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.

The COVID-19 pandemic has laid bare the inadequacy of the U.S. healthcare system to deliver timely and resilient care. According to the American Hospital Association, the pandemic has created a $202 billion loss across the healthcare industry, forcing health care systems to lay off workers and making hospitals scramble to minimize supply chain costs. However, as the demand for personal protective equipment (PPE) grows, hospitals have sacrificed sustainable solutions for disposable options that, although convenient, will exacerbate supply strains, financial burden, and waste. We advocate for reusable gowns as a means to lower health care costs, address climate change, and improve resilience while preserving the safety of health care workers. Reusable gowns' polyester material provides comparable capacity to reduce microbial cross-transmission and liquid penetration. In addition, previous hospitals have reported a 50% cost reduction in gown expenditures after adopting reusable gowns; given the current 2000% price increase in isolation gowns during COVID-19, reusable gown use will build both healthcare resilience and security from price fluctuations. Finally, with the United States' medical waste stream worsening, reusable isolation gowns show promising reductions in energy and water use, solid waste, and carbon footprint. The gowns are shown to withstand laundering 75–100 times in contrast to the single-use disposable gown. The circumstances of the pandemic forewarn the need to shift our single-use PPE practices to standardized reusable applications. Ultimately, sustainable forms of protective equipment can help us prepare for future crises that challenge the resilience of the healthcare system.

Objective: To explore sequential steps of employee engagement in wellness interventions and the impact of wellness interventions on employee health. Methods: Using previously collected survey data from 23,667 UK employees, we tabulated intervention availability, awareness, participation, and associated health improvement and compared engagement by participation and risk status. Results: Employees’ awareness of wellness interventions at their workplaces was often low (mean 43.3%, range 11.6%–82.3%). Participation was highest in diet/nutrition initiatives (94.2%) and lowest in alcohol counseling and smoking cessation interventions (2.1%). Employees with health risks were less likely than lower-risk employees to report awareness, participation, and health improvements from wellness interventions addressing the relevant health concern. Conclusion: Employers and policymakers should consider variation in intervention engagement as they plan and implement wellness interventions. Engaging employee populations with higher health risks requires a more targeted approach.