Scaling COVID-19 against inequalities: should the policy response consistently match the mortality challenge?
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Abstract
The mortality impact of COVID-19 has thus far been described in terms of crude death counts. We aimed to calibrate the scale of the modelled mortality impact of COVID-19 using age-standardised mortality rates and life expectancy contribution against other, socially determined, causes of death in order to inform governments and the public.
Methods
We compared mortality attributable to suicide, drug poisoning and socioeconomic inequality with estimates of mortality from an infectious disease model of COVID-19. We calculated age-standardised mortality rates and life expectancy contributions for the UK and its constituent nations.
Results
Mortality from a fully unmitigated COVID-19 pandemic is estimated to be responsible for a negative life expectancy contribution of −5.96 years for the UK. This is reduced to −0.33 years in the fully mitigated scenario. The equivalent annual life expectancy contributions of suicide, drug poisoning and socioeconomic inequality-related deaths are −0.25, −0.20 and −3.51 years, respectively. The negative impact of fully unmitigated COVID-19 on life expectancy is therefore equivalent to 24 years of suicide deaths, 30 years of drug poisoning deaths and 1.7 years of inequality-related deaths for the UK.
Conclusion
Fully mitigating COVID-19 is estimated to prevent a loss of 5.63 years of life expectancy for the UK. Over 10 years, there is a greater negative life expectancy contribution from inequality than around six unmitigated COVID-19 pandemics. To achieve long-term population health improvements it is therefore important to take this opportunity to introduce post-pandemic economic policies to ‘build back better’.
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SciScore for 10.1101/2020.05.04.20090761: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Strengths and limitations: There is an urgency in being able to calibrate the mortality risk due to COVID-19 in order to be able to ascertain the appropriate level of control measures required. This study therefore uses the available modelled data that have been used to justify the control measures in place at the time of writing …
SciScore for 10.1101/2020.05.04.20090761: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Strengths and limitations: There is an urgency in being able to calibrate the mortality risk due to COVID-19 in order to be able to ascertain the appropriate level of control measures required. This study therefore uses the available modelled data that have been used to justify the control measures in place at the time of writing alongside routinely available and published data on other mortality risks that have been present in the UK and around the world for some time.11 There are, however, a number of limitations. We have had to model the age-specific mortality of COVID-19 by 5 year age band as this was not available in the Imperial College data. The exponential relationship between age and COVID-19 mortality alongside the open upper age bound in our data make the estimates at this upper age more uncertain. Similarly, the Imperial College modelling does not provide estimates by sex, although the emerging evidence suggests that the mortality rates are higher amongst men. This means that the life expectancy impacts of COVID-19 provided in this paper are likely to be overestimated because men have a systematically lower life expectancy than women and so the loss of lifespan for men will be less. It is also recognised that COVID-19 mortality rates are higher amongst those with co-morbidities for any given age-sex group.12 Our modelling does not differentiate between groups on this basis and is therefore likely to be a further source of systematic bias which overestimates the mo...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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