Covid vaccines: how effective? Variants, duration of immunity, efficacy on contamination and on severe cases?

[Christophe]

So a liar manipulator speculator pro vax takes 13 likes (000% bots?) ... if my Tweet, much more realistic in the analysis and above all not speculative, in fact 10 I could consider myself happy ...

Everything is rotten and corrupt on twitter!

[Christophe]

So a liar manipulator speculator pro vax takes 13 likes (000% of bots?) ... if my Tweet, much more realistic in the analysis and especially not speculative, in fact 95 I could consider myself happy ...

Everything is rotten and corrupt on twitter!

The proof that it is pipeau like, the news to which he replied barely made 300 likes ...



To stack this world of cheating and fake ass!

If they cheat like pigs with villainous methods on social media, do you think they are being honest in their studies?

Mouahahahahha band of trouts !!

[GuyGadeboisTheBack]

Everything is rotten and corrupt on twitter!

Frankly (Come in, eh ...), were you expecting something else? It's the same on Fessebouc ...

[Christophe]

LeParisien tries pro vax lobbying ... with a still speculative diagram ... 1% chance of being infected (based on ???), 90% of vaccinated (based on ??) and 90% of efficiency (based on Big Pharma promises only...)!

pro_vax.jpg (124.68 KiB) Viewed 624 times

[Christophe]

You have 10 minutes to return your copies!

If you do not even answer when we chew your job, do not try to lobbies our brains with your deviant mainstream news ... eh funny ...

[pedrodelavega]

[GuyGadeboisTheBack]

Check it out: Get out, CxxxxxD !!!

[Christophe]

What is this neneus diagram ...

Don't you want to personally answer where Israel is on the curves I drew this afternoon ?? Why ?

[Christophe]

Check it out: Get out, CxxxxxD !!!

Uh, calm there !!!

[ABC2019]

Go some math for those who like ...

Let there be two possible characteristics A and B in a population N.

The probability of having both A and B can be calculated in two equivalent ways
* either we say that we must have A (probability p (A)), but also B knowing that we have A (probability noted p (B | A), probability of B knowing that A, therefore calculated in the subpopulation restricted to those who are A)

total probability p (A) p (B | A)

* or the reverse, we say that we must have B, but also A knowing that B is symmetrical

probability p (B) p (A | B)

the two are equal, it is p (A and B) = N (A and B) / N, and so we have

p (A) p (B | A) = p (B) p (A | B)

and we obtain the fundamental formula called "Bayes formula"
p (B | A) = p (B) p (A | B) / p (A)

which is widely used in a whole sector of probabilities, Bayesian probabilities, which aim to answer questions like: knowing that A has a probability p1 of occurring in hypothesis B, and p2 in hypothesis not B, what is the probability that B is true if I observe A (an absolutely central question, most discussions on this forum can fit into this framework).


Let's apply here to A = to be vaccinated and B = to be infected

The probability of being infected when vaccinated , is equal to the probability of being vaccinated when you are infected , multiplied by the ratio of the odds of being infected over the odds of being vaccinated.

It is this factor that is forgotten when we confuse the two: the proportion of vaccinated among the infected, and the proportion of infected among the vaccinated.

We can write the same relation for the unvaccinated (non A)

p (B | not A) = p (B) p (not A | B) / p (not A)

by dividing one by the other, we can assess the ratio between the probability of being infected when we are vaccinated, to the probability of being infected when we are not vaccinated, which is the thing that really interests us (l vaccine efficacy)

p (B | A) / p (B | not A) = p (A | B) / p (not A | B) * p (not A) / p (A)

Who says that the ratio of the probabilities of being infected when one is vaccinated, compared to unvaccinated, is equal to the ratio of the number of vaccinated to the unvaccinated in infected , multiplied by the ratio of the proportion of unvaccinated to the proportion of vaccinated in the population.

Once again it is this ratio of the number of vaccinated to the number of unvaccinated in the population which is forgotten and which must be taken into account when looking at the number of vaccinated among the infected.

this ratio varies quite rapidly with the proportion of vaccinated. With 50% vaccinated, it is 1, so it does not change the result. With 60% of vaccinated, it is 60/40 = 1,5, and with 90% of vaccinated, it takes 90/10 = 9

the re-evaluation is all the more spectacular as one approaches 100%, it becomes "infinite" at 100% since of course there are zero unvaccinated infected. All the "spectacular" examples take well on high rates of vaccination (but if it is only 50% the factor does not play any more, and below 50%, it acts in the opposite direction)

Strangely, the consequence is that the best case for evaluating vaccine effectiveness is to look at the proportion of vaccinated among the contaminated, not when everyone is vaccinated, but when only 50% are vaccinated (because there the two populations are equal) !!!

Well it is of course the same result as Christophe but put in a simple form: to have the vaccine effectiveness, it is necessary to make the relation between the proportion of vaccinated by the unvaccinated in the sick, but correct by the ratio of the non vaccinated over those vaccinated in the total population.

NB: I calculate the ratio r of the probabilities of being infected depending on whether we are vaccinated or not, but this ratio is equal to 1 when the probabilities are equal, therefore when the vaccine efficacy is "zero". The vaccine efficacy is rather 1 - r: if r = 1, the efficacy is zero, if r = 1/10, it is 90%. If r> 1, the efficacy is negative, i.e. the probability of being infected is greater if you are vaccinated than if you are not vaccinated.)