Daily briefing: Huge data set reveals COVID-19’s unequal toll in the United States

Nature ◽  
2020 ◽  
Author(s):  
Flora Graham
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Richard Johnston ◽  
Xiaohan Yan ◽  
Tatiana M. Anderson ◽  
Edwin A. Mitchell

AbstractThe effect of altitude on the risk of sudden infant death syndrome (SIDS) has been reported previously, but with conflicting findings. We aimed to examine whether the risk of sudden unexpected infant death (SUID) varies with altitude in the United States. Data from the Centers for Disease Control and Prevention (CDC)’s Cohort Linked Birth/Infant Death Data Set for births between 2005 and 2010 were examined. County of birth was used to estimate altitude. Logistic regression and Generalized Additive Model (GAM) were used, adjusting for year, mother’s race, Hispanic origin, marital status, age, education and smoking, father’s age and race, number of prenatal visits, plurality, live birth order, and infant’s sex, birthweight and gestation. There were 25,305,778 live births over the 6-year study period. The total number of deaths from SUID in this period were 23,673 (rate = 0.94/1000 live births). In the logistic regression model there was a small, but statistically significant, increased risk of SUID associated with birth at > 8000 feet compared with < 6000 feet (aOR = 1.93; 95% CI 1.00–3.71). The GAM showed a similar increased risk over 8000 feet, but this was not statistically significant. Only 9245 (0.037%) of mothers gave birth at > 8000 feet during the study period and 10 deaths (0.042%) were attributed to SUID. The number of SUID deaths at this altitude in the United States is very small (10 deaths in 6 years).


2014 ◽  
Vol 7 (5) ◽  
pp. 2477-2484 ◽  
Author(s):  
J. C. Kathilankal ◽  
T. L. O'Halloran ◽  
A. Schmidt ◽  
C. V. Hanson ◽  
B. E. Law

Abstract. A semi-parametric PAR diffuse radiation model was developed using commonly measured climatic variables from 108 site-years of data from 17 AmeriFlux sites. The model has a logistic form and improves upon previous efforts using a larger data set and physically viable climate variables as predictors, including relative humidity, clearness index, surface albedo and solar elevation angle. Model performance was evaluated by comparison with a simple cubic polynomial model developed for the PAR spectral range. The logistic model outperformed the polynomial model with an improved coefficient of determination and slope relative to measured data (logistic: R2 = 0.76; slope = 0.76; cubic: R2 = 0.73; slope = 0.72), making this the most robust PAR-partitioning model for the United States currently available.


2021 ◽  
pp. 215336872110389
Author(s):  
Andrew J. Baranauskas

In the effort to prevent school shootings in the United States, policies that aim to arm teachers with guns have received considerable attention. Recent research on public support for these policies finds that African Americans are substantially less likely to support them, indicating that support for arming teachers is a racial issue. Given the racialized nature of support for punitive crime policies in the United States, it is possible that racial sentiment shapes support for arming teachers as well. This study aims to determine the association between two types of racial sentiment—explicit negative feelings toward racial/ethnic minority groups and racial resentment—and support for arming teachers using a nationally representative data set. While explicit negative feelings toward African Americans and Hispanics are not associated with support for arming teachers, those with racial resentments are significantly more likely to support arming teachers. Racial resentment also weakens the effect of other variables found to be associated with support for arming teachers, including conservative ideology and economic pessimism. Implications for policy and research are discussed.


2021 ◽  
Author(s):  
Marni Mack ◽  
Argo Easston

In the United States, sepsis, the body's response to infection in a typically sterile circulation, is a leading causeof death (1). To assess the primary transcriptional alterations associated with each illness state, I utilized amicroarray data set from a cohort of thirtyone individuals with septic shock or systemic inflammatory responsesyndrome (2). At the transcriptional level, I discovered that the granulocytes of patients with SIRS weresimilar to those of patients with septic shock. SIRS showed a “intermediate” gene expression state betweenthat of control patients and that of septic shock patients for numerous genes expressed in the granulocyte. Thediscovery of the most differentially expressed genes in the granulocytic immune cells of patients with septicshock might aid the development of new therapies or diagnostics for an illness with a 14.7 percent to 29.9% inhospitaldeath rate despite decades of study (1).


Author(s):  
John S. Lapinski

This chapter introduces a new measure of legislative accomplishment. To understand lawmaking requires that one move beyond studying political behavior in Congress alone and beyond a complete empirical reliance on roll call votes. Moreover, legislative behavior and legislative outputs must be studied in tandem to gain a proper understanding of the lawmaking process in the United States. Although the idea of studying important lawmaking across time is not controversial, constructing an appropriate measure is not a trivial exercise. The chapter constructs a comprehensive lawmaking data set that provides measures of legislative accomplishment at the aggregate level as well as by specific policy issue areas for a 118-year period. It also explains the construction of Congress-by-Congress measures of legislative accomplishment, including measures broken down by the policy-coding schema.


Author(s):  
Sonia Gantman ◽  
Lorrie Metzger

We present a data cleaning project that utilizes real vendor master data of a large public university in the United States. Our main objective when developing this case was to identify the areas where students need guidance in order to apply a problem solving approach to the project. This includes initial analysis of the data and the task at hand, planning for cleaning and testing activities, executing this plan, and communicating the results in a written report. We provide a data set with 29K records of vendor master data, and a subset of the same data with 800 records. The assignment has two parts - the planning and the actual cleaning, each with its own deliverable. It can be used in many different courses and completed with almost any data analytics software. We provide suggested solutions and detailed solution notes for Excel and for Alteryx Designer.


