Phase 1 COVID-19 Longitudinal Health and Wellbeing - National Core Study

COVID-19 纵向健康与福祉第一阶段 - 国家核心研究

• 批准号: MC_PC_20059
• 负责人: Nishi Chaturvedi
• 金额: $ 1156.21万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Intramural
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MC_PC_20059
• 关键词: Phase; COVID; 19; Longitudinal; Health

The Longitudinal Health and Wellbeing National Core Study will improve understanding of COVID-19 infection risk factors, examine the physical and mental health consequences of asymptomatic to hospitalised cases, and assess the impact of population scale mitigation policy. We will unite distinct, but complementary, longitudinal studies already engaged in COVID-19 research, including UK representative population and hospitalised cohorts, household panel surveys, and national primary care registries. These will be enriched with health and administrative data linkage. Linkage, self-reporting and repeat serological assessment will allow greater precision in case assignment. This collective resource will be mined by a consortium of experienced analysts linked to these resources to provide rapid answers to existing and emerging priority research questions. These include physical and mental health impacts and socioeconomic adversity of those who have had COVID-19 infection, evolving impacts on health and socioeconomic inequalities, and uptake, safety and effectiveness of vaccination and determinants of responses. Our outputs will include briefing notes as well as scientific reports in order to optimise policy influence.

纵向健康和福祉国家核心研究将提高对COVID-19感染风险因素的理解，检查无症状到住院病例的身心健康后果，并评估人口规模缓解政策的影响。我们将联合已经参与COVID-19研究的不同但互补的纵向研究，包括英国代表性人群和住院队列、家庭小组调查和国家初级保健登记处。这些数据库将因保健和行政数据的连接而更加丰富。连锁、自我报告和重复血清学评估将使病例分配更加精确。这种集体资源将由与这些资源相关的经验丰富的分析师组成的联盟进行挖掘，为现有和新出现的优先研究问题提供快速答案。这些包括对COVID-19感染者的身心健康影响和社会经济困境，对健康和社会经济不平等的不断变化的影响，以及疫苗接种的吸收、安全性和有效性以及反应的决定因素。我们的产出将包括简报和科学报告，以优化政策影响。

项目成果

Estimating disease burden using national linked electronic health records: a study using an English population-based cohort.

使用国家关联电子健康记录估计疾病负担：一项使用基于英国人口的队列的研究。

• DOI: 10.12688/wellcomeopenres.19470.1
• 发表时间: 2023
• 期刊: Wellcome Open Research
• 作者: Aldridge R

Pharmacoepidemiology in pregnancy: analysis protocol for an observational cohort study in the UK Clinical Practice Research Datalink.

妊娠的药物ePIDEMIOGY：英国临床实践研究数据链接的观察队列研究的分析方案。

• DOI: 10.12688/wellcomeopenres.17523.1
• 发表时间: 2022
• 期刊: Wellcome open research

OpenSAFELY: Representativeness of electronic health record platform OpenSAFELY-TPP data compared to the population of England.

• DOI: 10.12688/wellcomeopenres.18010.1
• 发表时间: 2022
• 期刊: Wellcome open research

Genome-wide association study investigating short and long sleep duration: a cross-population meta-analysis

• DOI: 10.1101/2022.09.09.22279703
• 发表时间: 2022-09
• 作者: I. Austin-Zimmerman;D. Levey;O. Giannakopoulou;J. Deak;M. Galimberti;H. Zhou;Spiros C. Denaxas;H. Irizar;K. Kuchenbaecker;A. Mcquillin;the Million Veteran Program;J. Concato;Daniel J Buysse;J. Gaziano;D. Gottlieb;R. Polimanti;M. Stein;E. Bramon;J. Gelernter

Identifying subtypes of heart failure with machine learning: external, prognostic and genetic validation in three electronic health record sources with 320,863 individuals

通过机器学习识别心力衰竭的亚型：对 320,863 人的三个电子健康记录源进行外部、预后和遗传验证

• DOI: 10.1101/2022.06.27.22276961
• 发表时间: 2022
• 作者: Banerjee A