The thrust of the article is that vaccines work well at preventing infection, but that if you do get infected, it is _possible_ that you might die at a higher rate. _Possible_ comes from a big spread in the standard deviation of P(death|infected & vaccinated). I didn't check his calculations, I took his numbers at face value and just looked at the charts.

The author uses big standard errors to make claims about what could or could not be true, because the standard errors straddle both favorable and unfavorable statistics for the vaccine.

However when the standard errors are too small for this dubious reasoning, they come out in favor of the vaccine.

The author appears to me to be using motivating reasoning to push an agenda.

Edit: sorry I am not completely right, because I wrote this comment before thoroughly reading the whole article. Sometimes his standard errors come out against the vaccine, and for all I know his math could be right. But I don't want to check the math because I have limited time and I don't care if my death rate goes up given conditions {x, y, z.}

I care if getting the vaccine makes me less likely to get sick and die, which it does, because if you look at all the tables and charts that's exactly what it shows.

Pd1 = Prob(death GIVEN infected AND vaccinated)

vs

Pd2 = Prob(death GIVEN infected AND NOT vaccinated)

Which makes it easy to lose site of:

Pi1 = Prob(infected GIVEN vaccinated)

which is very very small compared to its opposite:

Pi2 = Prob(infected GIVEN NOT vaccinated)

Because Pi1 is so much smaller than Pi2 there are several consequences for Pd1 and Pd2:

- The small counts for "numerator" of Pd1 (zero in some cases) means large uncertainty in the ratio and that the centroid of the distribution is not particularly meaningful. Statistical fluctuations (just one more or one less death) will change Pd1 substantially.

- Statistically significant deviations between Pd1 and Pd2 do not point to a cause.

For example, it could be that those contributing to Pd1 all got a much higher viral load in order for the virus to break through the vaccine's defenses and high viral loads are known to correlate with death so once vax protection is defeated it is game over. The distribution of viral load exposure may even be the same in the Pd2 case, but for the unvaccinated a lesser load can be fatal. This explanation is consistent with P1d possibly being greater than P2d AND consistent with the given anecdotes of vaccinated tweeters saying covid is just the flu, bro.

The main take away is still: you do NOT want to get this shit and vaccine AND masking will help achieve that goal. And, unless you are a sociopath, you do NOT want to give this shit and vaccine AND masking will help achieve that goal.

It makes tons of sense that those who are vaccinated and get infected are more likely to die, simply because it would indicate a failure to develop antibodies and mount an effective immune response to the virus.

That being said I’m not sure such a rant is justified over a tweet like this. Dr. Frieden is more or less correct if you slightly re-word his sentence to: “Getting vaccinated decreases the chance of dying by approximately 100x”.

What I take home from this is that everyone is human, can make simple mistakes, and that we take things written on Twitter far too seriously. I’m sure that Dr. Frieden would not have made such a mistake if he wrote an article that was published somewhere reputable instead of a tweet that could have been sent while waiting for his coffee at Starbucks, or using the toilet.

There is a trade off in communicating science to the public in that using social media, TV, and newspapers reaches more people but almost always distorts the message. I’m not sure how exactly to balance this trade off, but I also think that some amount of responsibility lies with the reader to seek the truth instead of demanding that every sentence they read on the internet be as accurate as a peer reviewed journal.

This kind of mistake is understandable, but doesn't really inspire much confidence in a screed about the mistakes others are making in analyzing COVID-19 data.

Okay… but how much less likely are you to get “infected”?

How are you even defining “infected”, here? If virus gets in your body and then your immune system kills it before it does much damage, were you “infected”? If the answer is no, you've got pretty serious selection bias, because you're completely ignoring everyone who was completely protected by the vaccine in the “vaccinated” group, but paying attention to everyone who didn't really need a vaccine in the “unvaccinated” group: basically ignoring all the really-healthy, great-immune-systems, unlikely-to-die people in the “vaccinated” group so, proportionally, the sicker people take up more room. So you can't even say that the vaccine makes things worse for them! If it improves their chances by 100 times, as Dr. Tom said, but the selection bias is only paying attention to the 0.2% least immune people (those who got infected when exposed after vaccination), you'd expect to see a 5× higher death rate even though the actual death rate is 0.99× lower. (Made-up numbers.)

Okay. But immediately after…

> In fact, if there had been 24 deaths in the vaccinated group the efficacy reported would have been 3%! Because it was looking at rates over time, 24 deaths would have been the death rate over time similar to 36 in the unvaccinated group. But clearly, among those infected, 36 in 84611 is a far lower death rate than 24 in 1066!

If? Now we’re onto hypotheticals. Here is an idea, you have so few because they were vaccinated!

Also the mental gymnastics of saying: “it’s better to not be vaccinated in case you get covid because you are less likely to die” is worthy of a mental gymnastics olympics gold medal.

I understand that the CDC guy may have worded things differently but directionally he is right.

But, again, one cannot just ignore the hypotheticals of Dr. Gator when it provides validation for your anti-vaxx stupid attitude.

Also if the vaccine prevents contraction then it should be counted as preventing death/hospitalization, but obviously those numbers aren’t obvious. Seems to me the vaccine IS preventing contraction so you would need to account for that wouldn’t you?

The vaccine works by priming the immune system to work quickly against a disease. It is quite likely that if someone develops symptoms despite their body being at peak alert for coronavirus then they are in trouble. The graphs bear that out, and do not alarm me. If we only select for cases where the person is physically susceptible enough for the virus to break through the vaccine protections to cause an infection it makes sense that the cases will be on average worse.

