Epidemiology and Medical statistics Books

Book SynopsisGenetic epidemiology is a very rapidly developing field that has acquired a central role in modern biomedical science. Until now there has been no comprehensive introductory text for students and academics who do not have specialised training in statistics or genetics. This book begins with a primer in human molecular genetics and then examines standard methods in population genetics and genetic epidemiology required for an adequate grounding in the field. Among much else, the book contains discussion of the public health aspects of the new genetics, and of epidemiological methods for studying genes and environmental factors in complex diseases. Written by leading international experts and supplemented by a glossary and in-chapter guides to further reading, this essential textbook will be widely welcomed by teachers and students on many courses internationally.Trade Review"A very interesting and understandable, yet quite detailed, account of techniques used in a rapidly advancing field." 5* review on Amazon.co.uk"This is a sobering must-read for anyone who wishes to know how genetic epidemiology may change how we understand, treat or prevent human disease." Robert Elston, Case Western Reserve University School of Medicine"This book should be incredibly useful to students and researchers at all levels in genetic epidemiology. For students it offers an eminently readable and accessible foundation, and for researchers, a superb source to fill in missing pieces in our knowledge." Ezra Susser, Professor of Epidemiology and Psychiatry, Mailman School of Public Health, Columbia University, and New York State Psychiatric InstituteTable of ContentsKey concepts in genetic epidemiology ~ Paul R Burton, Martin D Tobin and John L Hopper; Genetic linkage studies ~ M Dawn Teare and Jennifer H. Barrett; Genetic association studies ~ Heather J. Cordell and David G. Clayton; Mapping complex disease genes using linkage disequilibrium and genome-wide association scans ~ Lyle J Palmer, Nicholas J Timpson, David M Evans, George Davey Smith and Lon R Cardon; A question of standards: what makes a good genetic association study? ~ Andrew T Hattersley and Mark I McCarthy; Biobanks and biobank harmonisation ~ Paul R Burton, Isabel Fortier, Mylene Deschênes, Anna Hansell and Lyle J Palmer; Population health aspects of genetic epidemiology: genomic profiling, personalised medicine, and Mendelian randomisation ~ George Davey Smith, Shah Ebrahim, Sarah Lewis and Lyle J Palmer.

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Book SynopsisGenetic epidemiology is a very rapidly developing field that has acquired a central role in modern biomedical science. Until now there has been no comprehensive introductory text for students and academics who do not have specialised training in statistics or genetics. This book begins with a primer in human molecular genetics and then examines standard methods in population genetics and genetic epidemiology required for an adequate grounding in the field. Among much else, the book contains discussion of the public health aspects of the new genetics, and of epidemiological methods for studying genes and environmental factors in complex diseases. Written by leading international experts and supplemented by a glossary and in-chapter guides to further reading, this essential textbook will be widely welcomed by teachers and students on many courses internationally.Trade Review"A very interesting and understandable, yet quite detailed, account of techniques used in a rapidly advancing field." 5* review on Amazon.co.uk"This is a sobering must-read for anyone who wishes to know how genetic epidemiology may change how we understand, treat or prevent human disease." Robert Elston, Case Western Reserve University School of Medicine"This book should be incredibly useful to students and researchers at all levels in genetic epidemiology. For students it offers an eminently readable and accessible foundation, and for researchers, a superb source to fill in missing pieces in our knowledge." Ezra Susser, Professor of Epidemiology and Psychiatry, Mailman School of Public Health, Columbia University, and New York State Psychiatric InstituteTable of ContentsKey concepts in genetic epidemiology ~ Paul R Burton, Martin D Tobin and John L Hopper; Genetic linkage studies ~ M Dawn Teare and Jennifer H. Barrett; Genetic association studies ~ Heather J. Cordell and David G. Clayton; Mapping complex disease genes using linkage disequilibrium and genome-wide association scans ~ Lyle J Palmer, Nicholas J Timpson, David M Evans, George Davey Smith and Lon R Cardon; A question of standards: what makes a good genetic association study? ~ Andrew T Hattersley and Mark I McCarthy; Biobanks and biobank harmonisation ~ Paul R Burton, Isabel Fortier, Mylene Deschênes, Anna Hansell and Lyle J Palmer; Population health aspects of genetic epidemiology: genomic profiling, personalised medicine, and Mendelian randomisation ~ George Davey Smith, Shah Ebrahim, Sarah Lewis and Lyle J Palmer.

