I will not reply directly to the bad faith actor who linked a laughably superficial (or dishonest) interpretation of specificity and sensitivity. For those interested, when using a Bayesian approach to address a clinical question, you estimate a pretest probability of disease, then interpret the test you are using through positive and/or negative predictive value in the form of a likelihood ratio, and this will result in your post-test probability. See the below graphic for a simplified way to view this.
https://media.springernature.com/ful...ML.jpg?as=webp
This is a good article to help those who are not familiar with different testing types and how to interpret them. There is a simple graph in here I suggest you all look at as it is well done.
https://jamanetwork.com/journals/jam...rticle/2765837
For the most part, RT-PCRs are designed to be high specific, so the risk of false positive is low. I found it hilarious that the author of the interpretation complained about testing for fragments of the virus. That is literally what RT-PCR is designed to do. Maybe the Emeritus professor needs to go back to school in the 21st century so he can understand the basics of molecular biology. A lot has changed since he went to medical school in, if I read correctly, the 1970s. It is true when they say medicine advances with one physician retirement (or death in the darker version) at a time. The number quoted of 70% specificity for the Covid-19 is inaccurate, and although there are variations of tests out there, RT-PCR are much more specific than that.
We also use PCR testing for most of our viral testing when looking for active disease. We do this well and I think we have enough information about Covid-19 at this time to do a good job interpreting this. Antibody testing is a whole different animal and I think the jury is still out on how to interpret that.
He didn’t complain about testing for virus fragments he explained some of the issues that creates
And he was spot on in regards to widespread testing providing no value at this point when a virus is already widely circulated.
The amount of bad data and inputs is astronomical and when it’s all said and done will be what is remembered about Covid19.
Also very accurate “It should be obvious from the data above that all the testing we have done and continue to do has likely confused more than enlightened.“
Even more so when you consider that there is almost no context the way things are being reported and the fact that we have never tested a virus like what is being done currently. And no other country is testing Covid19 like the US is for obvious reasons.
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