Author(s):  
Claire Annesley ◽  
Karen Beckwith ◽  
Susan Franceschet

Chapter 7 shows that aspirant ministers can qualify for cabinet appointment by meeting representational criteria, defined as membership in a politically relevant political, territorial, or socio-demographic group deemed important for legitimizing the cabinet team. In all country cases, a subset of ministrables qualify for appointment to cabinet on the basis of representational criteria, and all countries in the book’s data set employ representational criteria in defining the ministerial eligibility pool, even as specific representational criteria vary in number and content across cases. The chapter shows that regional representation is a strong prescriptive criterion in five countries (Australia, Canada, Germany, Spain, and the United Kingdom), and that race and ethnicity are prescribed as representational categories in Canada and the United States. The chapter finds that gender is the only representational category that appears across all countries, yet the magnitude of women’s inclusion varies significantly.


Author(s):  
Johannes Bubeck ◽  
Kai Jäger ◽  
Nikolay Marinov ◽  
Federico Nanni

Abstract Why do states intervene in elections abroad? This article argues that outsiders intervene when the main domestic contenders for office adopt policy positions that differ from the point of view of the outside power. It refers to the split between the government's and opposition's positions as policy polarization. Polarization between domestic political forces, rather than the degree of unfriendliness of the government in office, attracts two types of interventions: process (for or against democracy) and candidate (for or against the government) interventions. The study uses a novel, original data set to track local contenders’ policy positions. It shows that the new policy polarization measurement outperforms a number of available alternatives when it comes to explaining process and candidate interventions. The authors use this measurement to explain the behavior of the United States as an intervener in elections from 1945 to 2012. The United States is more likely to support the opposition, and the democratic process abroad, if a pro-US opposition is facing an anti-US government. It is more likely to support the government, and undermine the democratic process abroad, if a pro-US government is facing an anti-US opposition. The article also presents the results for all interveners, confirming the results from the US case.


2007 ◽  
Vol 2 (3) ◽  
pp. 94
Author(s):  
Stephanie Hall

Objective – To determine the effect of large bookstores (defined as those having 20 or more employees) on household library use. Design – Econometric analysis using cross-sectional data sets. Setting – The United States of America. Subjects – People in over 55,000 households across the U.S.A. Methods – Data from 3 1996 studies were examined using logit and multinomial logit estimation procedures: the National Center for Education Statistics’ National Household Education Survey (NHES) and Public Library Survey (PLS), and the U.S. Census Bureau’s County Business Patterns (CBP). The county level results of the NHES telephone survey were merged with the county level data from the PLS and the CBP. Additionally, data on Internet use at the state level from the Statistical Abstract of the United States were incorporated into the data set. A logit regression model was used to estimate probability of library use based on several independent variables, evaluated at the mean. Main results – In general, Hemmeter found that "with regard to the impact of large bookstores on household library use, large bookstores do not appear to have an effect on overall library use among the general population” (613). While no significant changes in general library use were found among high and low income households where more large bookstores were present, nor in the population taken as a whole, middle income households (between $25,000 and $50,000 in annual income) showed notable declines in library use in these situations. These effects were strongest in the areas of borrowing (200% less likely) and recreational purposes (161%), but were also present in work-related use and job searching. Hemmeter also writes that “poorer households use the library more often for job search purposes. The probability of library use for recreation, work, and consumer information increases as income increases. This effect diminishes as households get richer” (611). Finally, home ownership was also correlated with higher library use. Households with children were more than 20% more likely to use the library (610). Their use of the library for school-related purposes, general borrowing, program activities, and so on was not affected by the presence of book superstores. White families with children were somewhat less likely to use the library, while families with higher earning and education levels were more likely to use the library. Library use also increased with the number of children in the family. Shorter distances to the nearest branch and a higher proportion of AV materials were also predictive of higher library use. Educational level was another important factor, with those having less than high school completion being significantly less likely to use the library than those with higher levels of educational attainment. Conclusions – The notable decline in public library use among middle income households where more large bookstores are present is seen as an important threat to libraries, as it may result in a decline in general support and support for funding among an important voting block. More current data are needed in this area. In addition to the type of information examined in this study, the author recommends the inclusion of information on funding, support for library referenda, and library quality as they relate to the presence of large bookstores.


2020 ◽  
pp. 019874292096135
Author(s):  
Nicholas A. Gage ◽  
Antonis Katsiyannis ◽  
Kelly M. Carrero ◽  
Rhonda Miller ◽  
Danielle Pico

The Latinx population is the largest group of racially and ethnically diverse students in the United States. Although disproportionality in school discipline has been documented for Latinx students, findings related to such disparities have been inconsistent. We examined disciplinary exclusion practices involving students with and without disabilities who are Latinx across the United States using risk ratios (RR) and weighted mixed-effect models. We leveraged data from the Civil Rights Data Collection (CRDC) data set for the 2015 to 2016 academic school year, which included data from more than 94,000 schools. The CRDC is collected by the U.S. Department of Education’s Office of Civil Rights every 2 years. All U.S. public schools are required to submit data to the CRDC. Results suggest that Latinx students with and without disabilities were statistically significantly more likely to receive exclusionary discipline than White students, but less likely than Black students. Implications for research and practice are provided.


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