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Book SynopsisThis authoritative work, now in its fourth edition, presents state of the art knowledge on all key aspects of cancer prevention. In addition to detailed summaries on preventive strategies for specific cancers, readers will find current knowledge on a range of relevant scientific topics including the benefits of cancer prevention, the importance of diet and physical activity, innate and adaptive immune responses to cancer, hereditary risks, cancer health disparities, and the preventive role of telemedicine. In this new edition of the book, the coverage has been expanded to include additional disease sites and to provide up-to-date information across the range of disciplines in the field of cancer prevention and control. Written as a collaborative work by internationally recognized leaders in the field, Fundamentals of Cancer Prevention is an essential reference guide and tool for oncologists, primary care physicians, the research community, and students with an interest in reducing the burden of cancer through the implementation of effective preventive strategies.Table of ContentsIntroduction to Cancer Prevention.- Assessing the Humanistic Benefits of Cancer Prevention.- Assessing the Economic Outcomes of Cancer Prevention.- The Role of Diet, Physical Activity, and Body Composition in Cancer Prevention.- Innate and Adaptive Immune Responses to Cancer.- Hereditary Risk for cancer.- Cancer Health Disparities.- Human Categories and Health the power of the concept of ethnicity.- Complementary and alternative approaches to cancer prevention.- Telemedicine, Telehealth, and eHealth technologies in cancer prevention.- Global Cancer Prevention.- Topical skin protection against solar insult molecular mechanisms and opportunities.- Skin Cancer Prevention.- Colorectal Cancer Prevention.- Lung Cancer Prevention.- Breast Cancer Prevention.- Prostate Cancer Prevention.- Cervical Cancer Prevention.- Endometrial cancer Prevention.- Ovarian Cancer Prevention.- Cancer Survivorship.

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Book SynopsisThis 3rd edition of a classic textbook examines the context and background of public health informatics, explores the technology and science underlying the field, discusses challenges and emerging solutions, reviews many key public health information systems, and includes practical, case-based studies to guide the reader through the topic. The editors have expanded the text into new areas that have become important since publication of the previous two editions due to changing technologies and needs in the field, as well as updating and augmenting much of the core content. The book contains learning objectives, overviews, future directions, and review questions to assist readers to engage with this vast topic. The Editors and their team of well-known contributors have built upon the foundation established by the previous editions to provide the reader with a comprehensive and forward-looking review of public health informatics.The breadth of material in Public Health Informatics and Information Systems, 3rd edition makes it suitable for both undergraduate and graduate coursework in public health informatics, enabling instructors to select chapters that best fit their students’ needs.Table of ContentsPublic Health Informatics: an Introduction.- History of Public Health Information Systems and Informatics.- Public Health Informatics in the Larger Context of Biomedical and Health Informatics.- Governmental and Legislative Context for Informatics.- Role of Informatics in Bridging Public and Population Health.- Information Infrastructure to Support Public Health.- Data Sources and Data Tools: Preparing for the Open Data Ecosystem.- Public Health Information Standards.- Privacy and Confidentiality of Public Health Information.- Health Systems Security.- Electronic Health Records: Origination, Adoption, and Progression.- Public Health Analytics and Big Data.- Project Management and Public Health Informatics.- Informatics in Disease Prevention and Epidemiology.- Public Health Laboratories.- The US National Vital Statistics System.- Syndromic Surveillance – a Practical Application of Informatics.- New Means of Data Collection and Accessibility.- Interoperability and Health Information Exchange for Public Health.- Geographic Information Systems.- Public Health Decision Support Systems.- Local and Regional Public Health Informatics.- Public Health Informatics and the American Indian/Alaska Native Populations: Improving Community Health Despite Challenges.- Advancing Informatics Policy and Practice: A State Perspective.- National Public Health Informatics, United States.- Perspectives on Global Public Health Informatics.- Improving immunization through informatics: Perspectives from the BID Initiative Partnership with Tanzania and Zambia.- Public Health Informatics: the Path Forward.

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Book SynopsisThis unique and comprehensive title offers state-of-the-art guidance on all of the clinical principles and practices needed in providing optimal health and well-being services for college students. Designed for college health professionals and administrators, this highly practical title is comprised of 24 chapters organized in three sections: Common Clinical Problems in College Health, Organizational and Administrative Considerations for College Health, and Population and Public Health Management on a College Campus. Section I topics include travel health services, tuberculosis, eating disorders in college health, and attention deficit hyperactivity disorder among college students, along with several other chapters. Subsequent chapters in Section II then delve into topics such as supporting the health and well-being of a diverse student population, student veterans, health science students, student safety in the clinical setting, and campus management of infectious disease outbreaks, among other topics. The book concludes with organizational considerations such as unique issues in the practice of medicine in the institutional context, situating healthcare within the broader context of wellness on campus, organizational structures of student health, funding student health services, and delivery of innovative healthcare services in college health. Developed by a renowned, multidisciplinary authorship of leaders in college health theory and practice, and coinciding with the founding of the American College Health Association 100 years ago, Principles and Practice of College Health will be of great interest to college health and well-being professionals as well as college administrators.Table of ContentsSection I. Common Clinical Problems in College Health Chapter 1 Campus Travel Health Services Julie Richards and Gail Rosselot Chapter 2 Tuberculosis Kent W. Bullis Chapter 3 Eating Disorders in College Health Melanie Trost Chapter 4 Depression and Anxiety in College Students Ayesha K. Chaudhary Chapter 5 Attention Deficit Hyperactivity Disorder and College Students Cara M. Lusby and Scott H. Kollins Chapter 6 Athletic Medicine Jessica Higgs Chapter 7 Concussion Peter Duquette and P. Hunter Spotts Chapter 8 Contraception for College Reproductive Health Camille Moreno Chapter 9 Sexual Health Mary Johnson Section II. Population and Public Health Management on a College Campus Chapter 10 Supporting the Health and Well-Being of a Diverse Student Population Raphael D. Coleman, Katie Wilkinson, Padma Entsuah, Jaclyn M. Hawkins, and Gina Orlando Chapter 11 Student Veterans Amina Moghul Chapter 12 Health Science Students Giang T. Nguyen Chapter 13 Student Safety in the Clinical Setting David McBride Chapter 14 Campus Management of Infectious Disease Outbreaks Melanie J. Bernitz, Michael P. McNeil, and Julie A. Casani Chapter 15 Immunization Compliance Management Heather Spencer Chapter 16 Nutrition Services Franca Alphin and Toni Apadula Chapter 17 Sleep on College and University Campuses Michael P. McNeil and Eric S. Davidson Chapter 18 Substance Use and Abuse: Alcohol, Tobacco, and Other Drugs Alicia K. Czachowski and M. Scott Tims Section III. Organization and Administrative Considerations for College Health Chapter 19 Unique Issues in the Practice of Medicine in the Institutional Context Sarah Van Orman and Alyson Covington Chapter 20 Situating Healthcare Within the Broader Context of Wellness on Campus Julie Edwards Chapter 21 Organizational Structures of Student Health Richard P. Keeling Chapter 22 Funding Student Health Services James R. Jacobs and Leigh S. Stacy Chapter 23 Delivery of Innovative Healthcare Services Brian Halstater Chapter 24 Disability Access in Higher Education: Documenting as University Health Service Providers Grace C. Clifford

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Book SynopsisThis book introduces the open source R software language that can be implemented in biostatistics for data organization, statistical analysis, and graphical presentation. In the years since the authors’ 2014 work Introduction to Data Analysis and Graphical Presentation in Biostatistics with R, the R user community has grown exponentially and the R language has increased in maturity and functionality. This updated volume expands upon skill-sets useful for students and practitioners in the biological sciences by describing how to work with data in an efficient manner, how to engage in meaningful statistical analyses from multiple perspectives, and how to generate high-quality graphics for professional publication of their research. A common theme for research in the diverse biological sciences is that decision-making depends on the empirical use of data. Beginning with a focus on data from a parametric perspective, the authors address topics such as Student t-Tests for independent samples and matched pairs; oneway and twoway analyses of variance; and correlation and linear regression. The authors also demonstrate the importance of a nonparametric perspective for quality assurance through chapters on the Mann-Whitney U Test, Wilcoxon Matched-Pairs Signed-Ranks test, Kruskal-Wallis H-Test for Oneway Analysis of Variance, and the Friedman Twoway Analysis of Variance. To address the element of data presentation, the book also provides an extensive review of the many graphical functions available with R. There are now perhaps more than 15,000 external packages available to the R community. The authors place special emphasis on graphics using the lattice package and the ggplot2 package, as well as less common, but equally useful, figures such as bean plots, strip charts, and violin plots. A robust package of supplementary material, as well as an introduction of the development of both R and the discipline of biostatistics, makes this ideal for novice learners as well as more experienced practitioners.Trade Review“The strengths include the ideal analysis containing both graphical and statistical output as well as a variety of datasets … . the authors provide a number of R packages for obtaining the same results, such as graphics or statistics output. … Each chapter is so complete that it can be read in any order; learned readers will probably jump back and forth between the chapters. This book can be used for self-learning or teaching purpose on the subject.” (Shu-Hui Wen, Biometrics, Vol. 78 (2), July, 2022)Table of Contents1 Introduction: Biostatistics and R.- 1.1 Purpose of this Text.- 1.2 Development of Biostatistics.- 1.3 Development of R.- 1.4 How R is Used in this Text.- 1.5 Import Data into R.- 1.6 Addendum1: Efficient Programming with R, Project Workflow, and Good Programming Practices (gpp).- 1.7 Addendum2: Preview of Descriptive Statistics and Graphics Using R.- 1.8 Addendum3: R and Beautiful Graphics.- 1.9 Addendum4: Research Designs Used in Biostatistics.- 1.10 Prepare to Exit, Save, and Later Retrieve this R Session.- 1.11 External Data and/or Data Resources Used in this Lesson.- 2 Data Exploration, Descriptive Statistics, and Measures of Central Tendency.- 2.1 Background.- 2.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions.- 2.3 Organize the Data and Display the Code Book.- 2.4 Conduct a Visual Data Check Using Graphics (e.g., Figures).- 2.5 Descriptive Statistics for Initial Analysis of the Data.- 2.6 Quality Assurance, Data Distribution, and Tests for Normality.- 2.7 Statistical Test(s).- 2.8 Summary.- 2.9 Addendum1: Specialized External Packages and Functions.- 2.10 Addendum2: Parametric v Nonparametric.- 2.11 Addendum3: Additional Practice Datasets for Data with Normal Distribution Patterns and Data That Do Not Exhibit Normal Distribution Patterns.- 2.12 Prepare to Exit, Save, and Later Retrieve this R Session.