So, Delaware County has triggered indicator #6, 'increase' in new hospital admissions again.
Let's take a look, shall we?
Please look at the above graphic showing indicator #6 and a spreadsheet showing the 'hospitalizations.' First, note that this graph is a 7 day moving average. Each point represents 7 full days all averaged together. In order to have a value of '0' it's not just one day with 0.
It's at least 7. And on this graph, we see that there were 11 days without a single hospitalization from 4/2 and 4/11 there were 0 hospitalizations. And then again, there have been NO HOSPITALIZATIONS since 4/16.
Below the graph, please examine the spreadsheet. These are the exact hospitalizations that are represented in this graph. All 11 of them that have occurred over 4 full weeks.
Two (yellow) have 'onset' on date of admission, almost certainly people who had no symptoms, but tested positive while being admitted for another reason.
Two (orange) have an 'onset' ~1 month before hosp. Again, this is not indicative of a hospitalization for a respiratory virus.
One in red is, again, the nonsense of an 'unknown' date of hospital admission, while the other is of a 0-19 year old that was admitted to the hospital on 4/13, but did not have 'onset' until 13 days later. Again, this child was clearly not hospitalized for COVID-19.
⭐️⭐️⭐️Let it sink in - this county has over 200,000 residents and has had 5 potentially legitimate hospitalizations for COVID-19.
Today is Thursday, data dump day. The day we get our new official cases/100,000. Just 1 week ago, we were at 185.8 cases/100,000. Today, we will be at 155.9 (or close to it - they pull their data at a slightly different time than the csv file).
This is the number for all cases, probable and confirmed, and over 14 days. Two weeks ago, we were at 200 cases/100,000 (the last time Gov. DeWine mentioned the formerly all-important number). A drop of 44.1 cases/100,000, a truly incredible drop, yet will he speak of it today?
What argument do they have for the drop? In order for it to be truly 'science' a prediction must be made that is falsifiable. What is their falsifiable prediction? Have we masked harder? Have we kept further apart?
They don't just come from the ether. In Ohio (and many other places now) we are again focused on easily manipulated 'cases' and more specifically the now all-important 'cases per 100,000.'
Governor DeWine likes to say that it's a standard metric that they've been using all along (though I've noticed of late he no longer tries to tie it directly to the CDC's usage anymore, hmmmm) And it is a standard metric for the CDC. But not how it it being used in this instance.
This metric has been used for a long time for tracking the flu, and indeed, 50 cases/100,000 is the standard 'epidemic level' but what Gov. DeWine does not tell us is that it **matters how long we count for.**
I have been criticized for the focus I have been putting on 'probable' cases for the last month or so. 1/3rd of our cases are 'probable,' so what? "They're mostly just positive antigen test cases! Just as good as PCR confirmed!"
Well, according to the FDA, no. The FDA has been very explicit that antigen tests need to be used in a very conscientious way. Specifically, that to properly interpret antigen tests results, the provider needs to take into account the prevalence of the disease in the region.
Please see fda.gov/.../potential-…... to see their exact recommendations, with a special focus on the section I have attached in the first image.
From that clip, it is clear that prevalence is an incredibly important number to understand.
I had a question about what the significance of the number of days counted in the cases/100,000 metric is - whether it's 7 days (as the CDC counts it) or 14 days (the way Ohio counts it).
So I figure this is a good time for another set of hypotheticals to illustrate how this all works and how important the details really are. In the first attached graphic, I want you to imagine a county with exactly 100,000 residents that has exactly 7 new cases every single day.
If we count only one week's worth of cases (green box) we come up with 49 cases/100,000 - Freedom!
But if we count over 2 weeks (red box), we are suddenly at 98 cases/100,000!! PANIC!
So, there was a really great question in the comments yesterday, asking about where are we in our cases per 100,000 if we were to remove all probables in the last week. Let's take a look, shall we?
Please examine the attached table. In the first column I have listed out 'probable' cases, confirmed cases and the total combined from 2/24/21-3/9/21 - the range used for our current number. In the second column I have calculated the all important cases per 100,000 metric.
As you can see, the number of 'probables' alone exceeds the 50 cases/100,000.
But interestingly enough, if we were to count only confirmed cases and actually follow what the CDC does -
As it is Thursday, I have a post for you today in anticipation of Gov. DeWine's new Maps of Fear which he has tried to phase in. I have previously discussed both the new red and blue maps and their issues -
- but today I hope to illustrate even more clearly what level of manipulation is going on, particularly with the new blue 'ICU Utilization' map.
Attached I have two images.
The first is a hyper-simplistic (and unrealistic) but illustrative example of the calculations that the new blue map goes through to arrive at its numbers.