We do not have good test and data based results for infection rates based on the antibody test surveys. Various statistical modeling and testing problems are discussed at the link to a Columbia University Statistician.
None of the COVID-19 antibody test are accurate enough for mass screening. In early April, the FDA gave an emergency authorization to its first antibody blood test for COVID-19. It was developed by Cellex. According to the company, the test agreed with positive results from PCR tests 93% of the time and negative results 96% of the time. This would mean that 4-7% percent false positives and false negatives.
If you have 1 percent of your population infected and you have a test that’s only 99 percent specific, that means that 50 percent of the time you will have a real positive and 50 percent of the time it won’t be. The Santa Clara California study with 5% infection rate is the product of statistical error.
We need tests with specificity very close to 100% accurately measure infection rates in the 0-3% range. 99% specificity and we are figuring out infection rates with about plus or minus 2-3%.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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