Adjusting Expected Deaths for Mortality Displacement During the COVID-19 Pandemic: A Model Based Counterfactual Approach at the Level of Individuals

52 Pages Posted: 13 Jul 2022 Last revised: 10 Aug 2023

See all articles by Richard Holleyman

Richard Holleyman

UK Health Security Agency; Newcastle University - Population Health Sciences Institute

Sharmani Barnard

Office for Health Improvement and Disparities

Clarissa Bauer-Staeb

Office for Health Improvement and Disparities

Andrew Hughes

Office for Health Improvement and Disparities

Sam Dunn

Office for Health Improvement and Disparities

Sebastian Fox

Office for Health Improvement and Disparities

John Newton

Office for Health Improvement and Disparities

Justine Fitzpatrick

Office for Health Improvement and Disparities

Zachary Waller

Office for Health Improvement and Disparities

David Deehan

Newcastle Upon Tyne Hospitals NHS Foundation Trust

Andre Charlett

UK Health Security Agency

Celia Gregson

University of Bristol - Musculoskeletal Research Unit

Rebecca Wilson

University of Liverpool - Department of Public Health, Policy and Systems

Paul Fryers

Office for Health Improvement and Disparities

Peter Goldblatt

University College London - Department of Epidemiology and Public Health

Paul Burton

Newcastle University - Population Health Sciences Institute

Date Written: June 22, 2022

Abstract

Background: Near-real time surveillance of excess mortality has been an essential tool during the COVID-19 pandemic. It remains critical for monitoring mortality as the pandemic wanes, to detect fluctuations in the death rate associated both with the longer-term impact of the pandemic (e.g. infection, containment measures and reduced service provision by the health and other systems) and the responses that followed (e.g. curtailment of containment measures, vaccination and the response of health and other systems to backlogs). Following the relaxing of testing and social distancing regimes, across many countries, it becomes critical to measure the impact of COVID-19 infection. However, prolonged periods of mortality in excess of the expected across entire populations has raised doubts over the validity of using unadjusted historic estimates of mortality to calculate the expected numbers of deaths that form the baseline for computing numbers of excess deaths because many individuals died earlier than they would otherwise have done: i.e. their mortality was displaced earlier in time to occur during the pandemic rather than when historic rates predicted. This is also often termed “harvesting” in the literature.

Methods: We present a novel Cox-regression-based methodology using time-dependent covariates to estimate the profile of the increased risk of death across time in individuals who contracted COVID-19 among a population of hip fracture patients in England (N=98,365). We use these hazards to simulate a distribution of survival times, in the presence of a COVID-19 positive test, and then calculate survival times based on hazard rates without a positive test and use the difference between the medians of these distributions to estimate the number of days a death has been displaced. This methodology is applied at the individual level, rather than the population level to provide a better understanding of the impact of a positive COVID-19 test on the mortality of groups with different vulnerabilities conferred by sociodemographic and health characteristics. Finally, we apply the mortality displacement estimates to adjust estimates of excess mortality using a “ball and urn” model.

Results: Among the exemplar population we present an end-to-end application of our methodology to estimate the extent of mortality displacement. A greater proportion of older, male and frailer individuals were subject to significant displacement while the magnitude of displacement was higher in younger females and in individuals with lower frailty: groups who, in the absence of COVID-19, should have had a substantial life expectancy.

Conclusion: Our results indicate that calculating the expected number of deaths following the first wave of the pandemic in England based solely on historical trends results in an overestimate, and excess mortality will therefore be underestimated. Our findings, using this exemplar dataset are conditional on having experienced a hip fracture, which is not generalisable to the general population. Fractures that impede mobility in the weeks that follow the accident/surgery considerably shorten life expectancy and are in themselves markers of significant frailty. It is therefore important to apply these novel methods to the general population, among whom we anticipate strong patterns in mortality displacement – both in its length and prevalence – by age, sex, frailty and types of comorbidities. This counterfactual method may also be used to investigate a wider range of disruptive population health events. This has important implications for public health monitoring and the interpretation of public health data in England and globally.

