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Using data to improve public health: COVID-19 secondment

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:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --

项目摘要

项目成果

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中文摘要
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英文摘要
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.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
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
期刊:
影响因子: --
作者: [Henderson A]
通讯作者: 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]
通讯作者: Cezard GI
DOI: 10.1101/2023.08.07.23293778
发表时间: 2023
期刊:
影响因子: --
作者: [Taylor K]
通讯作者: 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
期刊:
影响因子: --
作者: [Cezard G]
通讯作者: Cezard G
9
    国内基金
    海外基金
    Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
    Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
    复杂数据下半参数转换模型及其在老年慢性病发展中的应用研究
    • 批准号:
      72101261
    • 项目类别:
      青年科学基金项目(C类)
    • 资助金额:
      30.0万元
    • 批准年份:
      2021
    • 负责人:
      孙韬
    • 依托单位:
    Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
    • 批准号:
      --
    • 项目类别:
      --
    • 资助金额:
      40万元
    • 批准年份:
      2020
    • 负责人:
      Vikrant Gupta
    • 依托单位: