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Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions

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Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions. / Lyons, J.; Akbari, A.; Torabi, F. et al.
In: BMJ Open, Vol. 10, No. 10, e043010, 21.10.2020.

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Lyons, J, Akbari, A, Torabi, F, Davies, GI, North, L, Griffiths, R, Bailey, R, Hollinghurst, J, Fry, R, Turner, SL, Thompson, D, Rafferty, J, Mizen, A, Orton, C, Thompson, S, Au-Yeung, L, Cross, L, Gravenor, MB, Brophy, S, Lucini, B, John, A, Szakmany, T, Davies, J, Davies, C, Thomas, DR, Williams, C, Emmerson, C, Cottrell, S, Connor, TR, Taylor, C, Pugh, RJ, Diggle, P, John, G, Scourfield, S, Hunt, J, Cunningham, AM, Helliwell, K & Lyons, R 2020, 'Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions', BMJ Open, vol. 10, no. 10, e043010. https://doi.org/10.1136/bmjopen-2020-043010

APA

Lyons, J., Akbari, A., Torabi, F., Davies, G. I., North, L., Griffiths, R., Bailey, R., Hollinghurst, J., Fry, R., Turner, S. L., Thompson, D., Rafferty, J., Mizen, A., Orton, C., Thompson, S., Au-Yeung, L., Cross, L., Gravenor, M. B., Brophy, S., ... Lyons, R. (2020). Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions. BMJ Open, 10(10), Article e043010. https://doi.org/10.1136/bmjopen-2020-043010

Vancouver

Lyons J, Akbari A, Torabi F, Davies GI, North L, Griffiths R et al. Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions. BMJ Open. 2020 Oct 21;10(10):e043010. doi: 10.1136/bmjopen-2020-043010

Author

Bibtex

@article{d26866b3663d487ba03a6e7fd1e11ebd,
title = "Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions",
abstract = "INTRODUCTION: The emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions. METHODS AND ANALYSIS: Two privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection. ETHICS AND DISSEMINATION: The Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.",
keywords = "COVID-19, epidemiology, health informatics, public health",
author = "J. Lyons and A. Akbari and F. Torabi and G.I. Davies and L. North and R. Griffiths and R. Bailey and J. Hollinghurst and R. Fry and S.L. Turner and D. Thompson and J. Rafferty and A. Mizen and C. Orton and S. Thompson and L. Au-Yeung and L. Cross and M.B. Gravenor and S. Brophy and B. Lucini and A. John and T. Szakmany and J. Davies and C. Davies and D.R. Thomas and C. Williams and C. Emmerson and S. Cottrell and T.R. Connor and C. Taylor and R.J. Pugh and P. Diggle and G. John and S. Scourfield and J. Hunt and A.M. Cunningham and K. Helliwell and R. Lyons",
year = "2020",
month = oct,
day = "21",
doi = "10.1136/bmjopen-2020-043010",
language = "English",
volume = "10",
journal = "BMJ Open",
issn = "2044-6055",
publisher = "BMJ Publishing Group Ltd",
number = "10",

}

RIS

TY - JOUR

T1 - Understanding and responding to COVID-19 in Wales

T2 - protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions

AU - Lyons, J.

AU - Akbari, A.

AU - Torabi, F.

AU - Davies, G.I.

AU - North, L.

AU - Griffiths, R.

AU - Bailey, R.

AU - Hollinghurst, J.

AU - Fry, R.

AU - Turner, S.L.

AU - Thompson, D.

AU - Rafferty, J.

AU - Mizen, A.

AU - Orton, C.

AU - Thompson, S.

AU - Au-Yeung, L.

AU - Cross, L.

AU - Gravenor, M.B.

AU - Brophy, S.

AU - Lucini, B.

AU - John, A.

AU - Szakmany, T.

AU - Davies, J.

AU - Davies, C.

AU - Thomas, D.R.

AU - Williams, C.

AU - Emmerson, C.

AU - Cottrell, S.

AU - Connor, T.R.

AU - Taylor, C.

AU - Pugh, R.J.

AU - Diggle, P.

AU - John, G.

AU - Scourfield, S.

AU - Hunt, J.

AU - Cunningham, A.M.

AU - Helliwell, K.

AU - Lyons, R.

PY - 2020/10/21

Y1 - 2020/10/21

N2 - INTRODUCTION: The emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions. METHODS AND ANALYSIS: Two privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection. ETHICS AND DISSEMINATION: The Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.

AB - INTRODUCTION: The emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions. METHODS AND ANALYSIS: Two privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection. ETHICS AND DISSEMINATION: The Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.

KW - COVID-19

KW - epidemiology

KW - health informatics

KW - public health

U2 - 10.1136/bmjopen-2020-043010

DO - 10.1136/bmjopen-2020-043010

M3 - Journal article

VL - 10

JO - BMJ Open

JF - BMJ Open

SN - 2044-6055

IS - 10

M1 - e043010

ER -