What's wrong with the paper I linked?

The paper you linked to says:

"A mathematical model of COVID-19 transmission and vaccination was separately fit to reported COVID-19 mortality and all-cause excess mortality in 185 countries and territories."

This is not a study of actual lives saved. It's a model. Modelling proves absolutely nothing. It's a fairy tale and pure junk science.

From the paper:

• They assume that Delta results in 145% higher hospitalisation rate than the original virus, which is counter-factual. In reality, the Delta strain was no more serious than earlier strains, and likely less serious:
  • No difference in risk of hospitalization between reported cases of the SARS-CoV-2 Delta variant and Alpha variant in Norway
  • "Alpha variant period compared to the Delta showed an increased risk of ICU admission..." Source: Severity of COVID-19 cases in the months of predominance of the Alpha and Delta variants
  • Hospital admission and emergency care attendance risk for SARS-CoV-2 delta (B.1.617.2) compared with alpha (B.1.1.7) variants of concern: a cohort study found almost identical risk of hospitalisation: 2.2% for alpha and 2.3% for delta.

(Disclaimer on that last paper: the authors quote a hazard ratio for this, which suggests to me they had no fucking clue what they were doing and just pushed buttons on their stats software until they got a number that they liked. Hazard ratios are very hard to interpret correctly even for experts but in this case the risk of hospitalisation from delta and alpha are clearly almost identical.)

Modelling Delta as almost fifty percent more severe than earlier strains is going to massively overestimate the unvaccinated deaths according to this model. This alone is enough to condemn it as junk science.

The paper is biased. It models immune escape from previous infection, but does not model vaccine escape. It even states: "If immune escape was higher than we assumed, more of the population would have been susceptible to re-infection and consequently more deaths from COVID-19 could have been averted by vaccination" which is fair enough but it makes no mention of the reverse scenario: if vaccine escape was included more vaccinated people would be susceptible to re-infection and consequently fewer deaths would be averted by vaccination.

Edit: oops, I made a mistake, the model does seemingly allow for breakthough infections of vaccinated people. So that's one criticism removed.

The paper uses completely bogus estimates of the IFR (infection fatality rate): 0.23% for countries with mostly younger people, and 1.15% for countries with more elderly people. These numbers, especially the second, are ludicrously high, and consequently they inflate the number of Covid deaths drastically.

In 2020, the WHO published a peer-reviewed estimate of Covid’s overall IFR of about 0.23% globally. Soon afterwards another peer-reviewed study revised that figure downward to about 0.15% globally. The latest research from John Ioannidis et al finds a global IFR of 0.03% and 0.07% for the 0-59 and 0-69 age groups.

There is absolutely no justification for an overall IFR of 1.15% unless you're going to assume that half the population is over 70. I would say that more realistic numbers are about 0.05 for countries with "young" populations and 0.1 for those with "old" populations.

Quoting the paper:

• "we assume that all vaccinated individuals have a 50% reduction in infectiousness for breakthrough infections" -- there's no good evidence for this assumption, or indeed even a good reason for it. In reality, breakthrough infections are just as infectious as non-breakthrough ones.

• "To simplify the model parameterisation, in both epidemics we assume a constant vaccine efficacy of 60% against infection and 90% against disease" -- both numbers are bogus. Vaccine efficacy against infection is not constant: it is typically negative for a week or two after vaccination due to immune suppression, then rises to possibly something as high as 40 or 50% for perhaps as long as 30 or 40 days, then falls to zero again. Efficacy against disease is more or less zero: asymptomatic infections are rare.

• That statement is then contradicted by their Supplementary Table 1, where they use different vaccine efficacies according to vaccine type. The paper doesn't explain the contradiction.

• "The standard deviation σ can be expressed as (mathematical formula) where r is the dispersion parameter and assumed to be equal to 7" (emphasis added). Why seven? Why not six, or eight? Or three? Or fifteen?

• "Additionally, the total number of deaths related to the epidemic is assumed to be described by the Negative Binomial distribution with a dispersion parameter of 40." The Negative Binomial distribution is the standard distribution used for modelling epidemics (which doesn't mean it is necessarily a good model, only that it is the standard, conventional choice that everyone uses) but what's the justification for the choice of 40? Why not 39, or 41, or 20, or 80?

The point is, all of these parameters can be varied, and even if you don't like my numbers, the numbers used in the model aren't god-given, they're just numbers the modellers chose. They could have chosen different numbers. This is an exercise in mathematical modelling and by choosing values for the parameters they can get any result they like.

Want to prove that vaccination saved millions? Choose this model and this set of parameters. Want to prove the opposite? Tweak the model and/or the parameters. Since both the model and the parameter values are made up, you can choose anything that looks plausible.

CC u/SeethingPeasant