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> I know that P.1 (Brazil variant) seems to totally avoid natural immunity.

This is completely false, and is a poor extrapolation from a faulty initial data point. There have now been several publications -- including the J&J clinical trial data itself [1] -- which show that immune responses induced by non-variant virus (or vaccine) are protective against the Brazilian variant.

There is some evidence that a particular mutation in the spike protein of the Brazilian variant can partially evade neutralization by particular antibodies, but this is far from "totally avoiding natural immunity".

> The proof is from the city of Manaus, which was over 75% infected in October 2020.

This number is based on a study that was written in summer 2020 [2], and used a number of questionable "adjustments" to the raw seroprevalence data to arrive at their conclusion. Raw seroprevalence data (Figure 2) was closer to 30%, not 75%.

The parsimonious conclusion is that the paper citing 75% seroprevalence in Manaus was wrong. Science really should retract this paper, or publish an addendum. It's an example where low-quality science is leading to a lot of unnecessary panic and speculation.

[1] https://www.ucsf.edu/news/2021/03/420071/how-effective-johns...

[2] https://science.sciencemag.org/content/371/6526/288

Use of blood donors is itself questionable and open to selection bias. Particularly if blood donors were getting free antibody testing and seeing the results, but even if they weren't. The authors seem to only have considered the demographics of the sample selection, and somewhat poorly.

Oh, definitely. I don't dispute the need for the adjustments that the authors were applying. It's just that...after a certain amount of "adjustment", what good is your prediction, anyway? Correcting the seroprevalence by a few percent is one thing. "Correcting" it by over 200% is quite another.

Basically, folks are going back to this paper (or more realistically: not reading it at all, and simply parroting headlines), ignoring the intense massaging of the data, and claiming that reality disagrees with the predictions from the paper, therefore reality must be wrong.

Right, I would argue there's factors that might call for a 200% correction the other direction. You just can't validate their tea leaf reading here of what are the correct set of corrections.

You say totally false, but your own favored hand-on-the-scale (which could be reasonable) adjustment leaves it at NOT in any way totally false

There is no adjustment. Those are the raw values.

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