Essentially the problem with the study is that the bounds on the false positive rate of the test used was such that the data are completely consistent with all of the positives being false positives.
https://arstechnica.com/science/2020/04/experts-demolish-stu...
I think calling it "extreme ignorance of binomial confidence intervals" is incorrect and far too charitable. The authors were intentionally deceitful. Co-authors of the preprint requested that they be taken off the pre-print because they had warned that the statistics were bad. Prior the the prevalence study, they had cherry picked weird data sets and published an editorial. They are clearly trying to bend the data to their preconceived notions, in a really public way.
To see journalists pick up their work again, just because they are at a big name institution, is a huge betrayal of the public trust.
Come on man, let's be fair: a couple of tweets and a few snarky emails hardly consist of the "scientific body demolishing them." I'm not sure if I agree with Bhattacharya's study, but it's hardly been universally repudiated. This just low-effort politicizing by Ars Technica (which has a spotty record to begin with).
Even this critical blog post[1] has all kinds of colorful discussion (mostly by academics) showing that things are simply not as cut-and-dry as we'd like them to be.
[1] https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw...