18 research outputs found
#595 Communist China Today.
No full textParticipants include: Dr. Peter S.H. Tang, Author of Communist China Today, Lecturer in International Relations, Georgetown University Dr. Paul M.A. Linebarger, School of Advanced International Studies, John Hopkins University Hon. Stanley K. Hornbeck, Diplomat and Autho
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American Sandwich: West Coast, East Coast, in Between
No full textThe thesis begins with an introduction, followed by six short stories. The stories that follow span three or four regions of the American landscape and three or four decades of the twentieth century. What drives each story is the isolation of both narrator and main character (when these are not the same) from the world of the story. In each story, there is either a sense of wanting to belong or an urge to escape, or both. The paradox--also the writer's paradox--is that if one belongs, one has no need to escape; if one escapes, one can never belong
Bugle rhymes from France /
No full text"And the ship players' comedy by the same author, This side of France."Mode of access: Internet
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Will Made Word and Other Conceptions
No full textThis thesis consists of a series of nine poems which deal with the theme of finding a balance between energy and form in life and in poetry. Fourteen miscellaneous poems are also included. In addition, an introduction by the author explains the purpose of the thesis as a whole and explicates the poems in terms of this purpose. The introduction discusses the meaning of each poem and the techniques used to convey its message. Each poem in the series of nine poems is also related to the. overall theme of the series
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Joyce's Dubliners and Hemingway's In Our Time: A Correlation
No full textOne rarely sees the names James Joyce and Ernest Hemingway together in the same sentence. Their obvious differences in writing styles, nationalities, and lifestyles prevent any automatic comparison from being made. But when one compares their early short story collections, Dubliners and In Our Time, many surprisingly similarities appear. Both are collections of short stories unified in some way, written by expatriates who knew each other in Paris. A mood of despair and hopelessness pervades the stories as the characters are trapped in the human condition. By examining the commonalities found in their methods of organization, handling of point of view, attitudes toward their subjects, stylistic techniques, and modes of writing, one is continually brought back to the differences between Joyce and Hemingway in each of these areas. For it is their differences that make these artists important; how each author chose to develop his craft gives him a significant place in literature
Reduced polynomial order linear prediction
No full textReduced rank linear predictive frequency and direction-of-arrival (DOA) estimation algorithms use the singular value decomposition (SVD) to produce a noise-cleaned linear prediction vector. These algorithms then root this vector to obtain a subset of roots, whose angles contain the desired frequency or DOA information. The roots closest to the unit circle are deemed to be the "signal roots." The rest of the roots are "extraneous." The extraneous roots are expensive to calculate. Further, a search must be done to discern the signal roots from the extraneous roots. Here, we present a reduced polynomial order linear prediction method that simplifies the rooting computation for applications where high-speed processing is critical.This work was supported, in part, by the National Science Foundation Grant MIP-9203296 and the Texas Advanced Research Program Grant 009741-022
87th Legislature of Texas
No full textReport from the Sunset Commission regarding the Texas Department of Licensing and Regulation, including decisions on statutory recommendations for the Texas Legislature and management recommendations for the agency, as well as information from the original staff report, such as the need for, performance by, and improvements to the Texas Department of Licensing and Regulation
ihmeuw/covid-shared: v2.2.0
No full textWhat's Changed
Collijk/feature/parallel tools by @collijk in https://github.com/ihmeuw/covid-shared/pull/136
Develop by @collijk in https://github.com/ihmeuw/covid-shared/pull/137
Full Changelog: https://github.com/ihmeuw/covid-shared/compare/v2.1.1...v2.2.
