I would be careful of drawing too many conclusions from this article. They are using the number or people who tested positive in the antibody test to determine the fatality rate. I don't see where the article indicates anything about the sensitivity or the false positive rate of the antibody test they used. Both of these are important factors and can really skew results when the amount of infection found in the community is low. This is due to Bayes' theorem, which has a lengthy wikipedia article. I think an easier to understand explanation is the figures below. The sensitivity and false positive rates were taken from news reports a couple weeks ago about the antibody test that was being developed. I don't know if the same test was used in this study, so the sensitivity and false positive rates may be different. But what these figures do show is that depending on the level of true infection found in the community, you can get wildly different ratios of detected true infections to false positives. This becomes more important when the true level of infection is a small percentage of the population. For instance, in the left figure the observed rate of infection is 5% whereas the true rate of infection is actually 1%. For the right figure the observed rate of infection is 13% whereas the true rate is 10%. So the error is significantly higher at lower levels of infection, and does so in such a way that it overestimates the number of people who have become infected by this virus. And the LA Times article states that 4% of people tested positive for antibodies, which falls in the category of low levels of exposure where the observed positives is likely much higher than the true positives. Of course, the caveat is that we don't know how good the antibody test they used for the study is. If they used a better antibody test with a much, much lower false positive rate, this would be less of a problem.
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Full disclosure, these are figures my friend who has a PhD in biochemistry made and then shared on Twitter for others to use. I am an organic chemist and we seldom if ever use statistics, so I was only useful as a clueless sounding board in the attempt to make easily understandable figures.