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.

Purpose-Human resource allocation is considered a relevant problem in business process management (BPM). The successful allocation of available resources for the execution of process activities can impact on process performance, reduce costs and obtain a better productivity of the resources. In particular, process mining is an emerging discipline that allows improvement of the resource allocation based on the analysis of historical data. The purpose of this paper is to provide a broad review of primary studies published in the research area of human resource allocation in BPM and process mining. Design/methodology/approach-A systematic mapping study (SMS) was conducted in order to classify the proposed approaches to allocate human resources. A total of 2,370 studies published between January 2005 and July 2016 were identified. Through a selection protocol, a group of 95 studies were selected. Findings-Human resource allocation is an emerging research area that has been evolving over time, generating new proposals that are increasingly applied to real case studies. The majority of proposed approaches relate to the period 2011-2016. Journals and conference proceedings are the most common venues. Validation research and evaluation research are the most common research types. There are two main evaluation methods: simulation and case studies. Originality/value-This study aims to provide an initial assessment of the state of the art in the research area of human resource allocation in BPM and process mining. To the best of the authors' knowledge, this is the first research that has been conducted to date that generates a SMS in this research area.

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This work represents a comparative uptake study of the toxic elements arsenic, boron, copper, manganese and zinc in monometallic and multimetallic solutions by four green microalgae species (Chlamydomonas reinhardtii, Chlorella vulgaris, Scenedesmus almeriensis and an indigenous Chlorophyceae spp.), evaluating the effect of pH and contact time. Maximum removal efficiencies for each toxic element were 99.4% for Mn (C. vulgaris, pH 7.0, 3 h), 91.9% for Zn (Chlorophyceae spp., pH 5.5, 3 h), 88% for Cu (Chlorophyceae spp., pH 7.0, 10 min), 40.7% for As (S. almeriensis, pH 9.5, 3 h) and 38.6% for B (S. almeriensis, pH 5.5, 10 min). B removal efficiencies decreased remarkably in multimetallic solutions (down to 0.2% in C. reinhardtii), except for Chlorophyceae spp., the only species isolated from a polluted environment. FTIR spectra shown the highest interactions for As (1150-1300 cm) and Cu (3300, 1741, 1535, 1350-1400 cm). Results confirm microalgae biomass as a potential biosorbent for toxic elements.