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.

Background Many mathematical models have investigated the impact of expanding access to antiretroviral therapy (ART) on new HIV infections. Comparing results and conclusions across models is challenging because models have addressed slightly different questions and have reported different outcome metrics. This study compares the predictions of several mathematical models simulating the same ART intervention programmes to determine the extent to which models agree about the epidemiological impact of expanded ART. Methods and Findings Twelve independent mathematical models evaluated a set of standardised ART intervention scenarios in South Africa and reported a common set of outputs. Intervention scenarios systematically varied the CD4 count threshold for treatment eligibility, access to treatment, and programme retention. For a scenario in which 80% of HIV-infected individuals start treatment on average 1 y after their CD4 count drops below 350 cells/µl and 85% remain on treatment after 3 y, the models projected that HIV incidence would be 35% to 54% lower 8 y after the introduction of ART, compared to a counterfactual scenario in which there is no ART. More variation existed in the estimated long-term (38 y) reductions in incidence. The impact of optimistic interventions including immediate ART initiation varied widely across models, maintaining substantial uncertainty about the theoretical prospect for elimination of HIV from the population using ART alone over the next four decades. The number of person-years of ART per infection averted over 8 y ranged between 5.8 and 18.7. Considering the actual scale-up of ART in South Africa, seven models estimated that current HIV incidence is 17% to 32% lower than it would have been in the absence of ART. Differences between model assumptions about CD4 decline and HIV transmissibility over the course of infection explained only a modest amount of the variation in model results. Conclusions Mathematical models evaluating the impact of ART vary substantially in structure, complexity, and parameter choices, but all suggest that ART, at high levels of access and with high adherence, has the potential to substantially reduce new HIV infections. There was broad agreement regarding the short-term epidemiologic impact of ambitious treatment scale-up, but more variation in longer term projections and in the efficiency with which treatment can reduce new infections. Differences between model predictions could not be explained by differences in model structure or parameterization that were hypothesized to affect intervention impact. Please see later in the article for the Editors' Summary

Background In a recent randomized controlled trial, daily oral preexposure chemoprophylaxis (PrEP) was shown to be effective for HIV prevention in men who have sex with men (MSM). The United States Centers for Disease Control and Prevention (CDC) recently provided interim guidance for PrEP use among MSM who are at high risk for acquiring HIV. Previous studies failed to reach a consistent estimate of its cost-effectiveness. Objective To estimate the effectiveness and cost-effectiveness of PrEP in MSM in the United States. Design Dynamic model of HIV transmission and progression combined with a detailed economic analysis. Data Sources Published literature. Target Population MSM aged 13–64 in the United States. Time Horizon Lifetime. Perspective Societal. Interventions We evaluated PrEP for the general MSM population and for high-risk MSM. We assumed that PrEP reduces infection risk by 44%, based on clinical trial results. Outcome Measures New HIV infections, discounted quality-adjusted life-years (QALYs) and costs, and incremental cost-effectiveness ratios. Results of Base-Case Analysis If PrEP is initiated in 20% of MSM in the United States, we estimate a 13% reduction in new HIV infections and a gain of 550,166 QALYs over 20 years at a cost of $172,091/QALY gained. Initiating PrEP in a larger proportion of MSM averts more infections but at increasing cost per QALY gained ($216,480/QALY gained when 100% of MSM receive PrEP). Using PrEP only in high-risk MSM can improve its cost-effectiveness. PrEP costs approximately $50,000/QALY gained for MSM with 5 annual partners on average. PrEP for all high-risk MSM for 20 years leads to $75 billion in healthcare-related costs incremental to the status quo and costs $600,000 per HIV infection averted, compared with incremental costs of $95 billion and $2 million per infection averted for 20% coverage of all MSM. Results of Sensitivity Analysis PrEP use in the general MSM population costs less than $100,000/QALY gained if the daily cost of antiretroviral drugs for PrEP is less than $15 or if PrEP efficacy is greater than 75%. Limitation When examining PrEP use in high-risk MSM, we did not model mixing between low- and high-risk MSM because of lack of data on mixing patterns. Conclusion Use of PrEP for HIV prevention in the general MSM population could prevent a substantial number of HIV infections but is expensive. PrEP use in high-risk MSM compares favorably to other interventions considered cost-effective, but could result in annual expenditures on PrEP of over $4 billion.