"fully vaccinated individuals with breakthrough infections have peak viral load similar to unvaccinated cases and can efficiently transmit infection in household settings, including to fully vaccinated contacts." [1]
This study is for household transmission in an extended setting. That's not the same as transmission e.g. in an outdoor environment or for short, casual contact.
Vaccinated people are less likely to be infected, hence "breakthrough case." Your quote is like saying that "people thrown out of windows in car crashes have the same rate of injury, despite whether the person was wearing a seatbelt or not." That may be true, but wearing a seatbelt definitely reduces the chance of getting thrown out of a window.
Only if you are looking to reinforce your beliefs. Otherwise, besides the above two strategies, you should look at which study has better methodology (though it's usually never trivial, especially not for us, bystanders), bigger sample size, stronger statistical power.
If none of these seem to suggest a clear winner then you should just think that this is still undecided. You can also ask an expert. Choosing one and believing is basically just going with your suspicion.
And, If there is uncertainty (and there always is some small amount of it) then this does not support the parent commenter's strong and confident assertion that "do not, and never have" ... produced an effect.
> in the real world, we had our biggest outbreak after vaccines were mainstream
Is that supposed to be relevant? When "we had our biggest outbreak" there were/are still sufficient unvaccinated people to transmit an outbreak.
You're clearly defending a fixed point of view here. If you want detailed responses to learn from, stop asking for people to do them yet again and look for what already exists upthread. If you're having trouble finding it, start here: https://news.ycombinator.com/item?id=29124446
Surprise: get vaccinated. And now you'll say that "but you can get it even if you are vaccinated". Which is true, but of course less likely. How much less likely is known from the experiments.
As far as I’m aware, the experiments covered symptomatic cases but didn’t look at a reduction in “getting it”.
Based on this study, vaccinated had a 25% chance vs 38% for unvaccinated to become infected if someone in their household had Covid. So a helpful reduction, but not night and day.
Once infected, from what I’ve read vaccinated folks are just as likely to spread it.
Just because you don't line an answer to a question you posted it doesn't mean that's not the right answer. But it does imply, I guess, that you'll keep posting this same question and robbing others' time.
We've banned this account because it has been using HN primarily for ideological battle. That's not allowed here, regardless of what you're battling for or against.
Please don't create accounts to break HN's guidelines with.
That is observational data confounded by reporting and inadequate testing.
Go look at Singapore. 80%+ vaccination rate (Pfizer or Moderna), with regular mass testing.
About 65% of new cases are in fully vaccinated but the new cases are still stacking up. So yes it reduces the risk, but not by 7x. This is backed up by the recent Lancet paper which showed about a ~30% decrease in risk of infection.
They provide daily updates but have been changing the detail level and categorization to get away from pure case numbers.
Go back to late August to see the breakdown of cases across fully, partially and unvaccinated individuals. The vaccines clearly work prevent serious illness, but don’t seem to be slowing the spread that much.
The MOH used to also breakdown daily deaths into vaccinated and unvaccinated, but recently stopped. I suspect (and they confirmed a few cases) where the deaths are often fully vaccinated.
Of course they don’t want to provide data for the vaccine hesitant to call out, but they have been changing their narrative so often it’s starting to be a problem.
Interesting. Last detailed report is from Sept 07. Vax rate ~90%, 2-3k new cases, ~90% in vaxed population. The vaccine seemingly had no effect on infections?! Nothing like 6.8x likelihood.
So on one hand we have detailed data from UK and Singapore with breakdown by age/date/vax status and limited VE agains infection, on the other hand opaque charts (US...) with only aggregate numbers, showing 6-10x odds in favor of vax. The lack of detailed epi USA data conspicuously continues.
I did sanity check one UK aggregate chart touted in a sibling thread claiming, absolute numbers, unvax infections >> vax infections in UK. There were egregious Simpson's issues, all age groups >18yo had (significantly) more vax infections than unvax infections. The <18yo case load was a huge outlier, dominating the aggregate numbers. Fireable offense for a data analyst.
I’ve seen some really sloppy analyses. There was one in Canada that was similar to the US. It entirely ignored factors like vaccinated people never testing positive because they are asymptomatic.
The Singapore one isn’t perfect since those at higher risk of exposure (medical workers) tend to be vaccinated so that isn’t corrected for. But that would also disappear as you start to get most of the population vaccinated.
The linked video, https://www.youtube.com/watch?v=Hc7A1bVuSJU&t=56s, is misleading. It shows that the number of unvax cases is much larger than vax cases. I hope that by know it is common knowledge that the pandemic behaves very differently between age groups. Simpson's paradox abounds. The video only breaks down vax/unvax for aggregate numbers. This is a smell.
