Man compares vaccines to airbags. Then man forgets and compares unvaccinated death rate to deathrate of car accidents on cars with airbags.
Man is all over the place.
Sure thing, pizza gate
What made it a "junk study"?
If almost a third of infections result in no antibodies, that would seem to support that assertion. That is what vaccines are designed to do.
JR
Interesting. I have zero doubt you fapped to this.
Now post your picture of Q chillin' outside Air Force One.
The CDC study did not create a cohort of people to follow over time. Instead, they identified people hospitalized with Covid-like symptoms, and then they evaluated how many of them tested positive versus negative for Covid. Among the vaccinated, 5% tested positive, while it was 9% among the Covid recovered. What does this mean?
Though the authors do not mention it, they adopt a de facto case-control design. While not as strong as a cohort study, this is a well-established epidemiological design. The first study to show that smoking increases the risk of lung cancer used a case-control design. They compared hospitalized patients with lung cancer and found more smokers in that group compared to non-cancer patients, who served as controls. Note that if they had restricted the control group to people with (say) heart attacks, they would have answered a different question: whether smoking is a larger risk factor for lung cancer than it is for heart attacks. Since smoking is a risk factor for both diseases, such a risk estimate would differ from the one they found.
In the CDC study on Covid immunity, the cases are those patients hospitalized for Covid disease, having both Covid-like symptoms and a positive test. That is appropriate. The controls should cons ute a representative sample from the population from which the Covid patients came. Unfortunately, that is not the case since Covid-negative people with Covid-like symptoms, such as pneumonia, tend to be older and frailer with comorbidities. They are also more likely to be vaccinated.
Suppose we wanted to know whether the vaccine rollout successfully reached not only the old but also frail people with comorbidities. In that case, we could conduct an age-adjusted cohort study to determine if the vaccinated were more likely to be hospitalized for non-Covid respiratory problems such as pneumonia. That would be an interesting study to do.
The problem is that the CDC study answers neither the direct question of whether vaccination or Covid recovery is better at decreasing the risk of subsequent Covid disease, nor whether the vaccine rollout successfully reached the frail. Instead, it asks which of these two has the greater effect size. It answers whether vaccination or Covid recovery is more related to Covid hospitalization or if it is more related to other respiratory type hospitalizations.
Let’s look at the numbers. Of the 413 cases (i.e., Covid positive patients), 324 were vaccinated, while 89 were Covid recovered. That does not mean that the vaccinated are at higher risk since there may be more of them. To put these numbers in context, we need to know how many in the background population were vaccinated versus Covid recovered. The study does not provide or utilize those numbers, although they are available from at least some of the data partners, including HealthPartners and Kaiser Permanente. Instead, they use Covid-negative patients with Covid like symptoms as their control group, of which there were 6004 vaccinated, and 931 Covid recovered. With these numbers in hand, we can calculate an unadjusted odds ratio of 1.77 (not reported in the paper). After covariate adjustments, the odds ratio becomes 5.49 (95% CI: 2.75-10.99).
Ignoring covariates for the moment, we will look at the unadjusted numbers in more detail for illustrative purposes. The paper does not report how many vaccinated and Covid recovered people there are in the population at risk for hospitalization with Covid-like symptoms. If there were 931,000 Covid recovered and 6,004,000 vaccinated (87%), then the proportions are the same as among the controls, and the results are valid. If, instead, there were (say) 931,000 Covid recovered and 3,003,000 vaccinated (76%), then the odds ratio would be 0.89 instead of 1.77. There is no way to know the truth without those baseline population numbers unless one is willing to assume that those hospitalized for Covid-like symptoms without having Covid are representative of the background population, which they are unlikely to be.
With a background population to define a cohort, one must still adjust for age and other covariates as in the Israeli study. Some may argue that the Covid negative hospitalized patients with Covid-like symptoms are a suitable control group because they provide a more representative sample of the population at risk of Covid hospitalization. That may be partially true compared to an unadjusted analysis, but the argument is incorrect as it does not address the key issue of the relevant medical question being asked. There is both a relationship between being vaccinated/recovered and Covid hospitalization and a relationship between being vaccinated/recovered and non-Covid hospitalization. Rather than evaluate the first one, which is of intense interest for health policy, the CDC study evaluates the contrast between the two, which is not particularly interesting.
