Research ethics with real-world data (RWD) on COVID-19 infections: the unCoVer study

Silvia Riva; Zubair Kabir; N. Biscoe; G. O'Sullivan; Gloria Soriano; José L. Peñalvo

doi:10.1093/eurpub/ckac130.060

Research ethics with real-world data (RWD) on COVID-19 infections: the unCoVer study

Silvia Riva
, Zubair Kabir
, N. Biscoe
, G. O'Sullivan
, Gloria Soriano
, José L. Peñalvo

School of Public Health

St Mary's University, Twickenham
Institute of Tropical Medicine Antwerp

Research output: Contribution to journal › Meeting abstract › peer-review

Abstract

The aim of the Horizon 2020 unCoVer project (Unravelling Data for Rapid Evidence-Based Response to COVID-19) is to coordinate research expertise in utilising Real World Data (RWD) to investigate the underlying risk factors for COVID-19 infection and severity, the effectiveness of treatments and the impact on health systems. RWD is particularly useful in a dynamic health context as it is relevant, timely, and more ecologically valid. Pooling clinical databases and integrating epidemiological principles and powerful biostatistical tools optimises resources and fully exploits routinely-collected data.

Original language	English
Journal	European Journal of Public Health
Volume	32
Issue number	3
DOIs	https://doi.org/10.1093/eurpub/ckac130.060
Publication status	Published - 25 Oct 2022
Event	15th European Public Health Conference - Berlin, Germany Duration: 9 Nov 2022 → 12 Nov 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Data sharing
Computer science
Exploit
Data science
Context (archaeology)
Pooling
Documentation
Data access
Data Protection Act 1998
Data anonymization
Research ethics
Big data
Knowledge management
Information privacy
Computer security
Medicine
Data mining
Database
Paleontology
Alternative medicine
Pathology
Artificial intelligence
Psychiatry
Biology
Programming language

Access to Document

10.1093/eurpub/ckac130.060Licence: CC BY

Cite this

@article{7fcdfcdf69a34dc9a46b6ea0507707fc,

title = "Research ethics with real-world data (RWD) on COVID-19 infections: the unCoVer study",

abstract = "The aim of the Horizon 2020 unCoVer project (Unravelling Data for Rapid Evidence-Based Response to COVID-19) is to coordinate research expertise in utilising Real World Data (RWD) to investigate the underlying risk factors for COVID-19 infection and severity, the effectiveness of treatments and the impact on health systems. RWD is particularly useful in a dynamic health context as it is relevant, timely, and more ecologically valid. Pooling clinical databases and integrating epidemiological principles and powerful biostatistical tools optimises resources and fully exploits routinely-collected data.",

keywords = "Data sharing, Computer science, Exploit, Data science, Context (archaeology), Pooling, Documentation, Data access, Data Protection Act 1998, Data anonymization, Research ethics, Big data, Knowledge management, Information privacy, Computer security, Medicine, Data mining, Database, Paleontology, Alternative medicine, Pathology, Artificial intelligence, Psychiatry, Biology, Programming language",

author = "Silvia Riva and Zubair Kabir and N. Biscoe and G. O'Sullivan and Gloria Soriano and Pe{\~n}alvo, \{Jos{\'e} L.\}",

year = "2022",

month = oct,

day = "25",

doi = "10.1093/eurpub/ckac130.060",

language = "English",

volume = "32",

journal = "European Journal of Public Health",

issn = "1101-1262",

publisher = "Oxford University Press",

number = "3",

note = "15th European Public Health Conference ; Conference date: 09-11-2022 Through 12-11-2022",

}

TY - JOUR

T1 - Research ethics with real-world data (RWD) on COVID-19 infections: the unCoVer study

AU - Riva, Silvia

AU - Kabir, Zubair

AU - Biscoe, N.

AU - O'Sullivan, G.

AU - Soriano, Gloria

AU - Peñalvo, José L.

PY - 2022/10/25

Y1 - 2022/10/25

N2 - The aim of the Horizon 2020 unCoVer project (Unravelling Data for Rapid Evidence-Based Response to COVID-19) is to coordinate research expertise in utilising Real World Data (RWD) to investigate the underlying risk factors for COVID-19 infection and severity, the effectiveness of treatments and the impact on health systems. RWD is particularly useful in a dynamic health context as it is relevant, timely, and more ecologically valid. Pooling clinical databases and integrating epidemiological principles and powerful biostatistical tools optimises resources and fully exploits routinely-collected data.

AB - The aim of the Horizon 2020 unCoVer project (Unravelling Data for Rapid Evidence-Based Response to COVID-19) is to coordinate research expertise in utilising Real World Data (RWD) to investigate the underlying risk factors for COVID-19 infection and severity, the effectiveness of treatments and the impact on health systems. RWD is particularly useful in a dynamic health context as it is relevant, timely, and more ecologically valid. Pooling clinical databases and integrating epidemiological principles and powerful biostatistical tools optimises resources and fully exploits routinely-collected data.

KW - Data sharing

KW - Computer science

KW - Exploit

KW - Data science

KW - Context (archaeology)

KW - Pooling

KW - Documentation

KW - Data access

KW - Data Protection Act 1998

KW - Data anonymization

KW - Research ethics

KW - Big data

KW - Knowledge management

KW - Information privacy

KW - Computer security

KW - Medicine

KW - Data mining

KW - Database

KW - Paleontology

KW - Alternative medicine

KW - Pathology

KW - Artificial intelligence

KW - Psychiatry

KW - Biology

KW - Programming language

UR - https://openalex.org/W4307384736

U2 - 10.1093/eurpub/ckac130.060

DO - 10.1093/eurpub/ckac130.060

M3 - Meeting abstract

SN - 1101-1262

VL - 32

JO - European Journal of Public Health

JF - European Journal of Public Health

IS - 3

T2 - 15th European Public Health Conference

Y2 - 9 November 2022 through 12 November 2022

ER -

Research ethics with real-world data (RWD) on COVID-19 infections: the unCoVer study

Abstract

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this