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.
Resilience was widely identified as a critical attribute for strong health systems following the 2014-15 West Africa Ebola epidemic. In Liberia, Sierra Leone and Guinea, struggles to control the disease and suspension of the operation of many health services demonstrated that health systems must plan for resilience long before a crisis. However, the operational elements of resilience and ways that a crisis experience can shape resilience are not well described in the literature. To understand how a health system adapts to crisis and how the priorities of different health system actors influence this response we conducted interviews with global, national, and local respondents in Liberia between July and September 2015 (n = 108), several months after the country was first declared Ebola-free. We found that health system resilience functions prioritized by global and national actors improved to a greater extent than those valued by community leaders and local health actors over the course of the epidemic. Although the Ebola epidemic stimulated some positive adaptations in Liberia's health system, building a truly resilient health system will require longer-term investments and sustained attention long beyond the crisis.
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