The CDC study adjusts for covariates such as age, but the procedure does not resolve this fundamental statistical issue and may even exacerbate it. Frail people are more likely to be vaccinated, while active people are more likely to have been Covid recovered, and neither of those are properly adjusted for. With the contrast analysis, there is also more confounding that must be adjusted for: both the confounding related to the exposures and Covid hospitalizations and the confounding related to the exposures and non-Covid hospitalizations. This increases the potential for biased results.
While not the main problem, there is one other curious fact about the paper. Covariate adjustments will typically change the point estimates somewhat, but it is unusual to see a change as large as the one from 1.77 to 5.49 that was observed in the CDC study. How can this be explained? It must be because some covariates are very different between the cases and controls. There are at least two of them. While 78% of the vaccinated are older than 65, 55% of the Covid recovered are younger than 65. Even more concerning is the fact that 96% of the vaccinated were hospitalized during the summer months of June to August, while 69% of the Covid recovered were hospitalized in the winter and spring months from January to May. Such unbalanced covariates are usually best adjusted for using matching as in the Israeli study.
Epidemiologists typically rely on case-control studies when data are unavailable for a whole cohort. For example, in nutritional epidemiology, researchers often compare the eating habits of patients with a disease of interest versus a sample of representative healthy controls. Following the eating habits of a cohort over long periods is too unwieldy and costly, so a questionnaire-based case control study is more efficient. For this immunity study, there is no rationale for a case-control study since cohort data are available from multiple CDC data partners. It is surprising that CDC chose this case-control design rather than the less biased cohort design selected by the Israeli authors. Such an analysis would answer the question of interest and may have given a different result more in line with the Israeli study.
Lol afraid to post the link
I already posted the entire article and link in this very thread.
It’s so obvious when you’re butthurt
Lol in this very 600 page threadI already posted the entire article and link in this very thread.
It’s so obvious when you’re butthurt
Sure it's me that's butthurt.
...
I'll take the CDC for the health information every day over twitter randos... you do do.
At the very least I would expect the study to be retracted. Has it been retracted yet?
Man forgets that car crashes are not a airborne transmissible disease.
The vaccine and airbags comparison is also spot on, they're both measures that substantially reduce death.
Yes in this very 600 page thread. 1 day ago. 2 pages back.
You really need to stop your just dropping in routine, it never works out well for you.
You’d know a thing or two about posting studies that get retracted
The study you posted came out Friday, I wouldn’t expect a retraction that soon. Although later the same day CDC released another study saying both were basically equal. Not sure how they square that.
Any counter to the flawed methodology that was pointed out in the study you posted?
i dont know how qualified any of us are to pick apart methodologies on these kinds of studies
but if you insist that we look up twitter randos to give reviews on studies before we share them to the forum, feel free to express that request
you are referring to a study that said HCQ was not effective at combatting covid. which was retracted. if we are all laypersons sharing studies that are being published, why would you hold a poster responsible for sharing a study that turns out to be flawed and ultimately retracted? do you conduct your own version of a peer review on everything you end up sharing here?You’d know a thing or two about posting studies that get retracted
The study you posted came out Friday, I wouldn’t expect a retraction that soon. Although later the same day CDC released another study saying both were basically equal. Not sure how they square that.
Any counter to the flawed methodology that was pointed out in the study you posted?
also, since then, havent there been other studies that reached the same conclusion re HCQ?
Sure, and unlike you, I've actually owned it that one time.You’d know a thing or two about posting studies that get retracted
Do let us know. I simply shared the study because it was indeed a topic of conversation here, haven't even looked at it myself. There's nothing for me to defend there either.
I stopped wasting my time with purported "expert opinions" from randos on the internet a long time ago. This case isn't any different.
If the study is indeed flawed, it'll be retracted in due time and that is that.
I don't even remember what was the study for. But it doesn't matter. I said I was apologize to Darrin if it was retracted and I did. Not sure what's the shame in that, tbh
i think its pretty dumb to demand apologies from posters who shared published studies that end up later being retracted. none of us here are experts who are qualified to conduct our own reviews of these papers to figure out for ourselves that the paper is ripe for retraction
if somebody shared a study that already has been retracted, and is pushing it as current/valid, that's a different issue. or if they're pushing some random twitter rando's opinion that isn't founded in an actua lpeer reviewed study, that's different.
Lol I'm not digging thru this thread to find your . It's you that's here trying to convince people you're right and you're doing a horrible job at it.
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