A quick lesson in medical statistics for those of you who believe the current "second wave" scare story out of #Victoria.
It starts with the concepts of sensitivity, specificity and positive predictive value.
Even doctors struggle with this..
Each medical test that you have has a built-in level of accuracy (and therefore inaccuracy). Most tests will identify most people with a disease correctly and also without a disease correctly. But no tests are perfect.
The #Theranos story for example (but I digress)...
Sensitivity is the probability that the test will be positive in people with a disease.
The "pick up rate" if you will. Usually this is high. Expect 100% but we are seeing reports of 50-70% in #covid19
So, of 100 people with Covid, 30 could test negative.
You need to have a bit of statistics background to understand this. It's all about the variance. When you have different groups they vary. The more numbers you have in each group, the less the variance (proportionally).
Different groups would never have the same variance
Except in this study!
Not only do all these age groups have the same variance in this chart, but what *should* happen is that very small groups would have big variance (confidence intervals on this chart).
Well, it appears there are a lot of hypertensive teens with #covid19
(1) the study says that they received data from 600 hospitals up to mid-April, and it was published end-May.
This is impossible. If you have ever collected clinical research data you will know how impossible it is.
You have to get doctors to enter information and they are completely unreliable, requiring to be chased all the time. If you're lucky some units have a research nurse who is much better, but the data reports are either on paper (needing mailing/faxing) or an electronic repository