I tried to read this with an open mind but there’s some pretty big flaws in the analysis. To note some that stood out:
The author looks at the percentage change in daily cases in the US vs latitude and finds a mildly strong correlation (R^2 = 0.25). Critically though this ignores that US southern states already have high daily case levels, so any increase is going to look smaller as a percentage.
You can see this flaw clearly in the State Trends table the author presents. Most of the states seeing large percentage increases have daily case levels per 100,000 people that are well _below_ the US average. The only two states in that table above the US average are Idaho and West Virginia, and low-and-behold they have very low vaccination rates.
The author’s analysis of % change in daily cases vs vaccination rates suffers from the same flaw, and has an even weaker correlation (R^2 = 0.021 for hospitalisation % change and 0.084 for case numbers % change). Of course you’re going to see these trends when southern states with low vaccination rates are already in large outbreaks. The fact that correlation is so weak despite this flaw to me seems like evidence that vaccination does in fact work.
To me the common sense approach here would be took at daily cases/hospitalisations/deaths vs vaccination status within the same geographic area to control for covariates such as potential seasonality and other measures to control spread.
Now to be fair to the author he does in fact attempt to do this in a separate post, and does indeed in his own analysis find that vaccines are effective at preventing death/hospitalisation. Contrary to other analyses though he find that vaccines correlate with higher infection rates. I’d argue though this result is because the authors analysis is again flawed. In particular he uses population level case numbers without any attempt to control for the prior probability of taking a test, or the error rates on the tests.
Overall I’m much more inclined to trust peer reviewed studies that find that vaccines are partially effective in preventing transmission. I also think the large outbreaks in SEA and the southern US suggest that seasonality doesn’t effect delta transmission as much.
Something doesn't add up. Vaccine makers say it also prevents against asymptomatic infection, e.g. biontech[1] delta variant asymtpomatic infection lists "79% (75–82%)" (presumably it's the 95% confidence interval or something similar in parentheses -- in any case, it's substantial). I remember the happy news when the studies came out, saying we were also preventing transmission to unvaccinated people (initially for Alpha with 92% (90–93%), that's the number that stuck in my head to be honest).
How can this part of the article be true then?
> the covid vaccines are extremely leaky and may well accelerate contracting and carrying covid.
(Where 'leaky' is a link to another article on substack where it is explained as meaning 'not preventing being contagious'. Continuing the quote:)
> they allow for very high viral loads to go unnoticed and generate a new and severe asymptomatic spread vector to where none existed before. [...]
> vaccine campaigns cause superspread events because vaccination leads to a 2 week window of 40-100% more covid risk
It might transmit via a vaccinated person in some of the cases, but way fewer than if you're unvaccinated, so vaccinations should still be helpful? Or does the math on 79% (assuming that's the true value) + Delta-levels of contagiousness + number of cases still around + % of people unvaccinated work out to a worse scenario than <10% vaccinated + people that get sick take notice and stay home?
The thing about vaccination is that it's given people license to go back to offices.
Maybe vaccines work pretty well, but the combination of cramming people into offices again (and elevators, and conference rooms) plus delta, is or will be, fueling a new and worse wave as things are worse on net.
I feel antagonized by the contradiction between "we have to be in the office because reasons" and "we have to wear masks, because it's life and death if we don't".
I'm fine with wearing masks in public, and I'm fine with being in the office, but I'm not ok with the contradiction implied by insisting on both.
I'm not searching really hard at the moment, but if I find a completely remote job, I may take it.
> vaccine campaigns cause superspread events because vaccination leads to a 2 week window of 40-100% more covid risk
This is referencing the period immediately after the first shot where there is general immune system suppression as the body reacts to the vaccine, making net "efficacy" negative. Ideally, vaccine recipients would isolate for 2 weeks after the vaccine to reduce exposure to pathogens, avoid physical exertion and rest so the body can recover quickly. Any infections during this period would be categorized as "unvaccinated" and the CDC maintains this categorization until 2 weeks after the final shot, by which time vaccine efficacy turns positive.
A "leaky" vaccine is one that is non-sterilizing, which applies to all existing Covid vaccines. They were designed to prevent serious illness, not infection or transmission. Since people remain confused about this topic, the CDC changed the definition of vaccine on their website in Sept 2021, defining it as providing "protection" rather than "immunity" (which is only available to Covid survivors).
The Moderna vaccine is 98% effective in preventing severe disease but only 63% effective in preventing infections. Those vaccinated but infected people can still spread the virus, although they're probably contagious for a shorter period on average than unvaccinated people. Note that data was largely gathered before the Delta variant became prevalent so the current numbers could be a little worse.
Preliminary data from Project Salus indicates that mRNA vaccine effectiveness against infection quickly drops to 41% among elderly patients. Hence the recommendation to administer a third booster to them.
This was expected, it behaved like a bad flu. Virus have temporal and geographic patterns, they do not roll out all at one everywhere. The expectation by experts is 3 years until some semblance or normality. We still have more than a year to go, assuming people can become comfortable when they realize it is endemic
Another possibility is that we're seeing phantom patterns in the data which are really just noise. Maybe the differences between countries and seasons are mostly random? That's basically the null hypothesis and I haven't seen anyone convincingly disprove it.
The author looks at the percentage change in daily cases in the US vs latitude and finds a mildly strong correlation (R^2 = 0.25). Critically though this ignores that US southern states already have high daily case levels, so any increase is going to look smaller as a percentage.
You can see this flaw clearly in the State Trends table the author presents. Most of the states seeing large percentage increases have daily case levels per 100,000 people that are well _below_ the US average. The only two states in that table above the US average are Idaho and West Virginia, and low-and-behold they have very low vaccination rates.
The author’s analysis of % change in daily cases vs vaccination rates suffers from the same flaw, and has an even weaker correlation (R^2 = 0.021 for hospitalisation % change and 0.084 for case numbers % change). Of course you’re going to see these trends when southern states with low vaccination rates are already in large outbreaks. The fact that correlation is so weak despite this flaw to me seems like evidence that vaccination does in fact work.
To me the common sense approach here would be took at daily cases/hospitalisations/deaths vs vaccination status within the same geographic area to control for covariates such as potential seasonality and other measures to control spread.
Now to be fair to the author he does in fact attempt to do this in a separate post, and does indeed in his own analysis find that vaccines are effective at preventing death/hospitalisation. Contrary to other analyses though he find that vaccines correlate with higher infection rates. I’d argue though this result is because the authors analysis is again flawed. In particular he uses population level case numbers without any attempt to control for the prior probability of taking a test, or the error rates on the tests.
Overall I’m much more inclined to trust peer reviewed studies that find that vaccines are partially effective in preventing transmission. I also think the large outbreaks in SEA and the southern US suggest that seasonality doesn’t effect delta transmission as much.