Community prevalence of SARS-CoV-2 in England from April to November, 2020: results from the ONS Coronavirus Infection Survey

Background: Decisions about the continued need for control measures to contain the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rely on accurate and up-to-date information about the number of people testing positive for SARS-CoV-2 and risk factors for testing positive. Existing surveillance systems are generally not based on population samples and are not longitudinal in design. Methods: Samples were collected from individuals aged 2 years and older living in private households in England that were randomly selected from address lists and previous Office for National Statistics surveys in repeated crosssectional household surveys with additional serial sampling and longitudinal follow-up. Participants completed a questionnaire and did nose and throat self-swabs. The percentage of individuals testing positive for SARS-CoV-2 RNA was estimated over time by use of dynamic multilevel regression and poststratification, to account for potential residual non-representativeness. Potential changes in risk factors for testing positive over time were also assessed. The study is registered with the ISRCTN Registry, ISRCTN21086382. Findings: Between April 26 and Nov 1, 2020, results were available from 1 191 170 samples from 280327 individuals; 5231 samples were positive overall, from 3923 individuals. The percentage of people testing positive for SARS-CoV-2 changed substantially over time, with an initial decrease between April 26 and June 28, 2020, from 0·40% (95% credible interval 0·29–0·54) to 0·06% (0·04–0·07), followed by low levels during July and August, 2020, before substantial increases at the end of August, 2020, with percentages testing positive above 1% from the end of October, 2020. Having a patient facing role and working outside your home were important risk factors for testing positive for SARS-CoV-2 at the end of the first wave (April 26 to June 28, 2020), but not in the second wave (from the end of August to Nov 1, 2020). Age (young adults, particularly those aged 17–24 years) was an important initial driver of increased positivity rates in the second wave. For example, the estimated percentage of individuals testing positive was more than six times higher in those aged 17–24 years than in those aged 70 years or older at the end of September, 2020. A substantial proportion of infections were in individuals not reporting symptoms around their positive test (45–68%, dependent on calendar time. Interpretation: Important risk factors for testing positive for SARS-CoV-2 varied substantially between the part of the first wave that was captured by the study (April to June, 2020) and the first part of the second wave of increased positivity rates (end of August to Nov 1, 2020), and a substantial proportion of infections were in individuals not reporting symptoms, indicating that continued monitoring for SARS-CoV-2 in the community will be important for managing the COVID-19 pandemic moving forwards

Prozac Leadership and the limits of positive thinking

This article critically examines excessive positivity in leadership dynamics. It argues that the tendency for leader positivity to become excessive is a recurrent but under-researched medium through which power and identity can be enacted in leadership dynamics. Drawing on the metaphor of ‘Prozac’, it suggests that leaders’ excessive positivity is often characterized by a reluctance to consider alternative voices, which can leave organizations and societies ill-prepared to deal with unexpected events. Prozac leadership encourages leaders to believe their own narratives that everything is going well and discourages followers from raising problems or admitting mistakes. The article also argues that followers (broadly defined) are often quick to identify leaders’ excessive positivity and are likely to respond through various forms of resistance. It concludes by considering the extent to which excessive positivity also characterizes leadership studies, and raises additional questions for further critical analyses of Prozac leadership

Relationship Between Total and Bioaccessible Lead on Children’s Blood Lead Levels in Urban Residential Philadelphia Soils

Relationships between total soil or bioaccessible lead (Pb), measured using an in vitro bioaccessibility assay, and children’s blood lead levels (BLL) were investigated in an urban neighborhood in Philadelphia, PA, with a history of soil Pb contamination. Soil samples from 38 homes were analyzed to determine whether accounting for the bioaccessible Pb fraction improves statistical relationships with children’s BLLs. Total soil Pb concentration ranged from 58 to 2821 mg/kg; the bioaccessible Pb concentration ranged from 47 to 2567 mg/kg. Children’s BLLs ranged from 0.3 to 9.8 μg/dL. Hierarchical models were used to compare relationships between total or bioaccessible Pb in soil and children’s BLLs. Total soil Pb concentration as the predictor accounted for 23% of the variability in child BLL; bioaccessible soil Pb concentration as the predictor accounted for 26% of BLL variability. A bootstrapping analysis confirmed a significant increase in <i>R</i>² for the model using bioaccessible soil Pb concentration as the predictor with 99.0% of bootstraps showing a positive increase. Estimated increases of 1.3 μg/dL and 1.5 μg/dL in BLL per 1000 mg/kg Pb in soil were observed for this study area using total and bioaccessible Pb concentrations, respectively. Children’s age did not contribute significantly to the prediction of BLLs