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Due to shortages of N95 respirators during the coronavirus disease 2019 (COVID-19) pandemic, it is necessary to estimate the number of N95s required for healthcare workers (HCWs) to inform manufacturing targets and resource allocation.
We developed a model to determine the number of N95 respirators needed for HCWs both in a single acute-care hospital and the United States.
For an acute-care hospital with 400 all-cause monthly admissions, the number of N95 respirators needed to manage COVID-19 patients admitted during a month ranges from 113 (95% interpercentile range [IPR], 50–229) if 0.5% of admissions are COVID-19 patients to 22,101 (95% IPR, 5,904–25,881) if 100% of admissions are COVID-19 patients (assuming single use per respirator, and 10 encounters between HCWs and each COVID-19 patient per day). The number of N95s needed decreases to a range of 22 (95% IPR, 10–43) to 4,445 (95% IPR, 1,975–8,684) if each N95 is used for 5 patient encounters. Varying monthly all-cause admissions to 2,000 requires 6,645–13,404 respirators with a 60% COVID-19 admission prevalence, 10 HCW–patient encounters, and reusing N95s 5–10 times. Nationally, the number of N95 respirators needed over the course of the pandemic ranges from 86 million (95% IPR, 37.1–200.6 million) to 1.6 billion (95% IPR, 0.7–3.6 billion) as 5%–90% of the population is exposed (single-use). This number ranges from 17.4 million (95% IPR, 7.3–41 million) to 312.3 million (95% IPR, 131.5–737.3 million) using each respirator for 5 encounters.
We quantified the number of N95 respirators needed for a given acute-care hospital and nationally during the COVID-19 pandemic under varying conditions.
Studies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds.
We examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes.
In COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47–0.68%, p = 2.0 × 10−8–1.0 × 10−10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10−8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10−6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10−11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10−7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10−16).
AUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.
Collaborative quality improvement and learning networks have amended healthcare quality and value across specialities. Motivated by these successes, the Pediatric Acute Care Cardiology Collaborative (PAC3) was founded in late 2014 with an emphasis on improving outcomes of paediatric cardiology patients within cardiac acute care units; acute care encompasses all hospital-based inpatient non-intensive care. PAC3 aims to deliver higher quality and greater value care by facilitating the sharing of ideas and building alignment among its member institutions. These aims are intentionally aligned with the work of other national clinical collaborations, registries, and parent advocacy organisations. The mission and early work of PAC3 is exemplified by the formal partnership with the Pediatric Cardiac Critical Care Consortium (PC4), as well as the creation of a clinical registry, which links with the PC4 registry to track practices and outcomes across the entire inpatient encounter from admission to discharge. Capturing the full inpatient experience allows detection of outcome differences related to variation in care delivered outside the cardiac ICU and development of benchmarks for cardiac acute care. We aspire to improve patient outcomes such as morbidity, hospital length of stay, and re-admission rates, while working to advance patient and family satisfaction. We will use quality improvement methodologies consistent with the Model for Improvement to achieve these aims. Membership currently includes 36 centres across North America, out of which 26 are also members of PC4. In this report, we describe the development of PAC3, including the philosophical, organisational, and infrastructural elements that will enable a paediatric acute care cardiology learning network.
Although computation and the science of physical systems would appear to be unrelated, there are a number of ways in which computational and physical concepts can be brought together in ways that illuminate both. This volume examines fundamental questions which connect scholars from both disciplines: is the universe a computer? Can a universal computing machine simulate every physical process? What is the source of the computational power of quantum computers? Are computational approaches to solving physical problems and paradoxes always fruitful? Contributors from multiple perspectives reflecting the diversity of thought regarding these interconnections address many of the most important developments and debates within this exciting area of research. Both a reference to the state of the art and a valuable and accessible entry to interdisciplinary work, the volume will interest researchers and students working in physics, computer science, and philosophy of science and mathematics.
In this introductory chapter, we summarize each of this volume's parts and the particular contributions that fall under them: I) the computability of physical systems and physical systems as computers, II) the implementation of computation in physical systems, III) physical perspectives on computer science, and IV) computational perspectives on physical theory. Before we do so, however, we review some of the basic concepts which will generally be taken for granted in the rest of the book, including those from: I) computability theory, Turing machines, and the Church-Turing thesis, II) computational complexity theory, III) quantum computing, IV) theories of computational implementation and the variety of “physical” Church-Turing theses, and V) Landauer's principle and the thermodynamics of computation.