- 2.13 External Data and/or Data Resources Used in this Lesson.- 3 Student's t-Test for Independent Samples.- 3.1 Background.- 3.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions.- 3.3 Organize the Data and Display the Code Book.- 3.4 Conduct a Visual Data Check Using Graphics (e.g., Figures).- 3.5 Descriptive Statistics for Initial Analysis of the Data.- 3.6 Quality Assurance, Data Distribution, and Tests for Normality.- 3.7 Statistical Test(s).- 3.8 Summary of Outcomes.- 3.9 Addendum1: t-Statistic v z-Statistic.- 3.10 Addendum2: Parametric v Nonparametric.- 3.11 Addendum3: Additional Practice Datasets for Data with Normal Distribution Patterns and Data That Do Not Exhibit Normal Distribution Patterns.- 3.12 Prepare to Exit, Save, and Later Retrieve This R Session.- 3.13 External Data and/or Data Resources Used in this Lesson.- 4 Student's t-Test for Matched Pairs.- 4.1 Background.- 4.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions.- 4.3 Organize the Data and Display the Code Book.- 4.4 Conduct a Visual Data Check Using Graphics(e.g., Figures).- 4.5 Descriptive Statistics for Initial Analysis of the Data.- 4.6 Quality Assurance, Data Distribution, and Tests for Normality.- 4.7 Statistical Test(s).- 4.8 Summary of Outcomes.- 4.9 Addendum1: R-Based Tools for Unstacked (e.g. Wide) Data.- 4.10 Addendum2: Stacked Data and Student's t-Test for Matched Pairs.- 4.11 Addendum 3: The Impact of N on Student's t-Test.- 4.12 Addendum 4: Parametric v Nonparametric.- 4.13 Addendum5: Additional Practice Datasets for Data with Normal Distribution Patterns and Data That Do Not Exhibit Normal Distribution Patterns.- 4.14 Prepare to Exit, Save, and Later Retrieve This R Session.- 4.15 External Data and/or Data Resources Used in this Lesson.- 5 Oneway Analysis of Variance (ANOVA).- 5.1 Background.- 5.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions.- 5.3 Organize the Data and Display the Code Book.- 5.4 Conduct a Visual Data Check Using Graphics(e.g., Figures).- 5.5 Descriptive Statistics for Initial Analysis of the Data.- 5.6 Quality Assurance, Data Distribution, and Tests for Normality.- 5.7 Statistical Test(s).- 5.8 Summary of Outcomes.- 5.9 Addendum1: Other Packages for Display of Oneway ANOVA.- 5.10 Addendum2: Parametric v Nonparametric.- 5.11 Addendum3: Additional Practice Data Sets.- 5.12 Prepare to Exit, Save, and Later Retrieve This R Session.- 5.13 External Data and/or Data Resources Used in this Lesson.- 6 Twoway Analysis of Variance (ANOVA).- 6.1 Background.- 6.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions.- 6.3 Organize the Data and Display the Code Book.- 6.4 Conduct a Visual Data Check Using Graphics (e.g., Figures).- 6.5 Descriptive Statistics for Initial Analysis of the Data.- 6.6 Quality Assurance, Data Distribution, and Tests for Normality.- 6.7 Statistical Test(s).- 6.8 Summary of Outcomes.- 6.9 Addendum 1: Other Packages for Display of Twoway ANOVA.- 6.10 Addendum 2: Parametric v Nonparametric.- 6.11 Addendum 3: Additional Practice Data Sets.- 6.12 Prepare to Exit, Save, and Later Retrieve This R Session.- 6.13 External Data and/or Data Resources Used in this Lesson.- 7 Correlation, Association, Regression, Likelihood, and Prediction.- 7.1 Background.- 7.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions.- 7.3 Organize the Data and Display the Code Book.- 7.4 Quality Assurance, Data Distribution, and Tests for Normality.- 7.5 Statistical Test(s).- 7.6 Summary of Outcomes.- 7.7 Addendum 1: Multiple Regression.- 7.8 Addendum 2: Likelihood and Odds Ratio.- 7.9 Addendum 3:Parametric v Nonparametric.- 7.10 Addendum 4: Additional Practice Data Sets.- 7.11 Prepare to Exit, Save, and Later Retrieve This R Session.- 7.12 External Data and/or Data Resources Used in this Lesson.- 8 Working with Large and Complex Datasets.- 8.1 Background.- 8.2 Import Data in Comma-Separated Values (.csv) File Format and/or Self Generate the Data Using R-Based Functions.- 8.3 Organize the Data and Display the Code Book.- 8.4 Conduct a Visual Data Check Using Graphics (e.g., Figures).- 8.5 Descriptive Statistics for Initial Analysis of the Data.- 8.6 Quality Assurance, Data Distribution, and Tests for Normality.- 8.7 Statistical Test(s).- 8.8 Summary of Outcomes.- 8.9 Addendum1: Additional Graphics, to Show Relationships Between and Among Data.- 8.10 Addendum2: Graphics Using the lattice Package.- 8.11 Addendum3: Graphics Using the ggplot2 Package.- 8.12 Addendum 4: Beyond an Introduction to R - Use the tidyverse to Create Subsets of Original Datasets.- 8.13 Prepare to Exit, Save, and Later Retrieve This R Session.- 8.14 External Data and/or Data Resources Used in this Lesson.- 9 Future Actions and Next Steps.- 9.1 Use of This Text.- 9.2 R and Beautiful Reporting with R Markdown.- 9.3 Future Use of R for Biostatistics.- 9.4 Big Data and Bio Informatics.- 9.5 External Resources.- 9.6 Contact the Authors.

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Book SynopsisThe book discusses the impact of genetics, social determinants of health, the environment, and lifestyle in the burden of cardiometabolic conditions in African American and Hispanic/Latinx populations. It includes fully updated and revised chapters on genetics and CVD risk, epidemiology of cardiovascular health, cardiovascular imaging, dyslipidemias and other emerging risk factors, obesity and metabolic syndrome, heart failure, and genetic variations in CVD. Unique aspects within African American and Hispanic/Latinx populations are explored with suggested appropriate therapeutic interventions. New chapters focus on ASCVD risk assessment, emerging precision medicine concepts, the impact of diabetes, resilience and CVD survival, and lifestyle and dieting considerations. Written by a team of experts, the book examines the degree to which biomedical and scientific literature can clarify the impact of genetic variation and environment on cardiovascular disease. The Second Edition of Cardiovascular Disease in Racial and Ethnic Minority Populations is an essential resource for physicians, residents, fellows, and medical students in cardiology, internal medicine, family medicine, clinical lipidology, and epidemiology.Table of Contents1. Overview and Perspectives: Cardiovascular Disease in Racial/Ethnic Minorities in the era of COVID-19.- 2. Introduction to Precision Medicine: Minority Populations and Cardiovascular Health.- 3. Lipoprotein (a): A Cardiovascular Risk Factor affecting Ethnic Minorities.- 4. Emerging Precision Medicine Concepts and Cardiovascular Health in African Americans and Hispanics.- 5. The Implementation Frontier: Impact on Cardiovascular Health in Racial and Ethnic Minority Populations.- 6. Genomic Approaches to Hypertension.- 7. Heart Failure in African Americans and Hispanic Americans; a persistent and disproportionate burden in under-represented minorities.- 8. Heterogeneity, Nativity, and Disaggregation of Cardiovascular Risk and Outcomes in Hispanic Americans.- 9. Cardiovascular Epidemiology in Hispanics/Latinos: Lessons Learned from HCHS/SOL.- 10. Lessons Learned from the Jackson Heart Study.- 11. Cardiovascular Disease Risk Factors in the Hispanic/Latino Population.- 12. Progress in ASCVD Risk Assessment in African Americans and Hispanic Americans.- 13. CARDIOVASCULAR DISEASE IN MINORITIES - Unique Considerations: Hypertension in African and Hispanic Americans.- 14. Weight Loss, Lifestyle, and Dietary Factors in Cardiovascular Disease in African Americans and Hispanics.- 15. Coronary Calcium Scoring In African American and Hispanic Patients.- 16. Epidemiology of Cardiovascular Disease in African Americans.- 17. Cardiac Amyloid Heart Disease in Racial/Ethnic Minorities: Focus on Transthyretin Amyloid Cardiomyopathy .- 18. Imaging for the Assessment and Management of Cardiovascular Disease in Women and Minority Populations.

