The sample size is this non peer reviewed study is 79 vaccinated people (corrected, misread as 83 before) and completely lacks the statistical power to differentiate between vaccinated and unvaccinanted people.
Also as in the Provincetown study it's a convenience sample, meaning people who chose to be tested, and not a random sample of all infections. That likely biases the sample toward more severe infections since people with more severe symptoms are more likely to seek out testing.
Another big statistical issue in these studies (at least the Wisconsin one) is that they have truncated samples. People with high Ct values (higher Ct = harder to find virus) are eliminated from the comparison because it's not clear they can be considered "infected".
If one way that breakthrough infections manifest themselves is thru very low amounts of virus in some people, but then you eliminate people with very low viral loads from your comparison, you're sort of begging the question. Need to be careful in cases like these.
Here is a study from the UK with a MUCH larger sample size (~50K vaccinated people) that indeed finds vaccinated people carry lower viral loads.
The study also avoids some of the selection bias issues discussed since it relies on a random sample, not just a convenience sample of those who happened to get tested because they had symptoms.
It is much more rigorous than e.g. the Wisconsin or Provincetown Bear Weak studies.
To throw a gauntlet down, a pretty simple test of whether news outlets like @nytimes actually care about getting the science right is if they report on this more rigorous UK study with >= fervor to the Provincetown study.
Seen discussion of the sample size in the UK study and it's worth pointing out that (although the overall sample size is very large) the number of *positives* is ~similar to the other studies. Note, however, that they do find a statistically significant result (p-value = 0.01).
And, again, this reflects a random sample of the entire UK population, which is >> more robust than a self-selected sample. The UK has done great work with large random samples like these; see also their work on Long COVID below, for instance.
It's definitely one of the more fortuitous accidents of timing I've had as a writer. On Tuesday, I wrote a piece saying Democrats use "But Her Emails" to deflect legitimate criticism. And that's exactly what they've done since the special council report on Thursday...
Biden's age is not at all comparable to Hillary's emails. It is a much more important issue. He wants to be president until he is 86 years old! Voters ratioanally think it's important. I criticized #ButHerEmails early and often. This story is not the same. natesilver.net/p/not-everythi…
Although there was a fresh round this week, people have been using this ButHerEmails excuse to deflect legitimate reporting on Biden's age for months. It hasn't worked. Voters have more concerns than ever. Now he's trailing Trump *even as economic perceptions improve*. Not good.
I'M SORRY BUT YOU DID A MISINFORMATION SANDER! YOU'RE ONE OF THE BADDIES! You've routinely spread misinformation about the scientific consensus on COVID origins. The fact that you can't acknowledge this why the concept is incoherent.
Half the reason the Team Misinformation people bug me is because it's just so obvious what they're doing, taking genuinely contentious discussions and stigmatizing the positions that don't match their politics with the thinnest imaginable reeds of expert authority.
A lot of it, like denial of the *possibility* of a lab leak, is quite close to propaganda as commonly defined. It's trying to advance an agenda, it presents facts in a manipulative way, and it seeks to trigger an emotional response (by saying e.g. the lab leak is xenophobic).
🧵1/ Our biennial forecast self-review is out! There’s lots of detail in the story, please check it out. We think it’s really important to do this. It’s also one of those years where it may clear up some misconceptions. fivethirtyeight.com/features/how-o…
2/ Polls (in the aggregate) and forecasts had a good year. Polling averages did ~not~ predict a red wave. They showed a highly competitive race for the Senate and below-average (by historical standards) GOP gains in the House, though with much uncertainty.
3/ Democrats did slightly better than expected based on polls/forecasts, but really only slightly, much less than the degree to which the GOP overperformed polls in 2016 & 2020. It was a somewhat surprising year relative to historical norms, but not relative to polls.
This is cool. GOP currently leads 220-215 based on called races + races where they're currently ahead. But, quite a few are uncertain; some key ones below.
Republicans have a 59% chance of winning the Senate, according to our final Deluxe forecast. It's closer in our alternative models: R chances are 51% in the Lite (polls-only) forecast, and also 51% in Classic (polls + fundamentals but no expert ratings). projects.fivethirtyeight.com/2022-election-…
In the House, Republicans are considerably more definitive favorites: 84% in Deluxe, 82% in Classic and 75% in Lite. Still, you shouldn't round their chances up to 100%. It wouldn't require **that** large of a polling/forecaster error for the House to be competitive.
Some qualifications on this, and more in some races than others, but our Deluxe model expects Republicans to outperform their current polling by ~2 points or so in the average Congressional race.
Here is the comparison in the Senate, for instance.
There's not any one simple reason for the gap, it's a few different things that add up. Also not mentioned in the story: Dems will likely perform worse in the *House popular vote* than on the generic ballot because there are a bunch of districts where there's no D on the ballot.