Using data to improve public health: COVID-19 secondment

利用数据改善公共卫生：COVID-19 借调

• 批准号: MR/W021358/1
• 负责人: Yinghui Wei
• 金额: $ 15.01万
• 依托单位: Plymouth University
• 依托单位国家: 英国
• 项目类别: Fellowship
• 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=MR%2FW021358%2F1
• 关键词: Using; data; improve; public; health

The COVID-19 pandemic has seen the importance of using data to understand the spread of the Coronavirus, predict future trends of the pandemic in space and time, forecast challenges for healthcare delivery and inform government management policies. The availability of national electronic health records and longitudinal cohort studies provides unique opportunities for using big data to better understand the impact of COVID-19 on health, society and economics. The aim of this fellowship is to develop well-designed statistical analyses which make the best use of data from multiple sources in order to understand the impacts and management of the COVID-19 pandemic to improve public health.The objectives of this fellowship are to:1. Identify risk factors associated with Long COVID.2. Evaluate the effectiveness and safety of vaccines.3. Quantify the healthcare disruptions during different waves of the pandemic.4. Assess the effects of COVID-19 infection on other health outcomes. A key focus of this fellowship will be for me to advance my research career from an independent researcher to become a leading expert in big data enabled health research. The proposed research will allow me to:a) Conduct COVID-19 research through engaging in the Longitudinal Health and Wellbeing National Core Study.The fellowship will allow me to apply and advance my expertise in big data, statistical modelling and epidemiology to develop statistical analyses for addressing important research questions which will have an impact on public health.b) Grow a research team for COVID-19 research and health data science.This will be achieved through bringing together researchers to support this fellowship, and by making funding applications to support the team's activities and to train early-career researchers beyond this fellowship.c) Advance my expertise in using big data for health research.I have an intrinsic passion for, and continually develop my experience in, using real-world big data to address important research questions, especially within the clinical decision-making framework. This fellowship will allow me to extend my expertise in this exciting area that has a great potential to influence healthcare policy leading to better population health.d) Disseminate research outputs widely.I will disseminate the outputs from this research in peer-reviewed journal publications and conference presentations. Furthermore, I will create a website to communicate the key findings of my work to a wider audience including the general public. I will also host seminars or a stakeholder workshop related to COVID-19, to generate further interests, collaborations and impact of the research.Achieving these fellowship objectives will enable me to reach my career goal to be a leading expert in big data approaches to health, heading up a research team that develops quantitative methods to address research questions related to COVID-19 public health and beyond. Big data approaches will allow us to provide better insights, more robust conclusions, and better recommendations for health policy, which will ultimately benefit the population health.

2019冠状病毒病疫情凸显了利用数据了解冠状病毒传播、预测疫情在空间和时间上的未来趋势、预测医疗服务面临的挑战以及为政府管理政策提供信息的重要性。国家电子健康记录和纵向队列研究的可用性为利用大数据更好地了解COVID-19对健康、社会和经济的影响提供了独特的机会。该奖学金的目的是开发精心设计的统计分析，充分利用来自多个来源的数据，以了解COVID-19大流行的影响和管理，以改善公共卫生。该奖学金的目标是：1.识别与长期COVID相关的风险因素。2.评估疫苗的有效性和安全性。量化不同流行浪潮期间的医疗中断。评估COVID-19感染对其他健康结果的影响。这个奖学金的一个关键重点将是我从一个独立的研究人员推进我的研究生涯，成为大数据支持的健康研究的领先专家。拟议的研究将使我能够：a）通过参与纵向健康与福祉国家核心研究开展COVID-19研究。该奖学金将使我能够应用和提升我在大数据、统计建模和流行病学方面的专业知识，以开发统计分析，解决对公共卫生有影响的重要研究问题。B）组建一个COVID-19研究和健康数据科学的研究团队。这将通过汇集研究人员支持该奖学金来实现，并提出资金申请，以支持该团队的活动，并在该奖学金之外培训早期职业研究人员。提升我在使用大数据进行健康研究方面的专业知识。我对使用真实世界的大数据来解决重要的研究问题有着内在的热情，并不断发展我的经验，特别是在临床决策框架内。这个奖学金将使我能够扩展我在这个令人兴奋的领域的专业知识，这个领域有很大的潜力影响医疗保健政策，从而改善人口健康。d）广泛传播研究成果。我将在同行评议的期刊出版物和会议演讲中传播这项研究的成果。此外，我将创建一个网站，向包括公众在内的更广泛的受众传达我的工作的主要发现。我还将主持与COVID-19相关的研讨会或利益相关者工作坊，以激发更多的兴趣，合作和研究的影响。实现这些奖学金目标将使我能够实现我的职业目标，成为健康大数据方法的领先专家，领导一个研究团队，开发定量方法来解决与COVID-19公共卫生及其他相关的研究问题。大数据方法将使我们能够为卫生政策提供更好的见解，更有力的结论和更好的建议，这将最终有利于人口健康。

项目成果

Clinical coding of long COVID in primary care 2020-2023 in a cohort of 19 million adults: an OpenSAFELY analysis

2020-2023 年初级保健中 1900 万成年人队列中长期新冠肺炎的临床编码：OpenSAFELY 分析

• DOI: 10.1101/2023.12.04.23299364
• 发表时间: 2023
• 作者: Henderson A

Impact of vaccination on the association of COVID-19 with cardiovascular diseases: An OpenSAFELY cohort study.

疫苗接种对 COVID-19 与心血管疾病关联的影响：一项 OpenSAFELY 队列研究。

• DOI: 10.1038/s41467-024-46497-0
• 发表时间: 2024
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Cezard GI

Diabetes following SARS-CoV-2 infection: Incidence, persistence, and implications of COVID-19 vaccination. A cohort study of fifteen million people

SARS-CoV-2 感染后糖尿病：发病率、持续性以及 COVID-19 疫苗接种的影响。

• DOI: 10.1101/2023.08.07.23293778
• 发表时间: 2023
• 作者: Taylor K

Impact of vaccination on the association of COVID-19 with arterial and venous thrombotic diseases: an OpenSAFELY cohort study using linked electronic health records

疫苗接种对 COVID-19 与动脉和静脉血栓性疾病关联的影响：一项使用关联电子健康记录的 OpenSAFELY 队列研究

• DOI: 10.21203/rs.3.rs-3168263/v1
• 发表时间: 2023
• 作者: Cezard G

Impact of COVID-19 on mental illness in vaccinated and unvaccinated people: a population-based cohort study in OpenSAFELY

COVID-19 对接种疫苗和未接种疫苗人群的精神疾病的影响：OpenSAFELY 中基于人群的队列研究

• DOI: 10.1101/2023.12.06.23299602
• 发表时间: 2023
• 作者: Walker V