (PCR) 确诊的 COVID-19 病例,并将其与 WGS 数据相关联。在研究期间,英国超过 10%的 COVID-19 病例有 WGS 数据可用于流行病学分析。随着测序能力在整个研究期间的提高,与所有报告的 COVID-19 病例相比,测序的代表性随时间推移而增加,从而能够使用人口统计学和社会经济特征进行有价值的流行病学分析,特别是在出现新的 SARS-CoV-2 变体期间。本研究展示了英格兰在整个 COVID-19 大流行期间测序的全面性,快速检测到令人关注的变体,并能够进行有代表性的流行病学分析,为政策提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f991/10600896/f6cf03f3e5c4/S0950268823001541_fig1.jpg

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