Ok, first, it's not like these scientists are just ignoring co-morbidities.
From the study:
"A significant aspect of COVID-19 deaths in calculating YLLs is that many of those who died of the disease had significant pre-existing medical conditions. Such deaths could be considered as displaced mortality in that these individuals on average would likely not reach the full life expectancy reported in actuarial tables. In their forecast model of COVID-19 deaths in the UK based on data from Italy, Hanlon et al. (2020) estimated that the greater pre-existing morbidity of those who died of COVID-19 reduced the estimated YLLs per COVID-19 death from 14 to 13 for men and 12 to 11 for women.15 In our analysis, we conservatively reduced the expected life expectancy by 25% to reflect the typically greater morbidity of COVID-19 decedents."
Here's Hanlon, et al:
The used various data sources to factor in types and # of cormorbidities into their estimates.
https://wellcomeopenresearch.org/articles/5-75/v1And a critique here:
I agree YLL is not a perfect measurement -- nothing is.
Read the comments on the Hanlon paper if you want more discussion.
https://wellcomeopenresearch.org/articles/5-137A few key points
1) Most older people have co-morbidities. The effect a co-morbidity has on life expectancy decreases as your cohort gets older, because bCM's get more common and this gets factored into life expectancy calculations. The preprint here has a reasonable discussion:
https://www.medrxiv.org/content/10.1101/2020.10.18.20214783v2.full.pdf+htmlParagraph here:
An important variable that this and other studies have not been able to adequately incorporate into this analysis is the effect of comorbidities on life expectancy of COVID-19 deaths which is due to a lack of appropriate statistical information. This must, therefore, be considered a potential source of error. The SARS-CoV-2 virus is known to infect and replicate in many different tissues and exacerbates problems in several organ systems including the kidney, liver, heart, lungs and brain (Lu et al., 2020; Chandrashekar et al., 2020). Any individual with problems in these systems or the immune system is likely to be more vulnerable to SARS-CoV-2 infection and suffer more severe outcomes as has been demonstrated for immune deficiencies. In addition, other health states qualifying as pre-existing conditions, such as obesity, hypertension, chronic kidney disease and diabetes are known comorbidity factors for COVID-19 (see CDC co-morbidity tables and references therein;
https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/evidence-table.html) and these cohorts of individuals have a shorter than average predicted life span. Deaths due to complications with pre-existing comorbid conditions would artificially increase the person-years lost in these calculations but are difficult to quantitate in this current analysis. However, most people over the age of 60 have comorbidities so these are already factored into the longevity tables. For example, one of the largest co-morbidity factors is diabetes (Table 10, 33,100 deaths out of 201,000, or 16.5% of COVID-19 deaths) and diabetes is thought to shorten life expectancy by approximately 8 years per individual and has lowered overall average life expectancy in the US by 0.83 and 0.89 years for males and females, respectively (Preston et al., 2018b). However, the prevalence of diabetes is 10.4% in the general population and its effects on life expectancy has already been factored into the actuarial tables. Thus, approximately 6% of the 194,000 COVID-19 deaths in our analysis, 11,640 in total, are likely due to excess diabetes deaths over the average amount in the population. This would result in an excess of 93,120 person-years, but this would need to be further adjusted for excess deaths per age because on average people over 80 years old have less than 8 years of residual life expectancy. As a result, diabetes may have less than a 4% impact on the current estimates as not all deaths are in individuals with a known co-morbidity. However, other comorbidities listed in Table 10 are actually at a lower prevalence than in the general population, i.e. Alzheimer’s disease and hypertension, and could be due to undercounting due to multiple comorbidities. Thus, it is not yet clear how to fully interpret these data and adjust our calculations. We include a 15% estimate of reduction in PYLL in the summary table (Table 11)."
2) You would need to make the case that people dying of COVID are extremely different that the 'reference' population used to calculate the baseline statistics. Is there a large stratification of severity among comorbidities that would affect the estimates by an order of magnitude? Maybe, but I haven't seen any evidence.
3). I'll admit that "10 years lost" is too simple an answer, but people are making claims that the true number is something around ~1 or less! It seems unlikely that those dying of COVID are so different than the rest of the elderly, comorbid population yet nobody has found data to support it. All these attempts to model have taken into account comorbidities in varyingly sophisticated ways from modeling in comorbidity data to just an arbitrary reduction in their final estimates.
Sorry, you can't just handwave away these studies and then try to push glaringly wrong arguments that use even more simple, uninformed math and data.