Avram Altaras writes:
This study is being quoted to justify the need for booster shorts for age > 60 and the immunocompromized.
From what in learned in the regression class, they should have added the prevalence of the delta varient at time of pcr test as a variable in the regression, no?
Yes, I think so. Whenever you’re trying to estimate a causal effect when comparing two groups, you should adjust for relevant pre-treatment variables.
They need to split it up by reason for the test. At least half the apparent effectiveness is due to differences in testing.
Waning immunity and selection for escape variants (the furin cleavage site of delta is mutated so the S1 region of the spike targeted by the vaccines is ~3x more likely to be cleaved *before* it leaves the cell) ensures that the protection against mild illness won’t last long.
Until the T-cell epitopes of the spike protein mutate, the vaccinated should still be protected against severe illness relative to the unexposed. Of course, exposure to the full virus means your body has seen all 29 viral proteins so immunity will be far more robust. It also means you will have mucosal immunity, which the vaccines fail to elicit.
It’s odd how this analysis ignores those with previous evidence of infection, that should be around half the population of most countries.
“At least half the apparent effectiveness is due to differences in testing.”
I’m curious how you calculated that.
Probably the same way the study authors calculated that differences in testing accounts for negligible amount of the difference!
From this study on infections in california: https://statmodeling.stat.columbia.edu/2021/07/20/the-challenges-of-statistical-measurement-in-an-environment-where-bad-measurement-and-junk-science-get-hyped/#comment-1932490
Or, potentially better, match of date and location of test, thus making comparisons for people facing the same conditions, however those ought to be described (including prevalence statistics).