Literature DB >> 32691080

Valuing the years of life lost due to COVID-19: the differences and pitfalls.

Brecht Devleesschauwer1,2, Scott A McDonald3, Niko Speybroeck4, Grant M A Wyper5.   

Abstract

Entities:  

Year:  2020        PMID: 32691080      PMCID: PMC7370635          DOI: 10.1007/s00038-020-01430-2

Source DB:  PubMed          Journal:  Int J Public Health        ISSN: 1661-8556            Impact factor:   3.380


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The only thing that is certain about death is that upon it, no life remains, and that the risk of death during a person’s lifetime is 1. These facts cannot be disputed; however, assessments over how much life has been prematurely lost upon death have led to polarised views. The impact of COVID-19 is drawing increased attention on how we approach putting a value on the life prematurely lost by death (Appleby 2020; Hanlon et al. 2020; Kirigia and Muthuri 2020). Years of life lost to premature mortality (YLL) is a frequently used population health metric, originating back to the 1940s (Haenszel 1950). The idea is appealingly simple—instead of merely counting the number of deaths, each death is weighted as a function of the age at death, reflecting the common appreciation that deaths at young ages are more severe than deaths at advanced ages. However, there is no single unique way to operationalise the concept, reflecting the reality that YLL can never be observed. Indeed, the estimation of YLL requires assumptions on the counterfactual, parallel world that did not happen—how long would the person have lived had they not have died? The debate around this normative assumption is largely centred on the choice of mortality risk that residual values for age-conditional life expectancy in YLL calculations are based on. Should they be based upon mortality risks that are country-specific, or risks that are external to the population studied, and are chosen to be aspirationally low? It may seem rational to use national life tables, reflecting the country-specific mortality risks, until we estimate residual life expectancy for sub-national units. This highlights that particular groups, such as those with a socioeconomic disadvantage, have very different mortality risks. Take Singapore, which has the highest life expectancy in the world (Institute for Health Metrics and Evaluation. GBD results tool. Global Health Data Exchange 2020). The mortality risk in Singapore is not representative for that in Scotland—for instance, the former country has a residual life expectancy for females aged 75 that is 3.67 years higher than the latter. However, looking at differences between the most and least deprived areas for this demographic in Scotland also yields a large disparity, of 2.91 years (National Records of  Scotland 2016). This raises the issue of why people are comfortable with the idea that life could be valued differently between countries, but are then uncomfortable with the idea of assigning different values of residual life expectancy on the basis of an individual’s sub-national location. Using a national life table furthermore creates a paradox by which increased mortality risks, of for instance the COVID-19 pandemic, could cause life expectancy to go down, which could result in a contradictory reduction in estimates of YLL (McCartney et al. 2020). A second major point of discussion is whether YLL should be corrected for comorbidities of the deceased (Hanlon et al. 2020; Cassini et al. 2019). This is particularly the case for COVID-19, which frequently causes death in the old and frail, and those with underlying chronic conditions. Some thus argue that valuing the death of a 90-year-old nursing home resident with advanced cardiac decompensation using the national life expectancy for 90-year olds would “overestimate” YLL due to COVID-19. What these discussions make clear is the importance of transparency in documenting the exact method used to calculate YLL. Since YLL cannot be observed, they can only be estimated, and obviously, the choice of counterfactual will have a major influence on the resulting estimates. Conversely, YLL can never be “overestimated” or “underestimated”, since there is no “true” value of YLL. The paradoxes and pitfalls described here can be circumvented by using a “standard” life table, based on aspirational mortality risks. Although these mortality risks may be lower than are currently observed in countries, they have many comparative and ethical advantages. This approach ensures that we do not accept a level of mortality risk merely because we are used to it, as to do this means we lose focus of the factors and environment that are responsible for it. Importantly, assessments on the value of human life are equal between, and within, countries. This is important as it means we are upfront about the extent of national and global inequalities, and the World Health Organisation’s goal of health for all and what that means (World Health Organisation 2020). Finally, through assuming a counterfactual based on a world free of disease, standard life tables allow measuring the impact of different diseases at the same level, which is essential for comparative studies such as the Global Burden of Disease study (GBD 2017 DALYs and HALE Collaborators 2018).
  5 in total

1.  A standardized rate for mortality defined in units of lost years of life.

Authors:  W HAENSZEL
Journal:  Am J Public Health Nations Health       Date:  1950-01

2.  Tackling covid-19: are the costs worth the benefits?

Authors:  John Appleby
Journal:  BMJ       Date:  2020-04-21

3.  Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

Authors: 
Journal:  Lancet       Date:  2018-11-10       Impact factor: 79.321

4.  Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis.

