What about the QALYs?

Since the arrival of SARS-CoV-2, figures have been used continuously. Hospital admissions, deaths, infections and later excess mortality. Which figures are used is a matter of choice and the purpose for which they are used. A commonly used measure in the healthcare sector is the QALY (Quality-Adjusted Life Years). These are the years of life that have been lost due to premature death from the consequences of covid-19 or the measures that were intended to prevent death. Below is the analysis.

How do we calculate a QALY?

It seems simple at first. At the time of death, you estimate how many years someone had left to live in good health without corona or measures. But we soon realize that even if you know the history of the deceased, it is difficult to estimate the number of years lost. If someone dies at the age of 40, did they "miss" 42 QALYs or was it "just their time"?

With this caveat, we're going to give it a try anyway. We do have to make the distinction between death from covid-19 and the "unexplained excess mortality". So we are not going to try to pinpoint a cause for the latter, but we will attach a number to it.

Death from corona

In previous articles, we have already seen that death from covid-19 is numerically very similar to an ordinary flu. They are mainly the vulnerable, often with one or more underlying sufferings. We also see that after a flu wave and also after the first corona wave, undermortality follows. This can be seen in this graph.

We set the under-mortality expectation at 18 months, with each 1/18th of the excess mortality wave as under-mortality. This is a simplified assumption, based on the regular excess mortality pattern in which seasonal influences also play a role. In reality, it's a curve that slowly bounces back to baseline. Essential to this is the age structure: Suppose a fatal disease is spreading that only affects children, then the undermortality looks very different. With the approximation of those 18 months, we can say that everyone who has died of corona died on average 9 months earlier, so 3/4 QALY per death. A strong flu year with a flu mortality of 6,000 leads to a net QALY loss of approximately 4,500.

Died of "unexplained excess mortality"

That is of course a difficult one, because these deceased people do not have a special characteristic. We do know how many deaths there were in total per week and per age, and we also know how many deaths there were from covid-19. But we don't know how long these deceased had to live if there had been no unexplained excess mortality.

In this graph (see our article in ResearchGate) we see the cumulative excess mortality over the 4 corona years. In 2020 there was only corona and the mortality pattern is roughly the same as in previous years. For 2021-2023, the entire curve has shifted to the left, so people died at least 5 years earlier than average.

We have a clue when we look at the possible explanations for this mortality. The first candidate is the vaccination. People would then have died from the side effects of the vaccine. If this were the case, the deceased would probably still have had a life expectancy of 82 years. But just as often, this is also contradicted, even with the argument that it was corona after all, without symptoms or positive tests. We don't go along with this.

Another frequently mentioned option is deferred care. Someone would have died due to the lack of proper care during the pandemic. Even then, you could assume that with the right care, life expectancy would still have been 82 years, but that is also an assumption.

The social consequences of the measures are mentioned. Suicide, less sports, domestic violence and so on. By the end of 2021, we already have most of these causes impossible, including the text of this article, also as a Dutch version.

We do not look for the causes, but only observe that these are all interventions, arising from our actions. All options assume a life expectancy that would be 82 years at death, but it remains a model assumption. Only when we know the real causes would we be able to say something more about this.

Another aspect is that we only look at mortality, while the consequences of diseases can also be expressed in QALYs. Lockdown depression, economic downturn, long-term effects of vaccinations and/or of Covid will also contribute to the number of QALYs lost.

The calculation

The calculation for the total number of QALYs lost is simple. For every death from covid-19, we count 9 months; For the unexplained excess mortality (mortality minus covid mortality) it is 82 minus the age at death, with a minimum of 1 year. For 2020, 100% of excess mortality was explained by covid-19. For 2021 to 2023, these percentages were 66.3%, 17.1% and 4.6%, divided between the excess mortality of around 12,000 per year. It is most insightful to display cumulatively, so that we can read the total number of lost QALYs on the right.

We read here that 9,675 QALYs were lost to covid-19 itself in the first year. 2021 was a year in which corona was still 66% responsible for excess mortality. In 2022 and 2023, we almost exclusively had to deal with "unexplained excess mortality".

The number of QALYs lost from 2021 to 2023 is 210,086. This is more than 20 times as much as what is attributable to Covid.

This is mainly caused by the shift to the lower ages. Under the age of 70, the interventions have caused a lot of suffering.

There will still be a lot of fighting to be done about what the real people responsible for this effect are and how they each contributed. It seems very likely that our efforts to limit covid mortality have made it twenty times worse.

Previous estimates

In the Gupta Report It was already calculated in June 2020 that the QALY loss in regular care (100K-400K) would be a factor of 10 to 20 higher than the number of QALY lost due to Covid (13K – 21K). So those numbers were in the same direction, at the time of the pandemic. The post-Covid years have continued that trend in population mortality rates. This is despite or because of interventions such as lockdowns, vaccination coercion, social invalidation, school closures, curfews and so on.

The government was aware of this scenario (see Former CBS director interprets chilling figures), but ignored the warnings of its officials in order to keep a clear path for the ordered vaccinations. Based on those calculations, 520,000 lost QALYs were found. As former CBS director Jan van der Zanden explains, that number is something to be said about it, but "Even if you divide 500,000 QALYs from that report by 2 or 3, the outcome is horrific."

Conclusions

• The number of QALY lost from 2021 to 2023 is 210,086. This is more than 20 times as much as what is attributable to Covid.
• This figure is flattering because it does not look at illness, economic decline and other QALY influences, only at death.
• These findings are in line with earlier estimates, including a report by Ministry of Economic Affairs officials that was supposed to underpin policymaking.