1. In every age group, except under 18, the number of vax cases is larger than the number of unvax cases, contradicting the video on its face.
2. Under 18 has a large case number, which dominates the totals. Some issues:
2.1. Schools have strict testing and tracing policies. The large case numbers may simply an effect of higher testing rates for the respective population.
2.2. Related to 2.1., there are two ways to count cases: PCR cases and symptomatic cases. In case of large case numbers outliers, the difference between the two measures can explain a large difference, though it is impossible to independently verify that a consistent measure was applied for all age groups.
2.3. Vaccination in 12-17 was only recently introduced. VE decreases over time. Studies disagrees by how much. At six months time, for Pfizer I've seen 55%-75%, from a high of 90%. Closer to the vaccination event VE is higher, thus the number of vax cases is temporarily lower. A more realistic assessment assessment ought to a. break down under 18 in to 0-5, 5-11, 12-17, and wait 6 months post vaccination campaign. Note that VE is also a somewhat misleading metric, 90% means 9/10 case reduction, 50% merely 1/2; a small percentage drop in VE at the high values mean a large increase in cases.
3. In some age categories, e.g. 50-59, unvax share of the cases is as small as 6%. Not sure (*) what the unvax rate in UK is for that age group, the reports says somewhere in the low teens, that number has been contested. But 6% is low enough by itself. If that doesn't make you wonder about the official line "unvaccinated people were 6.8 times more likely to get COVID-19 than fully vaccinated people.", then nothing will ever do.
Can't speak about US data because US is, for some reason, very tight lipped when it comes to publishing basic epi data with breakdown by date, age and vax status. If you have a link to the equivalent of the UK PHE vaccine surveillance report for any US state, please share.
(*) Apparently UK is not sure about the vax rates either, because apparently UK doesn't know how many people of a given age live in the country. That is a story for another time.
Thanks for linking to that report, it's interesting reading, particularly the part with "We present data on COVID-19 cases, hospitalisations and deaths by vaccination status. These
raw data should not be used to estimate vaccine effectiveness" (that sentence occurs twice so tat you don't miss it)
You should not expect ZOE study data to match UK Govt data exactly, they use different methods and check different symptoms. This is that theme that Prof. Spector talks about often.
"should not be used to estimate vaccine effectiveness"
Exactly. Neither should aggregate numbers that various US states and Prof. Spector use to spread fear, acrimony and stigma should be used to estimate VE, or mislead the audiences to estimate VE by themselves. Notice how the ZOE video you linked lacks the intellectual honesty to display the same disclaimer. His own website says "Incidence estimates were updated on 21 July 2021.". He's basically fabricating numbers, for all we know just as accurate as Prof. Ferguson. This is no better than the "antivax garbage" some people are so keen on summarily calling out.
Here are some longish term studies and preprints for Pfizer's VE against infection.
* VE against infection drops over time. Sadly, I am not aware of any reliable literature for VE after 9 or 12 months. Unfortunately Pfizer killed their own critical trials, which had a solid headstart, by vaccinating the control arm after 6 months. But the trend is clear, and worrisome.
* 80% VE => 1:5 infection odds. 75% VE => 1:4 infection odds. 50% VE => 1:2 infection odds. 12% VE, it's a wash. Numbers like 1:6.8 infection odds this long after the vaccination campaign are fantasy.
> Prof. Spector use to spread fear, acrimony and stigma should be used to estimate VE, or mislead the audiences ... lacks the intellectual honesty
This is a very bold partisan claim, in fact it is insult. It comes across as another Paranoid fantasy out of US politics, irrelevant to the UK. I'm no longer interested in anything that you have to say. Good day.
This ZOE business is something else. Their website is 75% building up their credentials, 25% promoting their app and 0% substance, e.g. what the actual formulas are or a link to code and data dumps. Or at least a research publication with some details. Perhaps there is a link hidden somewhere, but neither their Home, About or FAQ point to it.
They literally changed their formula because the trends in the unvaccinated population didn't to conform to their prior biases. Though the formula details are still a mystery.
"Last week, we reported a plateau in new COVID cases based on our methods at the time, which relied on a small number of unvaccinated people in our dataset compared with the wider UK population. The number of daily new cases in the unvaccinated group appeared to be dropping which in turn resulted in our overall numbers trending down. This meant the figures were accurate to our dataset but didn’t represent the full picture in the UK."
That's simply not correct.