Note:
Funding Information: RH was supported to undertake this study by grants from Orthopaedic Research UK (ref. 541) and a Royal College of Surgeons of England research fellowship funded through a generous donation from the Shears Foundation. CLG receives funding from Versus Arthritis (ref. 22086).

Conflict of Interests: No conflicts of interest declared by any author.

Ethical Approval: Study governance approval was granted by the UK Healthcare Quality Improvement Partnership in June 2020 (reference: HQIP286). National excess death modelling was carried out as part of Public Health England’s (PHE, now the Office for Health Improvement and Disparities (OHID)) responsibility to manage the COVID-19 pandemic. PHE/OHID have a legal basis, provided by Regulation 3 of The Health Service (Control of Patient Information) Regulations 2002, to process confidential patient information in order to monitor the impact of SARS-COV-2 infection on the population and to respond to the pandemic.

Keywords: Excess, death, mortality, displacement, COVID-19, Public Health, counterfactual

Suggested Citation

Holleyman, Richard and Barnard, Sharmani and Bauer-Staeb, Clarissa and Hughes, Andrew and Dunn, Sam and Fox, Sebastian and Newton, John and Fitzpatrick, Justine and Waller, Zachary and Deehan, David and Charlett, Andre and Gregson, Celia and Wilson, Rebecca and Fryers, Paul and Goldblatt, Peter and Burton, Paul, Adjusting Expected Deaths for Mortality Displacement During the COVID-19 Pandemic: A Model Based Counterfactual Approach at the Level of Individuals (June 22, 2022). Available at SSRN: https://ssrn.com/abstract=4144980 or http://dx.doi.org/10.2139/ssrn.4144980

Richard Holleyman (Contact Author)

UK Health Security Agency

London
United Kingdom

Newcastle University - Population Health Sciences Institute ( email )

United Kingdom

Sharmani Barnard

Office for Health Improvement and Disparities ( email )

Department of Health and Social Care
39 Victoria Street, London
London, SW1H0EU
United Kingdom

Clarissa Bauer-Staeb

Office for Health Improvement and Disparities ( email )

Department of Health and Social Care
39 Victoria Street
London, SW1H 0EU
United Kingdom

Andrew Hughes

Office for Health Improvement and Disparities ( email )

Department of Health and Social Care
39 Victoria Street
London, SW1H 0EU
United Kingdom

Sam Dunn

Office for Health Improvement and Disparities ( email )

Department of Health and Social Care
39 Victoria Street
London, SW1H 0EU
United Kingdom

Sebastian Fox

Office for Health Improvement and Disparities ( email )

Department of Health and Social Care
39 Victoria Street
London, SW1H 0EU
United Kingdom

John Newton

Office for Health Improvement and Disparities ( email )

Department of Health and Social Care
39 Victoria Street
London, SW1H 0EU
United Kingdom

Justine Fitzpatrick

Office for Health Improvement and Disparities ( email )

Department of Health and Social Care
39 Victoria Street
London, SW1H 0EU
United Kingdom

Zachary Waller

Office for Health Improvement and Disparities ( email )

Department of Health and Social Care
39 Victoria Street
London, SW1H 0EU
United Kingdom

David Deehan

Newcastle Upon Tyne Hospitals NHS Foundation Trust ( email )

Newcastle
United Kingdom

Andre Charlett

UK Health Security Agency ( email )

London
United Kingdom

Celia Gregson

University of Bristol - Musculoskeletal Research Unit ( email )

Bristol
United Kingdom

Rebecca Wilson

University of Liverpool - Department of Public Health, Policy and Systems ( email )

Liverpool, L69 3GB
United Kingdom

Paul Fryers

Office for Health Improvement and Disparities ( email )

Department of Health and Social Care
39 Victoria Street
London, SW1H 0EU
United Kingdom

Peter Goldblatt

University College London - Department of Epidemiology and Public Health ( email )

1-19 Torrington Place
London, FL WC1E 6BT
United Kingdom

Paul Burton

Newcastle University - Population Health Sciences Institute ( email )

United Kingdom

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