BackgroundAddressing COVID-19 is a pressing health and social concern. To date, many epidemic projections and policies addressing COVID-19 have been designed without seroprevalence data to inform epidemic parameters. We measured the seroprevalence of antibodies to SARS-CoV-2 in Santa Clara County. MethodsOn 4/3-4/4, 2020, we tested county residents for antibodies to SARS-CoV-2 using a lateral flow immunoassay. Participants were recruited using Facebook ads targeting a representative sample of the county by demographic and geographic characteristics. 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. ResultsThe 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. ConclusionsThe 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.

Role of the Funder/Sponsor: The Lilly Endowment Inc Physician Scientist Initiative had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Dendritic cells (DCs) play a central role in initiating immune responses. Despite this, there is little understanding how different DC subsets contribute to immunity to different pathogens. CD8α+ DC have been shown to prime immunity to HSV. Whether this very limited capacity of a single DC subset priming CTL immunity is restricted to HSV infection or is a more general property of anti-viral immunity was examined. Here, we show that the CD8α+ DCs are the principal DC subset that initiates CTL immunity to s.c. infection by influenza virus, HSV, and vaccinia virus. This same subset also dominated immunity after i.v. infection with all three viruses, suggesting a similar involvement in other routes of infection. These data highlight the general role played by CD8α+ DCs in CTL priming to viral infection and raises the possibility that this DC subset is specialized for viral immunity.

Background Measuring the seroprevalence of antibodies to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is central to understanding infection risk and fatality rates. We studied Coronavirus Disease 2019 (COVID-19)-antibody seroprevalence in a community sample drawn from Santa Clara County. Methods On 3 and 4 April 2020, we tested 3328 county residents for immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies to SARS-CoV-2 using a rapid lateral-flow assay (Premier Biotech). Participants were recruited using advertisements that were targeted to reach county residents that matched the county population by gender, race/ethnicity and zip code of residence. We estimate weights to match our sample to the county by zip, age, sex and race/ethnicity. We report the weighted and unweighted prevalence of antibodies to SARS-CoV-2. We adjust for test-performance characteristics by combining data from 18 independent test-kit assessments: 14 for specificity and 4 for sensitivity. Results The raw prevalence of antibodies in our sample was 1.5% [exact binomial 95% confidence interval (CI) 1.1–2.0%]. Test-performance specificity in our data was 99.5% (95% CI 99.2–99.7%) and sensitivity was 82.8% (95% CI 76.0–88.4%). The unweighted prevalence adjusted for test-performance characteristics was 1.2% (95% CI 0.7–1.8%). After weighting for population demographics, the prevalence was 2.8% (95% CI 1.3–4.2%), using bootstrap to estimate confidence bounds. These prevalence point estimates imply that 53 000 [95% CI 26 000 to 82 000 using weighted prevalence; 23 000 (95% CI 14 000–35 000) using unweighted prevalence] people were infected in Santa Clara County by late March—many more than the ∼1200 confirmed cases at the time. Conclusion The estimated prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that COVID-19 was likely more widespread than indicated by the number of cases in late March, 2020. At the time, low-burden contexts such as Santa Clara County were far from herd-immunity thresholds.

There is significant evidence that athletes are using recombinant human growth hormone (rhGH) to enhance performance, and its use is banned by the World Anti-Doping Agency and professional sports leagues. Insulin-like growth factor-1 (IGF-1) is the primary mediator of growth hormone action and is used as a biomarker for the detection of rhGH abuse. The current biomarker-based method requires collection and expedited shipment of venous blood which is costly and may decrease the number of tests performed. Measurement of GH biomarkers in dried blood spots (DBS) would considerably simplify sample collection and shipping methods to allow testing of a greater number of samples regardless of location. A method was developed to quantify intact IGF-1 protein in DBS by liquid chromatography-tandem mass spectrometry. A step-wise acid-acetonitrile extraction was optimized to achieve a sensitive assay with a lower limit of quantification of 50 ng/mL. IGF-1 remained stable at room temperature for up to 8 days, which would allow shipment of DBS cards at ambient temperature. In a comparison between plasma concentrations of IGF-1 and concentrations measured from venous and finger prick DBS, there was good correlation and agreement, r(2) of 0.8551 and accuracy of 86-113 % for venous DBS and r(2) of 0.9586 and accuracy of 89-122 % for finger prick DBS. The method is intended for use as a rapid screening method for IGF-1 to be used in the biomarker method of rhGH abuse detection.