But there is an interesting point here that if the vaccine were killing people (eg, heart inflammation problems have been detected in some cases) then the "COVID-19-related-death" stats, etc, would be highly misleading. It would be more interesting to see all-cause mortality and the cited tables don't do that.

Why do professionals get in the business of exaggeration when it serves no useful purpose than to provide excuses and doubt to the hesitant.

Also. Often when officials state things with exaggerated and unwarranted certainty, take it with a grain of salt.

PS why isn’t Twitter marking such as misinformation? My guess, it fits their narrative, so it gets a pass.

We should be as accurate as possible with when talking about vaccine but throwing around statics(or should we say "Vaccine Statistics") like:

> "the death rate among the vaccinated, if infected with COVID, can be 3 to 5.7 times higher than the death rate of the unvaccinated."

is not exactly providing the big picture context needed for a productive social discussion.

The article suggests focusing "real efficacy". Before the vaccine program started there were ~4000 deaths per day in the US, now there are ~100. Clearly it is very effective at reducing death.

But in this case, what people really want and need to know is how well the vaccine is going to prevent them from dying.

They don't care about the difference between "Prevent dying from covid" and "prevent dying from covid once you have covid". The latter simply doesn't matter to them until they have covid, and then it's too late for the vaccine. That statistic is meaningless to the general public.

People only want to know if the vaccine can help them not die. And it absolutely can because it helps prevent getting infected in the first place.

Edit: I just realized the statistic that people want: "How likely are you to die from Covid if exposed to it, vaxed vs unvaxed." Not if you get it. Just if you're exposed to it. And since we don't run tries where we deliberately expose people to viruses, it's going to be a hard number to get.

According to most major studies coming out (including this one: https://www.imperial.ac.uk/news/227713/coronavirus-infection...), with the advent of delta variant, the vaccinated have about a 50% less chance of getting infected than unvaccinated people.

If we assume the vaccine offers no additional protection against hospitalization/death given that one is already infected (which is what the author seems to be arguing), then what we should be seeing is 67% of hospitalized COVID patients are unvaccinated, yet we're seeing the rate closer to 97%. So there's obviously something going on here, and the most likely culprit would be that the vaccine does offer protection against hospitalization/death, contrary to the author's argument.

It also fails to consider the false positive and false negative rates inherent in these studies. In particular, lots of asymptomatic cases in the vaccinated arm are not caught by efficacy studies (false negatives). So claiming that low death rates are solely a result of reduced infection(as opposed to fighting off infections better) is also a conclusion made hastily.

Death rates and symptomatic cases are much measured much more accurately, and claiming that effectiveness studies have little point once there's vaccine efficacy is available underestimates the challenges of epidemiology.

But the overall point that statistics are hard to understand, easily misused in online arguments is a valid point.

There is not a single comment pointing out any error or misinformation or lie or damned lie.

Unless somebody can show that the data and/or interpretation are wrong, it should not be flagged.

And since the main purpose of religion is dividing people on Us vs Them (Us - clean and moral, Them - stained and evil) this is exactly what is happening with pandemic. Plus some overzealous virtue signaling.

Rational arguments and rational people are doomed to fail in the circumstances.

It's a given that you do not want to contract COVID-19. Vaccination and wearing a mask will help.

You also do not want to give COVID-19 to others. Again, vaccination and wearing a mask will help.

So this article is just pedantry over a statistical quirk.

Obviously most of the people the author is criticizing are using "exposure that would cause detectable disease in non-immune individuals" as their definition, and I don't know if we have a better word for that.

Leaky vaccines can also cause mutation pressure on viruses, but the only acceptable public position is that the unvaccinated are causing the more virulent strains.

Propaganda from the top down to sell more (in patent) pharmaceutical products, with force and public shame. Think about this for a moment: someone at WHO identified their herd immunity definition on their website and willingly modified it to exclude natural immunity. Ask yourself how that is in any way scientific or appropriate. It is scientific gaslighting and the only explanation is a desire to sell more vaccines.

Changing the way you categorise death can do wonders..

> Q Can you talk about your concerns about deaths being misreported by coronavirus because of either testing or standards for how they’re characterized?

> DR. BIRX: So, I think, in this country, we’ve taken a very liberal approach to mortality, and I think the reporting here has been pretty straightforward over the last five to six weeks. Prior to that, when there wasn’t testing in January and February, that’s a very different situation and unknown. There are other countries that if you had a pre-existing condition and let’s say the virus caused you to go to the ICU and then have a heart or kidney problem — some countries are recording that as a heart issue or a kidney issue and not a COVID-19 death. Right now, we’re still recording it, and we’ll — I mean, the great thing about having forms that come in and a form that has the ability to mark it as COVID-19 infection — the intent is, right now, that those — if someone dies with COVID-19, we are counting that as a COVID-19 death.

Now, imagine if, after vaccine rollout, we counts those deaths as cause by a heart condition. Boom. Drop in covid deaths! Vaccines worked! Hail pharma!

The evidence that vaccination reduces the severity or decreases mortality of COVID-19 infection is not as strong as the evidence that vaccination prevents COVID-19 infection entirely.

Where are the "damn lies"? We're talking about splitting hairs in the interpretation of twitter posts that evidence does support. It's interesting, but exactly this kind of inflammatory language is what I will always flag on HN, whether it be about COVID or VIM vs. EMACs.

The article was posted 1 hr ago. Assuming some time to notice the article, then something like 30 minutes to read it and write a response, you'd not expect to see many comments pointing out the problems in the first hour.

Thanks for vouching for it.