Potential false-positive rate among the 'asymptomatic infected individuals'

One fallacy that seems universal with healthcare folks is they think the false positive rate is the chance that a given positive result is erroneous. If an illness is rare, a positive result in a test with a 1% error rate might have an overwhelming probability of being a false positive. This is why prior probabilities need to be taken into account in making decisions.

In Denmark we increased our testing 10-fold and found 300% more people infected. Our response to that increase has been to shut down the country completely for 2 weeks and expand our governments right to act: Forced entry into private property, forced isolation and treatment, forced testing. If this is all because of an error in the test kit I'm going to be super ticked off.

Would this indicate that the mortality rate is actually much higher percentage-wise, since the denominator is actually artificially inflated?

One big question is what percentage of positive tests are asymptomatic? If only a tiny percent are asymptomatic, then this false positive issue would not be elevating the total numbers much, right? I won’t claim to have the best resource here but one article stated:<p>“ Dr. Tedros noted that only 1 percent of cases in China are reported as “asymptomatic.” And of that 1 percent, 75 percent do go on to develop symptoms.”<p><a href="https:&#x2F;&#x2F;arstechnica.com&#x2F;science&#x2F;2020&#x2F;03&#x2F;dont-panic-the-comprehensive-ars-technica-guide-to-the-coronavirus&#x2F;2&#x2F;" rel="nofollow">https:&#x2F;&#x2F;arstechnica.com&#x2F;science&#x2F;2020&#x2F;03&#x2F;dont-panic-the-compr...</a>

How did they estimate this? If anybody can read the actual paper, I’d love to know.<p>If false positives dominate true positives then you’d expect total positives to depend primarily on number of tests given, right? Which sounds wrong to me, but I’d be interested in hearing other thoughts.

Can someone clarify which type of test they analyzed? 80% seems way too high. I would expect something closer to 10% at most (which would still mean the probability of a true positive might be very low per Bayes&#x27; theorem)

Interesting, as this means that China would be quarantining more people than &quot;necessary&quot;, which would help slow the pandemic anyway. I can&#x27;t imagine an asymptomatic person would put stress on the hospital system? But maybe I&#x27;m wrong there.<p>I am curious if this also could indicate a false-positive problem with non asymptomatic people as well.<p>False-positives are also why the CDC tests had to be shipped back, although that was because it was showing false positives in other diseases it was testing for, not COVID-19.

Wait, so the actual mortality rate for COVID-19 is much higher than thought because of all the false positives on cases without symptoms?

Anyone save the full text? Every time I try to get to it I get a 404.

If tests indeed have such a high false-positive rate, then all estimates of fatality rate calculated by dividing over the number of individuals identified as &quot;infected&quot; are too low, i.e., by implication the virus is actually deadlier than naively estimated.<p>EDIT: <i>All else remaining the same.</i> See AnthonyMouse&#x27;s comment below for important clarifications and corrections.