A rapid, unsolicited peer review on emerging serosurvey data from Santa Clara County, and why I remain skeptical of claims that we are identifying only 1 out of every 50 to 85 confirmed cases. 1/10https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1 …
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The study recruited patients in the county through Facebook ads. To make the survey representative, enrollment was capped when quotas were reached in certain areas, and encouraged in areas with lower participation. A smart strategy for easy recruitment, in my opinion. 2/10
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After completing an online demographic survey (zip code, age, sex, race/ethnicity, comorbidities, prior symptoms), consenting adults could bring a child with them for drive-thru testing at one of three locations. Their final sample size was 2,718 adults and 612 children. 3/10
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Participation rate was not even across the region. This is relevant because the authors report both a crude % seropositive and a population-adjusted % seropositive. Adjustment is achieved through survey weights, to account for undersampling. 4/10pic.twitter.com/HHj0jPXbNI
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The crude seroprevalence is 1.5% (1.11-1.97%). The population weighted seroprevalence is 2.81% (2.24-3.37%). These are different because under-represented combinations of zip code, sex, and race will receive more weight. 5/10
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Having had experience with these types of weighted surveys, I am always a little skeptical when the weighted result is very different from the unweighted result. Here, nearly double. This can be due to a few highly influential observations. Weights can be wonky. 6/10
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I also don't understand the rationale behind weighting at all in this sample. For this to make sense, the infectious outbreak would have to be evenly distributed across the population which is extremely unlikely surely?
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