Ok--I said that I'd provide some more information on the issue of how I (and others) have reported testing numbers wrong in several states.
This is actually a pretty big deal, and could affect policy decisions with a cursory look at the wrong positive testing percentage.
1/x
People looking at the national snapshot often use @COVID19Tracking's data. I do. Their site provides easy-to-access data.
And they have updated testing data for several states in a new column on their spreadsheet, but many of us continued to use the "legacy" column.
2/x
For 24 states, using that column provides a *very* skewed version of daily testing numbers (some states more skewed than others), creating erroneously high *current* positive testing percentages.
3/x
First, here are the 24 states:
CO, DE, FL, HI, IA, IN, KS, LA, MA, MD, MN, MO, ND, NE, NH, NV, OR, PA, RI, SD, UT, VT, WI & WY.
Many high % states here, but also some low % states that would be even lower (e.g., MA, NH, VT)
4/x
Here's the issue: this data creates a tabulation of daily tests excluding every person who has ever tested previously. At any time. Not the same day--ever.
That's a big problem. Why? You have an ever-shrinking pool of people who "count" as a test as more people get tested.
5/x
I'll use an example: North Dakota.
My data as of Friday showed ND with a 7-day average percent testing positive of 28.12%. Holy hell, that's high, right?
Take a look at the snapshot of their testing. We have:
5661 tests processed (5444 suitable encounters)
1548 first time testers
343 positive cases
144 of those are from repeat testers
199 of from first time testers (343 - 144)
7/x
Most of us who use @COVID19Tracking's data reference the day-over-day change in positive and negative cases, and use the combination thereof to get total tests.
Over time, those numbers have become poor for current test counts in the 24 states that stop counting a person's test after their first one. These states essentially are just tracking how many of their citizens have ever gotten a test.
Back to North Dakota for why...
9/x
Using those two columns, North Dakota would show 343 new cases (the *total* amount of new cases), but only 1548 tests (the amount of *first time ever* testers).
So ND's % for today is 6.30% (343/5444), but I (and others) would report that as 22.16% (343/1548)
10/x
That's a massive difference, but in a pretty small state, so it's fairly hidden nationally. Over 30% of the state has been tested once though, and will never be counted again!
Also, this isn't on @COVID19Tracking--it's on some pretty poor data presentation by the states.
11/x
Fortunately, @COVID19Tracking added a column that fixes this issue for 16 of the 24 states, and that's what I'll be using going forward (and correcting retroactively).
For the other 8, however, I'll manually update 3 of them (FL, WI, KS).
12/x
But 5 states *only* show the change in *first time ever* testers (as far as I can tell): Vermont, Oregon, Louisiana, Delaware, and Iowa.
VT is so low that it won't make much difference in the NE anyway. And at least the other states are all in separate regions of my data.
13/x
Starting with today's thread, I will be using the new data, and you'll notice some changes.
My "Great Plains" region, for example, was absurdly over-inflated, since all seven states had this reporting issue!
14/x
One final note: the overall US trends are don't change *that* much with the shift. 8 of the 10 most populous states were already being reported the more accurate way, including states conducting high levels of testing (CA, NY, TX, IL).
But they do change some...
15/x
For example, with this updated data (even with the 5 lost-cause states hurting), the US percent testing positive yesterday was 4.36%.
And now (as of yesterday's reporting), we showed a week-over-week drop in percent testing positive for 64 of the last 65 days.
16/x
Thanks to all of you who follow me or engage with me for helping me figure this stuff out. Folks poked me about FL, CO, and other states when seeing the discrepancies in positive testing between the state websites and my data.
You've helped me fix this. I appreciate it.
17/x
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A few days ago, I stumbled upon an exchange between @michaelsfuhrer, @greg_travis, @karencutter4, @PienaarJm.
The crux is Greg’s claim of a sharp increase from 2022 to 2023 in 18-44yo deaths from disease in the US (his graphic below).
Greg is wrong.
Join me on a 12-pack 🧵
2/ It quickly became apparent that the main point of contention was whether including R99-coded deaths (“Other ill-defined and unspecified causes of mortality”) in Greg's definition of deaths from disease, as they are later re-coded to non-disease deaths.
3/ Oh, but not to worry. Greg states that "R99 itself is a tiny portion of overall deaths and generally resolves to <2,000 deaths a month overall (out of 300K deaths a month)."
Weekly #Covid19 update in my Substack newsletter, The Issue. Just click the link below.
I'll excerpt a few portions below, but the upshot is: steady rise in cases/% positive, lower rise in Hosps, even lower for ICUs, and continued decline in deaths. thelawyercraig.substack.com/p/covid-19-wee…
"Despite the rise in other metrics, deaths late last week dropped below 300 (7-day-average) for the first time since June/July 2021. ICU census is still well below pre-Omicron pandemic lows."
"Perhaps the best news right now is global Covid deaths. According to Our World in Data, global daily confirmed Covid-19 deaths (7DA) have dropped to 1,772. For comparison, . . . our lowest ever number globally was 4,436 before Omicron entered the picture."
I cannot overstate the absolute idiocy of touting this study purporting to show Omicron is just as likely to send someone to the hospital or the morgue as Delta.
There are 2 enormous issues with this study (among others, I'm sure).
2/ ISSUE #1: The authors use PCR positives as the case denominator and just assume that the "case-to-infection" ratio was similar between all 4 periods. Unbelievable.
The fact that a study can look at the data and just say this boggles my mind. Just read that green highlighting!
3/ Here were Massachusetts' peak positive testing percentages for the 4 different periods in the study (data = @CDCgov)
8.69% - Winter 20-21
2.62% - Spring 21 (sub-1% for 38 days!)
4.47% - "Delta" (per the study)
23.36% - "Omicron"
#Covid19 in South Africa...5th wave? Well, that depends on what metric you use to define wave.
Thread 🧵🧵🧵
2/ If you look at 7DA cases, it's a clear increase. It's a long way off from the OG Omicron peak (and not quite as vertical), but they're still up ~4x in barely over 2 weeks.
3/ But everywhere is testing a bit less these days, so what about % positive? Yep, even more vertical, and more closely resembles the prior waves.
Of course, these are all just tests/infections. Let's look at outcomes...
Down 91.5% from peak. Seeing a rise nationally from recent low of 2.13%. During the entire pandemic, was only lower in June 2021 than our recent numbers.