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.

Figure 1

Data linkage of multiple demographic and healthcare data sources used in the creation of two population-wide cohorts: C20 and C16. ADDD, Annual District Death Daily; ADDE, Annual District Death Extract; CAPD, Postponed Admitted Procedures; CARE, Care homes Index; CCDS, Critical Care Data Set; CDDS, Consolidated Death Data Source; CVSP, COVID-19 Shielded People list; CVST, KCL Zoe Symptom Tracker App; EDDD, Emergency Department Dataset Daily; EDDS, Emergency Department Data Set; ICNARC, Intensive Care National Audit & Research Centre; LIMS, Laboratory Information Management System; LSOA, Lower Layer Super Output Area; OPDW, Out Patient Dataset for Wales; PEDW, Patient Episode; PLASC, Pupil Level Annual School Census; SAIL, Secure Anonymised Information Linkage; SQL, Structured Query Language; WDSD, Wash Demographic Service Dataset; WIMD, Welsh Index of Multiple Deprivation; WLGP, Welsh Longitudinal General Practise; WRRS, Wales Results Reporting Service.

Figure 2

Flow diagram of the C20 cohort inclusion criteria. WDSD, Wales Demographic Service Dataset.