Estimating global, regional, and national daily and cumulative infections with SARS-CoV-2 through Nov 14, 2021: a statistical analysis
No full textBackground: timely, accurate, and comprehensive estimates of SARS-CoV-2 daily infection rates, cumulative infections, the proportion of the population that has been infected at least once, and the effective reproductive number (Reffective) are essential for understanding the determinants of past infection, current transmission patterns, and a population's susceptibility to future infection with the same variant. Although several studies have estimated cumulative SARS-CoV-2 infections in select locations at specific points in time, all of these analyses have relied on biased data inputs that were not adequately corrected for. In this study, we aimed to provide a novel approach to estimating past SARS-CoV-2 daily infections, cumulative infections, and the proportion of the population infected, for 190 countries and territories from the start of the pandemic to Nov 14, 2021. This approach combines data from reported cases, reported deaths, excess deaths attributable to COVID-19, hospitalisations, and seroprevalence surveys to produce more robust estimates that minimise constituent biases. Methods: we produced a comprehensive set of global and location-specific estimates of daily and cumulative SARS-CoV-2 infections through Nov 14, 2021, using data largely from Johns Hopkins University (Baltimore, MD, USA) and national databases for reported cases, hospital admissions, and reported deaths, as well as seroprevalence surveys identified through previous reviews, SeroTracker, and governmental organisations. We corrected these data for known biases such as lags in reporting, accounted for under-reporting of deaths by use of a statistical model of the proportion of excess mortality attributable to SARS-CoV-2, and adjusted seroprevalence surveys for waning antibody sensitivity, vaccinations, and reinfection from SARS-CoV-2 escape variants. We then created an empirical database of infection–detection ratios (IDRs), infection–hospitalisation ratios (IHRs), and infection–fatality ratios (IFRs). To estimate a complete time series for each location, we developed statistical models to predict the IDR, IHR, and IFR by location and day, testing a set of predictors justified through published systematic reviews. Next, we combined three series of estimates of daily infections (cases divided by IDR, hospitalisations divided by IHR, and deaths divided by IFR), into a more robust estimate of daily infections. We then used daily infections to estimate cumulative infections and the cumulative proportion of the population with one or more infections, and we then calculated posterior estimates of cumulative IDR, IHR, and IFR using cumulative infections and the corrected data on reported cases, hospitalisations, and deaths. Finally, we converted daily infections into a historical time series of Reffective by location and day based on assumptions of duration from infection to infectiousness and time an individual spent being infectious. For each of these quantities, we estimated a distribution based on an ensemble framework that captured uncertainty in data sources, model design, and parameter assumptions. Findings: global daily SARS-CoV-2 infections fluctuated between 3 million and 17 million new infections per day between April, 2020, and October, 2021, peaking in mid-April, 2021, primarily as a result of surges in India. Between the start of the pandemic and Nov 14, 2021, there were an estimated 3·80 billion (95% uncertainty interval 3·44–4·08) total SARS-CoV-2 infections and reinfections combined, and an estimated 3·39 billion (3·08–3·63) individuals, or 43·9% (39·9–46·9) of the global population, had been infected one or more times. 1·34 billion (1·20–1·49) of these infections occurred in south Asia, the highest among the seven super-regions, although the sub-Saharan Africa super-region had the highest infection rate (79·3 per 100 population [69·0–86·4]). The high-income super-region had the fewest infections (239 million [226–252]), and southeast Asia, east Asia, and Oceania had the lowest infection rate (13·0 per 100 population [8·4–17·7]). The cumulative proportion of the population ever infected varied greatly between countries and territories, with rates higher than 70% in 40 countries and lower than 20% in 39 countries. There was no discernible relationship between Reffective and total immunity, and even at total immunity levels of 80%, we observed no indication of an abrupt drop in Reffective, indicating that there is not a clear herd immunity threshold observed in the data.Interpretation: COVID-19 has already had a staggering impact on the world up to the beginning of the omicron (B.1.1.529) wave, with over 40% of the global population infected at least once by Nov 14, 2021. The vast differences in cumulative proportion of the population infected across locations could help policy makers identify the transmission-prevention strategies that have been most effective, as well as the populations at greatest risk for future infection. This information might also be useful for targeted transmission-prevention interventions, including vaccine prioritisation. Our statistical approach to estimating SARS-CoV-2 infection allows estimates to be updated and disseminated rapidly on the basis of newly available data, which has and will be crucially important for timely COVID-19 research, science, and policy responses. Funding: Bill & Melinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom
Pandemic preparedness and COVID-19: an exploratory analysis of infection and fatality rates, and contextual factors associated with preparedness in 177 countries, from Jan 1, 2020, to Sept 30, 2021
No full textNational rates of COVID-19 infection and fatality have varied dramatically since the onset of the pandemic. Understanding the conditions associated with this cross-country variation is essential to guiding investment in more effective preparedness and response for future pandemics.
Daily SARS-CoV-2 infections and COVID-19 deaths for 177 countries and territories and 181 subnational locations were extracted from the Institute for Health Metrics and Evaluation's modelling database. Cumulative infection rate and infection-fatality ratio (IFR) were estimated and standardised for environmental, demographic, biological, and economic factors. For infections, we included factors associated with environmental seasonality (measured as the relative risk of pneumonia), population density, gross domestic product (GDP) per capita, proportion of the population living below 100 m, and a proxy for previous exposure to other betacoronaviruses. For IFR, factors were age distribution of the population, mean body-mass index (BMI), exposure to air pollution, smoking rates, the proxy for previous exposure to other betacoronaviruses, population density, age-standardised prevalence of chronic obstructive pulmonary disease and cancer, and GDP per capita. These were standardised using indirect age standardisation and multivariate linear models. Standardised national cumulative infection rates and IFRs were tested for associations with 12 pandemic preparedness indices, seven health-care capacity indicators, and ten other demographic, social, and political conditions using linear regression. To investigate pathways by which important factors might affect infections with SARS-CoV-2, we also assessed the relationship between interpersonal and governmental trust and corruption and changes in mobility patterns and COVID-19 vaccination rates.
The factors that explained the most variation in cumulative rates of SARS-CoV-2 infection between Jan 1, 2020, and Sept 30, 2021, included the proportion of the population living below 100 m (5·4% [4·0–7·9] of variation), GDP per capita (4·2% [1·8–6·6] of variation), and the proportion of infections attributable to seasonality (2·1% [95% uncertainty interval 1·7–2·7] of variation). Most cross-country variation in cumulative infection rates could not be explained. The factors that explained the most variation in COVID-19 IFR over the same period were the age profile of the country (46·7% [18·4–67·6] of variation), GDP per capita (3·1% [0·3–8·6] of variation), and national mean BMI (1·1% [0·2–2·6] of variation). 44·4% (29·2–61·7) of cross-national variation in IFR could not be explained. Pandemic-preparedness indices, which aim to measure health security capacity, were not meaningfully associated with standardised infection rates or IFRs. Measures of trust in the government and interpersonal trust, as well as less government corruption, had larger, statistically significant associations with lower standardised infection rates. High levels of government and interpersonal trust, as well as less government corruption, were also associated with higher COVID-19 vaccine coverage among middle-income and high-income countries where vaccine availability was more widespread, and lower corruption was associated with greater reductions in mobility. If these modelled associations were to be causal, an increase in trust of governments such that all countries had societies that attained at least the amount of trust in government or interpersonal trust measured in Denmark, which is in the 75th percentile across these spectrums, might have reduced global infections by 12·9% (5·7–17·8) for government trust and 40·3% (24·3–51·4) for interpersonal trust. Similarly, if all countries had a national BMI equal to or less than that of the 25th percentile, our analysis suggests global standardised IFR would be reduced by 11·1%.
Efforts to improve pandemic preparedness and response for the next pandemic might benefit from greater investment in risk communication and community engagement strategies to boost the confidence that individuals have in public health guidance. Our results suggest that increasing health promotion for key modifiable risks is associated with a reduction of fatalities in such a scenario
