https://www.discovermagazine.com/health/covid-19-antibody-testing-tougher-than-true-false In the United States, eight organizations had received emergency use authorization from the Food and Drug Administration for antibody tests, as of April 30. But the FDA announced in March that test makers could sell Covid-19 diagnostics as soon as they’re satisfied with their own test and have notified the FDA, before the agency has reviewed their data. Dozens of tests have come out under these guidelines. Often, these antibodies are detected via a test called an ELISA (enzyme-linked immunosorbent assay), which is typically run in a lab, taking a few hours. An alternative test, using the same principles, takes place on a paper strip, much like a pregnancy test. This test, called a lateral flow assay, can be used in a doctor’s office, with results in minutes. But the World Health Organization has warned that the faster tests are less accurate. Part of the challenge with specificity in this context is that SARS-CoV-2 is not the only member of the coronavirus family to infect human beings. Two other coronaviruses, SARS and MERS, caused earlier multi-country outbreaks. Moreover, there are at least four coronaviruses that cause a fraction of cases of the common cold. Many people have been exposed to these common-cold coronaviruses, and could be carrying antibodies against them. So any Covid-19 test must be able to distinguish between the novel coronavirus and the more common, less dangerous ones. A lot of the tests being used right now fail to do so, says Sylvia Daunert, a bioanalytical chemist and director of the JT Macdonald Foundation Biomedical Nanotechnology Institute at the University of Miami in Florida. Daunert coauthored a paper on the use of antibody-like molecules in biotechnology for the Annual Review of Analytical Chemistry in 2017. jem, A test that is has 95% specificity and 95 % Sensitivity is used to test a community of 500 with a 5% actual Prevalence of Covid-2 will produce 50% false positive. i.e., a person who tests positive has only a 50 percent chance of actually being positive. But the early tests used extensively were not this specific. with a lower prevalence, tests are more likely to give false positives. Search recent Scientific American issues for the following:try https://www.scientificamerican.com/article/what-covid-19-antibody-tests-can-and-cannot-tell-us/ The preprint study on an antibody test in Santa Clara County claimed that it had a specificity of 99.5 percent. But University of Washington epidemiologist Trevor Bedford argued in a Twitter thread that if that test instead had a 98.5 percent specificity—well within the possible range of uncertainty defined by the researchers—all of the study’s “positive results” could have been false positives. there is massive literature on this. use Google. If your going to get your information from our Jackass President or Fox, be prepared to be wrong 100% of the time. Also, see an earlier post of mine, perhaps it was in chit chat, which give a reference to a peer reviewed article on an antibody test(a very carefully done one) on SARS-Covid exposed hospital workers. SARS-Covid-2 is so similar to SARS-Covid-1 that it is highly unlikely the asymptomatic statistics are significantly different between the two viruses. And if all else fails, there is always common sense to fall back on. Why would 50% of passengers on a ten day cruise develop SARS-Covid-2 antibodies at sufficient titer to be detected!!! Probably the meat plant data is similarly flawed in that it is likely reporting many false positives for antibodies. I doubt Smithfield is going to spring for the cost of doing lab ELIZA on their undocumented workers.
1. this does address the issue of whether the antibody tests were considered in the statistics we were discussing. As I told you the stats came out before the antibody tests. Do you have any new studies saying that the antibody tests were considered when calculating the number of asymptomatic but infected? 2. My wife's friend went positive negative positive negative with antibody tests. 3. I agreed with you position that many of the tests are not as accurate as would like.
For individuals the quick antibody tests that were being extensively used are worthless. They are useful for population surveys but worthless for individual diagnostics. There was no centralized data base for the U.S. until sometime in May, and that data base co-mingles antibody and live covid tests. It's a total, Federal failure. There is no known case of a Covid version of Typhoid Mary. The reports you may have heard of large numbers of asymptomatic carrier are "fake news." jem, it's is too complicated to explain this to the general public. Let others try, I say. They ONLY tests that were widely available when the more ridiculous reports of large numbers of asymptomatic carriers surfaced were unreliable "quickie," antibody tests. These tests dominate the data. Equally absurd were the reports that the virus is not nearly as dangerous as thought because there are large numbers of people who have antibodies (NOT) and they never had symptoms. In a Trumpian World truth is a rare quantity. The people who tell the truth have already been fired, or they are on their way out the door.
I agree its a total failure. Do you think quality scientists could do that by mistake and not immediately correct it or do their best to update? -- 2. But with regards to percent of asymptomatic spread... you have not provided any proof. 3. Now you seem to making a straw man argument. I never made a statement about typhoid mary... or an asymptomatic super spreader.... But... There is a great deal of evidence for clusters and super spreaders... for instance... https://www.sciencemag.org/news/202...ny-others-whereas-most-don-t-spread-virus-all Estimates of k for SARS-CoV-2 vary. In January, Julien Riou and Christian Althaus at the University of Bern simulated the epidemic in China for different combinations of R and k and compared the outcomes with what had actually taken place. They concluded that k for COVID-19 is somewhat higher than for SARS and MERS. That seems about right, says Gabriel Leung, a modeler at the University of Hong Kong. “I don’t think this is quite like SARS or MERS, where we observed very large superspreading clusters,” Leung says. “But we are certainly seeing a lot of concentrated clusters where a small proportion of people are responsible for a large proportion of infections.” But in a recent preprint, Adam Kucharski of LSHTM estimated that k for COVID-19 is as low as 0.1. “Probably about 10% of cases lead to 80% of the spread,” Kucharski says.