COVID-19: Data and Connectivity - National Core Study (D&C-NCS)

  • Funded by UK Research and Innovation (UKRI)
  • Total publications:68 publications

Grant number: MC_PC_20029

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2021
  • Known Financial Commitments (USD)

    $10,945,900
  • Funder

    UK Research and Innovation (UKRI)
  • Principal Investigator

    Professor Andrew Morris
  • Research Location

    United Kingdom
  • Lead Research Institution

    Health Data Research UK
  • Research Priority Alignment

    N/A
  • Research Category

    Health Systems Research

  • Research Subcategory

    Health information systems

  • Special Interest Tags

    Data Management and Data Sharing

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

The Data and Connectivity study sits across the other National Core Studies and aims to build a national health data research capability to support COVID-19 research questions, ensuring datasets are discoverable and accessible and linkages are established to answer the priority research questions from the other five National Core Studies. Making data available for wider research use will increase the scope of benefits beyond the specific studies above, leading to unexpected benefits and boosting UK research capacity more generally, increasing return on investment for the NCS programme. Data integration and harmonisation of methods and standards will enable rapid research and development of new interventions and technologies across the spectrum of COVID-19, and knowledge and technology transfer to other clinical and public health areas. Over the next 6 months the Data and Connectivity study will: 1. Map the initial high priority COVID 19 datasets required by the National Core Studies. 2. Deliver the necessary data infrastructure and services (quality and timely data, ability to link the data and provide access to data for multiple researchers) in 5 Trusted Research Environments across the UK to allow the initial high priority research questions to be answered efficiently in a transparent and trustworthy way. 3. Deliver a single "shop window" for the COVID-19 National Core Studies to ensure the priority datasets for COVID 19 research are findable, accessible, interoperable and reusable (FAIR) by enhancing the UK Health Data Research Innovation Gateway Collation and linkage between datasets is critical to bringing the core studies together, ensuring that each of them can deliver against their policy priorities e.g. hospital data may not currently be linked with GP data and wider community data (e.g. socioeconomic data or data on housing and the built environment). Access, cleaning, linkage and use of these datasets together is needed to fully understand links between these factors and outcomes.Delivery of the COVID-19 Data and Connectivity Study will involve close interaction with data custodians, the public and patients, and providers of UK-wide national Trusted Research Environments (TREs) to ensure the required data is stored safely and securely, made readily available to approved researchers and is associated with compute, analytical and data services that make it easier to address priority research questions in a transparent and trustworthy way.

Publicationslinked via Europe PMC

Occupational differences in COVID-19 hospital admission and mortality risks between women and men in Scotland: a population-based study using linked administrative data.

Socioeconomic area deprivation and its relationship with dementia, Parkinson's Disease and all-cause mortality among UK older adults: a multistate modeling approach.

Plasma MERTK is causally associated with infection mortality.

Myocardial Strain Measured by Cardiac Magnetic Resonance Predicts Cardiovascular Morbidity and Death.

Association of pre-existing depression and anxiety with Omicron variant infection.

Exploring Prior Antibiotic Exposure Characteristics for COVID-19 Hospital Admission Patients: OpenSAFELY

Homozygosity for R47H in <i>TREM2</i> and the Risk of Alzheimer's Disease.

Acute and long-term outcomes of SARS-CoV-2 infection in school-aged children in England: Study protocol for the joint analysis of the COVID-19 schools infection survey (SIS) and the COVID-19 mapping and mitigation in schools (CoMMinS) study.

Incorporating polygenic risk into the Leicester Risk Assessment score for 10-year risk prediction of type 2 diabetes.