This is a preprint, not a peer-reviewed article; from the abstract:
We report the prevalence of antibodies to SARS-CoV-2 in a sample of 3,330 people, adjusting for zip code, sex, and race/ethnicity. We also adjust for test performance characteristics using 3 different estimates: (i) the test manufacturer's data, (ii) a sample of 37 positive and 30 negative controls tested at Stanford, and (iii) a combination of both. Results The unadjusted prevalence of antibodies to SARS-CoV-2 in Santa Clara County was 1.5% (exact binomial 95CI 1.11-1.97%), and the population-weighted prevalence was 2.81% (95CI 2.24-3.37%). Under the three scenarios for test performance characteristics, the population prevalence of COVID-19 in Santa Clara ranged from 2.49% (95CI 1.80-3.17%) to 4.16% (2.58-5.70%). These prevalence estimates represent a range between 48,000 and 81,000 people infected in Santa Clara County by early April, 50-85-fold more than the number of confirmed cases. Conclusions The population prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that the infection is much more widespread than indicated by the number of confirmed cases.
If this finding holds up elsewhere, it would suggest the infection fatality rate is much lower than 1%. On the other hand, it would not alter the fact that when infections spread unchecked, healthcare system are overwhelmed, as we saw in Wuhan, Northern Italy, and New York City.
UPDATE: As Professor Risch notes in the comments, California has been lagging in testing, which would mean its confirmed cases lag the actual number of infections even more than elsewhere.
