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

article

Peter Hanlon¹  Fergus Chadwick¹  Anoop Shah²  Rachael Wood²  Jon Minton³  Gerry McCartney⁴  Colin Fischbacher³  Frances S. Mair¹  Dirk Husmeier¹  Jason Matthiopoulos¹  David A. McAllister¹ 

[1] University of Glasgow;University of Edinburgh;Public Health Scotland;Scottish Public Health Observatory, NHS Health Scotland

关键词: COVID-19;    Coronavirus;    Multimorbidity;    Epidemiology;    noncommunicable diseases;   

DOI  :  10.12688/wellcomeopenres.15849.3

学科分类：内科医学

来源: Wellcome

【 摘 要 】

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: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.

【 授权许可】

CC BY