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.
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.
BACKGROUND Surgical stabilization of rib fracture (SSRF) is increasingly used to manage patients with rib fractures. Benefits of performing SSRF appear variable, and the procedure is costly, necessitating cost-effectiveness analysis for distinct subgroups. We aimed to assess the cost-effectiveness of SSRF versus nonoperative management among patients with rib fractures younger than 65 years versus 65 years or older, with versus without flail chest. We hypothesized that, compared with nonoperative management, SSRF is cost-effective only for patients with flail chest. METHODS This economic evaluation used a decision-analytic Markov model with a lifetime time horizon incorporating US population-representative inputs to simulate benefits and risks of SSRF compared with nonoperative management. We report quality-adjusted life years (QALYs), costs, and incremental cost-effectiveness ratios. Deterministic and probabilistic sensitivity analyses accounted for most plausible clinical scenarios. RESULTS Compared with nonoperative management, SSRF was cost-effective for patients with flail chest at willingness-to-pay threshold of US $150,000/QALY gained. Surgical stabilization of rib fracture costs US $25,338 and US $123,377/QALY gained for those with flail chest younger than 65 years and 65 years or older, respectively. Surgical stabilization of rib fracture was not cost-effective for patients without flail chest, costing US $172,704 and US $243,758/QALY gained for those younger than 65 years and 65 years or older, respectively. One-way sensitivity analyses showed that, under most plausible scenarios, SSRF remained cost-effective for subgroups with flail chest, and nonoperative management remained cost-effective for patients older than 65 years without flail chest. Probability that SSRF is cost-effective ranged from 98% among patients younger than 65 years with flail chest to 35% among patients 65 years or older without flail chest. CONCLUSIONS Surgical stabilization of rib fracture is cost-effective for patients with flail chest. Surgical stabilization of rib fracture may be cost-effective in some patients without flail chest, but delineating these patients requires further study. LEVEL OF EVIDENCE Economic/decision, level II.
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