This medRxiv study released April 14, 2020 attempts to add meaningful data to the discussion, by measuring the seroprevalence of antibodies to SARS-CoV-2 in Santa Clara County. (Seroprevalence means the level of a pathogen in a population, as measured in the blood serum.)
They tested 3300 people, adjusting for zip code, sex, and race/ethnicity.
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.
Conclusion: 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. Population prevalence estimates can now be used to calibrate epidemic and mortality projections.
CF Note: This study was reported on in both the SJ Mercury News, and the SF Chronicle as uncertain and mostly bad news. In fact, in my opinion, this is good news! It means the denominator is much greater than originally guessed in the modeling, bringing down the grim statistics currently being used to support the economic lockdown.
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