COVID-19 – exploring the implications of long-term condition type and extent of multimorbidity on years of life lost: a modelling study

Hanlon, P. et al. (2021) COVID-19 – exploring the implications of long-term condition type and extent of multimorbidity on years of life lost: a modelling study. Wellcome Open Research, 5, 75. (doi: 10.12688/wellcomeopenres.15849.3) (PMID:33709037) (PMCID:PMC7927210)

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Publisher's URL: https://doi.org/10.12688/wellcomeopenres.15849.3

Abstract

Background: COVID-19 is responsible for increasing deaths globally. As most people dying with COVID-19 are older with underlying long-term conditions (LTCs), some speculate that YLL are low. We aim to estimate YLL attributable to COVID-19, before and after adjustment for number/type of LTCs, using the limited data available early in the pandemic. Methods: We first estimated YLL from COVID-19 using WHO life tables, based on published age/sex data from COVID-19 deaths in Italy. We then used aggregate data on number/type of LTCs in a Bayesian model to estimate likely combinations of LTCs among people dying with COVID-19. We used routine UK healthcare data from Scotland and Wales to estimate life expectancy based on age/sex/these combinations of LTCs using Gompertz models from which we then estimate YLL. Results: Using the standard WHO life tables, YLL per COVID-19 death was 14 for men and 12 for women. After adjustment for number and type of LTCs, the mean YLL was slightly lower, but remained high (11.6 and 9.4 years for men and women, respectively). The number and type of LTCs led to wide variability in the estimated YLL at a given age (e.g. at ≥80 years, YLL was >10 years for people with 0 LTCs, and <3 years for people with ≥6). Conclusions: Deaths from COVID-19 represent a substantial burden in terms of per-person YLL, more than a decade, even after adjusting for the typical number and type of LTCs found in people dying of COVID-19. The extent of multimorbidity heavily influences the estimated YLL at a given age. More comprehensive and standardised collection of data (including LTC type, severity, and potential confounders such as socioeconomic-deprivation and care-home status) is needed to optimise YLL estimates for specific populations, and to understand the global burden of COVID-19, and guide policy-making and interventions.

Item Type:Articles
Additional Information:Version 3; peer review: 3 approved.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Minton, Dr Jonathan and McAllister, Professor David and Chadwick, Mr Fergus and McCartney, Dr Gerard and Hanlon, Dr Peter and Matthiopoulos, Professor Jason and Husmeier, Professor Dirk and Mair, Professor Frances
Creator Roles:
Hanlon, P.Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Writing – original draft, Writing – review and editing
Chadwick, F.Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review and editing
Mair, F. S.Writing – review and editing
Husmeier, D.Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review and editing
Matthiopoulos, J.Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review and editing
McAllister, D. A.Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing
Minton, J.Investigation, Methodology, Visualization, Writing – original draft, Writing – review and editing
McCartney, G.Conceptualization, Methodology, Writing – review and editing
Authors: Hanlon, P., Chadwick, F., Shah, A., Wood, R., Minton, J., McCartney, G., Fischbacher, C., Mair, F. S., Husmeier, D., Matthiopoulos, J., and McAllister, D. A.
College/School:College of Medical Veterinary and Life Sciences > Institute of Biodiversity Animal Health and Comparative Medicine
College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > General Practice and Primary Care
College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > Public Health
College of Science and Engineering > School of Mathematics and Statistics > Statistics
College of Social Sciences > School of Social and Political Sciences
College of Social Sciences > School of Social and Political Sciences > Sociology Anthropology and Applied Social Sciences
Journal Name:Wellcome Open Research
Publisher:F1000Research
ISSN:2398-502X
ISSN (Online):2398-502X
Published Online:23 April 2020
Copyright Holders:Copyright © 2020 Hanlon P et al.
First Published:First published in Wellcome Open Research 5:75
Publisher Policy:Reproduced under a Creative Commons licence

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
173492Combining efficacy estimates from clinical trials with the natural history obtained from large routine healthcare databases to determine net overall treatment benefitsDavid McAllisterWellcome Trust (WELLCOTR)201492/Z/16/ZInstitute of Health & Wellbeing
305232Understanding prevalence and impact of frailty in chronic illness and implications for clinical managementFrances MairMedical Research Council (MRC)MR/S021949/1HW - General Practice and Primary Care