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Really excited to say our paper describing our citywide serosurveillance of the initial SARS-CoV-2 outbreak San Francisco ( #SCALEIT) is now up as a pre-print! https://www.researchsquare.com/article/rs-180966/v1 1/10
"Gold standard" population-based serosurveys often cost a prohibitive amount of time and $$$. As a result, they are performed infrequently if at all, and are difficult to launch quickly in response to an emerging epidemic. 2/10
For example, almost one year after the pandemic started, there are still no city-wide estimates of seroprevalence in San Francisco!! 3/10
Testing blood already collected for other purposes (e.g. routine medical testing) is one way to solve this, but results are often hard to interpret because the population they are sampled from is not known. Are they representative? 4/10
Early on in the pandemic, we launched an ongoing study which algorithmically selected residual blood samples by age and zipcode from two hospital systems in SF to test for antibodies to SARS-CoV-2: #SCALEIT (it's an acronym, full name of study too long for this tweet...) 5/10
Importantly, samples were selected to ensure good coverage of the entire city of SF. We had access to rich EMR data and therefore know where samples were coming from. 6/10
We tested 5000+ samples from late March-June 2020, estimating an overall seroprevalence of 4.2% (adjusted for assay performance + weighted by age + sex) - a case ascertainment of just 4.9%, meaning we estimate only around 5% of infections were detected during this period! 7/10
We find stark and important disparities by race/ethnicity, homelessness status, and neighborhood in the city. Higher seroprev in those who identify as Hispanic/Latinx and Black/African American compared to White/Asian, and also amongst people experiencing homelessness. 8/10
We think that this serosurveillance approach provides a nimble framework that can be expanded beyond San Francisco and applied to other pathogens. We kept collecting samples, so if anyone wants to fund us to analyze them / develop #SCALEIT further, we'd 
to hear from you
9/10
to hear from you9/10
This was a HUGE amount of work carried out by many people including @EPPIcenter_UCSF @adriennepstein @sakitakahashi1 Owen Janson, Kierstinne Turcios, Elias Duarte, @jo_rae_v @jessikator @isabelrodbar @bgreenhouse1, @czbiohub @UCSF clinical labs and @SF_DPH amongst others! 10/10
And @EPPIcenter_UCSF's Jill Hakim!
