September 16, 2020

Undetected COVID cases?

The Herald

Researchers from the Australian National University have now developed a new test which picks up previous Covid-19 infection in a patient’s blood

The study indicates eight in 3000 healthy and previously undiagnosed Australians had likely been infected with the virus.

“This suggests that instead of 11,000 cases we know about from nasal swab testing, about 70,000 people had been exposed overall,” Associate Professor Ian Cockburn said.

We had a few of these ‘seroprevalence’ studies a while back. If you’re trying to estimate a proportion as low as 8 in 3000 from a sample, you need a representative sample and you need a test with a false-positive rate that you know is much lower than 8 in 3000.

Let’s look at the preprint:

You don’t need to download the PDF,  just skimming the abstract will tell you how they got the 3000 people, and what the uncertainty is:

 We used this assay to assess the frequency of virus-specific antibodies in a cohort of elective surgery patients in Australia and estimated seroprevalence in Australia to be 0.28% (0 to 0.72%)

Emphasis added: the uncertainty interval goes all the way down to  zero.   In contrast to some of the earlier seroprevalence studies, they seem to have done the analysis right, but I’m not convinced that people getting  surgery are a representative sample — they certainly aren’t a random sample.

If you do click through the PDF, the Discussion section says it even more clearly

Here we report results from the first large scale seroprevalence survey in Australia. We estimate a seroprevalence of 0.28%, which–given a population estimate for Australia of 25.50 million individuals — equates to 71,400 infections(95% CI: 0 to 181,050).

It’s actually pretty impressive  that the test is as good as it is, but it’s still not really up to the challenge of providing reliable evidence on the number of people exposed to Covid in Australia.

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Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »