Can someone recommend a new irony meter? Mine just exploded.
I ordered one from Amazon six months ago and it’s stuck on a shipping container off the coast of Long Beach. Sorry I can’t help.
There’s this (NOTE: Video autoplays at link):
Full Title: The death rates from Covid in red America and blue America are growing further apart
Spoiler: It’s worse in red areas.
This has a collection of stories like the one above:
Meanwhile, some rightists are getting closer to actually killing people on the left…
Here’s what’s confusing to me: according to this map from NPR, community transmission (i.e. how many new people are being diagnosed with Covid) is much lower in many parts of the south than in most of the rest of the country (note, the headline is about mask wearing, but the statistics behind the map are about transmission). I don’t understand how that works.
It seems to be the indoor season vs. outdoor season. Summer is indoor season down south and they had a rough summer. As it gets colder up north, we’re starting to see more cases.
WAG:
I think the other article is noting that most people dying from covid are unvaccinated and conservatives are more likely to be unvaccinated. So, even if transmission is lower death rates are higher.
Also, while those southern states are red they still have sizable blue populations (and vice versa).
Mentally ill, violent individuals, being radicalized and used as tools of destruction by right wing politicians who are seeking power. Nice.
Understood, I think. My question is, why would transmission rates be lower in an area where vaccinations are lower? Why would their blue cities have a lower transmission rate than California’s blue cities (as an example, because that’s where I am)?
This is from CNN, here, about these CDC statistics on the map:
A county’s level of transmission is based on just two metrics: new Covid-19 cases per 100,000 people and the positivity rate, both measured over the last seven days.
So that’s new cases per 100,000, and percentage of positive cases in the population. If one is rated higher than the other, then the higher rating is used in the map. These results still don’t make sense to me. As for the indoor/outdoor thing, northern and western states have been either “substantial” or “high” for months on this map. California is outdoor most of the year. I really don’t see that as a factor.
Its possible that the delta variant already burned through the unvaccinated population in the South, so they have more quickly achieved overall herd immunity (at the cost of tens of thousands of deaths), than those that flattened the curve.
They test more in California and other high-vax areas. Which means more asymptomatic and low-symptom cases are discovered. Just a guess, but I think it very likely.
That may be partially the answer, although they do to some extent correct for it by also looking at the % positive test rate. So that if a county was, for example, only testing people actively dying of respiratory disease it may report few Covid cases, but its % positive test rate would be through the roof.
‘Hey, I’m just throwing lit matches around, nothing wrong with that! It’s not my fault someone left all these open containers of gasoline lying around!’
I thought the positivity rate was the rate of (tested) positives for the entire population, not the rate of positives only among those tested. If your version is correct, that would make a big difference.
If positivity rate were the rate of positive tests compared to the entire population, that number would always be higher than the number of new cases per 100,000, right? Isn’t every new case a positive test?
Does the positive test rate include repeats? If a professional athlete tests positive, they get quarantined (can’t play, practice, or even come to the building) and tested every morning until they test negative some number of days in a row.
Aaron Rodgers (starting quarterback for the Green Bay Packers) has been having positive tests for probably the last 5 or 6 days in a row. Do all five or six of those positive tests count against the positivity rate in Wisconsin? Or are they just counted as one positive because it’s the same person suffering the same episode?
If repeats count, then diligent testing of asymptomatic positives until they test negative seems like it would inflate the number. And that seems more like the kind of behavior you’d expect to find in highly vaxxed blue areas than anti-vax red.
The level categories (high, substantial, moderate, low) use different values for new cases vs. positivity rate. For example, “moderate” is 10 to 50 new cases per 100,000 people (which is 0.1% to 0.5%) or a positivity rate between 5% and 8%. Of these two values, if one is in a higher category than the other, then the county goes into the higher category. This is in the cited article.
I hope, because it would make sense to me, that re-testing the same person and getting another positive reading for the same instance of the disease, would not affect the statistics at all.
On the other hand, if someone had a positive test again after testing negative for a while, I suspect that would count as a new case for new cases, but not for positivity rate (because the previous positive reading would have already counted and one person shouldn’t be counted more than once). This was not covered in the article as far as I read. I expect this situation is more rare than breakout cases where the person had been vaccinated.
It’s actually .01% to .05%. That’s what I get for doing it in my head.
I wonder how much having big universities in a state contributes to the testing rate. The university I work for is only medium-sized and it alone is testing more than 1% of the state’s population twice a month because vaccinated students/staff/faculty still have to test every two weeks.