Authors:  Alessandro Cassini; Liselotte Diaz Högberg; Diamantis Plachouras; Annalisa Quattrocchi; Ana Hoxha; Gunnar Skov Simonsen; Mélanie Colomb-Cotinat; Mirjam E Kretzschmar; Brecht Devleesschauwer; Michele Cecchini; Driss Ait Ouakrim; Tiago Cravo Oliveira; Marc J Struelens; Carl Suetens; Dominique L Monnet
Journal:  Lancet Infect Dis       Date:  2018-11-05       Impact factor: 25.071

5.  The fiscal value of human lives lost from coronavirus disease (COVID-19) in China.

Authors:  Joses M Kirigia; Rose Nabi Deborah Karimi Muthuri
Journal:  BMC Res Notes       Date:  2020-04-01
  5 in total
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Journal:  PLoS Negl Trop Dis       Date:  2022-07-06

Review 2.  Burden of Disease of COVID-19: Strengthening the Collaboration for National Studies.

Authors:  Sara Monteiro Pires; Grant M A Wyper; Annelene Wengler; José L Peñalvo; Romana Haneef; Declan Moran; Sarah Cuschieri; Hernan G Redondo; Robby De Pauw; Scott A McDonald; Lynelle Moon; Jad Shedrawy; Elena Pallari; Periklis Charalampous; Brecht Devleesschauwer; Elena Von Der Lippe
Journal:  Front Public Health       Date:  2022-06-03

3.  Conducting national burden of disease studies and knowledge translation in eight small European states: challenges and opportunities.

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Journal:  Health Res Policy Syst       Date:  2022-10-21

4.  The COVID-19 Disease Burden in Germany in 2020—Years of Life Lost to Death and Disease Over the Course of the Pandemic.

Authors:  Alexander Rommel; Elena von der Lippe; Dietrich Plass; Thomas Ziese; Michaela Diercke; Matthias An der Heiden; Sebastian Haller; Annelene Wengler
Journal:  Dtsch Arztebl Int       Date:  2021-03-05       Impact factor: 5.594

5.  Reflections on key methodological decisions in national burden of disease assessments.

Authors:  Elena von der Lippe; Brecht Devleesschauwer; Michelle Gourley; Juanita Haagsma; Henk Hilderink; Michael Porst; Annelene Wengler; Grant Wyper; Ian Grant
Journal:  Arch Public Health       Date:  2020-12-31

6.  Optimal Allocation of the Limited COVID-19 Vaccine Supply in South Korea.

Authors:  Eunha Shim
Journal:  J Clin Med       Date:  2021-02-04       Impact factor: 4.241

7.  Years of life lost (YLL) associated with COVID-19 deaths in Khorasan-RAZAVI province, Iran.

Authors:  Mehdi Yousefi; Somayeh Fazaeli; Saeed Mohammad-Pour
Journal:  J Public Health (Oxf)       Date:  2021-12-20       Impact factor: 2.341

8.  Premature mortality attributable to COVID-19: potential years of life lost in 17 countries around the world, January-August 2020.

Authors:  Maider Pagola Ugarte; Souzana Achilleos; Annalisa Quattrocchi; John Gabel; Ourania Kolokotroni; Constantina Constantinou; Nicoletta Nicolaou; Jose Manuel Rodriguez-Llanes; Qian Huang; Olesia Verstiuk; Nataliia Pidmurniak; Jennifer Wenjing Tao; Bo Burström; Petra Klepac; Ivan Erzen; Mario Chong; Manuel Barron; Terje P Hagen; Zhanna Kalmatayeva; Kairat Davletov; Inbar Zucker; Zalman Kaufman; Maia Kereselidze; Levan Kandelaki; Nolwenn Le Meur; Lucy Goldsmith; Julia A Critchley; Maria Angelica Pinilla; Gloria Isabel Jaramillo; Domingos Teixeira; Lara Ferrero Goméz; Jackeline Lobato; Carolina Araújo; Joseph Cuthbertson; Catherine M Bennett; Antonis Polemitis; Andreas Charalambous; Christiana A Demetriou
Journal:  BMC Public Health       Date:  2022-01-09       Impact factor: 3.295

9.  Different approaches to quantify years of life lost from COVID-19.

Authors:  Tamás Ferenci
Journal:  Eur J Epidemiol       Date:  2021-06-10       Impact factor: 8.082

10.  Recommendations to plan a national burden of disease study.

Authors:  Romana Haneef; Jürgen Schmidt; Anne Gallay; Brecht Devleesschauwer; Ian Grant; Alexander Rommel; Grant Ma Wyper; Herman Van Oyen; Henk Hilderink; Thomas Ziese; John Newton
Journal:  Arch Public Health       Date:  2021-07-07
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