I’m going to share something about 2020 that deserves a second glance. If you don’t like Trump, forgive me, I’m going to quote him…it’s for a good cause. Remember, this isn’t about Trump. It’s about my friend, science, who was killed by coronavirus last year.
Edit: Trump had said that as we increase the testing, we’d see more COVID cases. I’d originally quoted a news source here- I think it was CNBC- but they’ve since taken down their story. No wait, here it is!
Remember that? Everyone had a good laugh at Trump’s expense. Some of us actually stopped to THINK about it though. I’ll explain.
Suppose there are 100 people in a room, and 10 of them have COVID:
Let’s watch what happens when we measure COVID cases using various sample sizes: 20-, 40-, then 80-person subsets.
First, let’s test 20 people in this group:
Case number = 2
[notice it’s still a 10% infection rate rate in the sample population. 2/20 = 1/10 = 10%]
Now let’s test 40 people in this same group:
Well wouldn’t you know- the case number jumped up to 3.
[interestingly, the infection rate in this sample population is 3 out of 40, or 7.5%]
Let’s test 80 people in this same group:
Now the total case number is 8.
[Infection rate is 8/80 = 1/10 = 10%]
Does the number of positive test results (cases) increase with the number of people tested?
Trump was correct.
There’s a positive linear relationship between the number of tests administered and the number of positive test results.
Granted, I’ve effectively modeled random sampling here. I tested arbitrarily from the left, and worked my way to the right, with cases randomly distributed, and no pre-screening. With real world pre-screening, you’d expect some selection bias. People who have symptoms are more likely to seek & receive testing than people without symptoms.
However, any selection bias would remain fairly consistent over time (despite being influenced by shifting administrative policies deciding which people and how many people receive testing). Without an in-depth analysis, I’m quite certain a positive linear relationship still holds true in the real world, across time. I admit this is an assumption.
more testing = more cases
Crazy talk? Nope. Just common sense. It’s only funny if you don’t think about it for a second. Which is funny, too.
Ah, but when the media told us to laugh, we laughed. People are trained to soak in information without taking time to consider it. The average plumber is a better scientist than most scientists, because a plumber learns to think for himself.
Doesn’t matter how much you know, if you don’t have an ounce of common sense! Which brings us back to fake journalism.
The American media has been consistently presenting case numbers as if it were a meaningful way to measure COVID.
Case numbers only has meaning when we compare it to:
a) the number of tests – this gives the positivity rate
b) the total population – this gives the infection rate
Of course, the reliability of the PCR test for diagnosis is dicey, which makes the whole discussion of case numbers and case rates dicey. Reliance on inappropriate test parameters has been yielding inappropriate results. You’re not going to hear this from the NIH, NIAID, FDA, CDC, or the WHO, because they have a financial stake in a successful ongoing fear campaign leading to drug and vaccine implementation. The inventor of the PCR test said you can use PCR to “find anything in just about anything”. See video here. Then there’s the matter of presumed cases, which I’ll leave to medical professionals for comment.
Now, the CNBC article I quoted above DOES get into the positivity rate a bit, which is nice. They of course dance around the issue and paint a slanted picture of doom & gloom. As CNBC stated in their article, “However, public health specialists have repeatedly said the data does not indicate that increased testing accounts for the recent surge in daily new cases.”
Recent surge? It’s a joke and a sham. Here’s why:
Have a look at the following graph from the CDC (FYI- you can access the current graph here). This is data CNBC would have had access to back in June (for the relevant time period), so let’s use it for the sake of discussion.
Notice the solid black line, which represents Percent Positive. It peaked at just over 22% in early April, 2020. Then it dropped hard for five or six weeks, taking us into June. At the time the CNBC article was written (June 23, 2020), it looks like Percent Positive may have climbed again by three or four percent. Of course, I recall the media painting a horrifying picture by saying things like “case rates are up by an incredible 150% in this second surge“.
While that’s a true statement, I can present the same data differently by saying, “Positive test results are up just slightly in June, from 7% to 10%”. We can affect people emotionally by presenting data certain ways. Please be conscious of this next time you listen to the news.
Dudes? What the hell happened to the Influenza-Like Illnesses (green line) during the winter of 2020-2021? No flu cases this winter? Really? Or is COVID the new word for influenza? I see why doctors and nurses have been blowing the whistle about changes to diagnostic criteria.
Percent Positives for COVID are down compared with last Spring, yet the combined total deaths from influenza, pneumonia, and COVID are similar to those during the first wave of COVID. Okay. Is it truly a more lethal strain of COVID causing this, or is it pneumonia?….or is it actually the flu which nobody seems to be diagnosing this year? There isn’t enough data here to say, since everything is lumped together. Changes in diagnostic criteria and hospital admission trends have been obfuscating reality. See this statement from the Association of American Physicians and Surgeons for perspective.
Truth, honesty, openness, and science have been herded into a dark corner and told to shut the hell up.
Science may be dead, abused, or taboo today. Help bring back science by thinking for yourself. We are each as smart as the brightest scientist, and almost as clever as the handiest plumber.
I’m not saying we have the big picture completely wrong….but we do place far too much trust in “authoritative sources”. It’s crazy.
Turn off the TV news, step back, and breathe. Then curl up with some raw data and find the truth for yourself!
Take Care & God Bless,