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Book SynopsisThis book addresses the many ethical issues and extraordinary risks that nurses and others are facing during the COVID-19 pandemic, which creates physical, emotional, and economic burdens, affecting nurses' overall health and well-being. Nurses are essential front-line clinicians across all health care settings and in every nation. The COVID-19 pandemic caused by the novel SARs-CoV-2 virus has affected children, adults, and communities within and across all societies. Nurses, too, have contracted the virus and died from the disease. They have also seen their colleagues, family members, and friends hospitalized or in intensive care units struggling to survive. Nursing’s professionalism and disciplinary resolve to care for patients and families amidst confusion, misinformation, and shifting guidelines has been called “heroic” by the public. How much risk should nurses be expected to accept during a pandemic? How do nurses help patients and families find comfort and dignity at the end-of-life? How do we help nurses who are suffering from moral distress and mental health concerns from what they have seen, been asked to do, or are unable to provide? And, how does society move forward from a pandemic that has challenged our basic ethical principles of justice and what is “fair, good and right” in caring for those who need care, including the most vulnerable and nurses themselves? This book addresses these and other ethical concerns that nurses are facing in their day-to-day clinical practice; experiences shared with patients, families, and colleagues. Although this book was written while the pandemic was still raging across the United States and globally, the events needed to be told as they were unfolding. This book helps us to learn from both the successes and failures that are affecting so many across the globe, including those on whom the public relies on to provide quality, compassionate, and expert care when they are sick: nurses. Table of ContentsChapter 1. IntroductionChristine Grady and Connie UlrichChapter 2. Understanding Acceptable Risks in Healthcare? [Occupational risks/limits/PPE/obligations]a. This chapter will focus on how we define an “acceptable risk” in healthcare. We will discuss the many risks that nurses encounter in their day-to-day patient care activities during COVID-19 both within hospital systems and other types of care facilities, including working without protective equipment and the general risks to patients and families. (adding statistics on risks for CPR, risks to ICU providers and others; risks with use of PPEChristine Grady and Connie UlrichChapter 3. Finding Compassion: Helping Patients Die and Sometimes Alone a. This chapter will discuss the role of nurses and others (palliative care) in helping patients die, often alone, within intensive care environments or other settings. We will share some of the innovative ways in which nurses and others met their foundational moral obligations to patients at the end-of-life, honoring the dignity of patients, and helping families through this stressful time. Christine Grady and Connie UlrichChapter 4. Preparing to Make Difficult Choices: Triage Decision and Crisis Standards of Care a. This chapter will speak to the different models of triage decision-making and the ethics of priority setting and allocation of scarce resources.Christine MitchellChapter 5. The Emotional and Moral Remnants of COVID-19: Burnout, Moral Distress, and Mental Health Concerns a. The pandemic has focused our attention to the mental health concerns of front-line nurses, including their moral distress, burnout, depression, and emotional scars from a sense of exhaustion, tragic choices, and overwhelming circumstances. Christine Grady and Connie UlrichChapter 6. Unintended Consequences: Lack of Essential and Nonessential Patient Care, Furloughs of HCP, and Institutional Financial Lossesa. The COVID-19 pandemic has given rise to unintended consequences of what is considered essential and nonessential patient care. Patients, for example, were delayed in seeking surgical services or other types of specialty care (e.g., cancer care). With the focus on COVID-19 patients, nurses have also been furloughed, affecting their economic livelihood. This chapter will highlight and discuss these concerns. Dr. Peter Buerhaus and colleaguesChapter 7. Lingering and Glaring Health Disparities amidst COVID-19 a. The COVID-19 related illnesses and deaths in minority and socially disadvantaged communities warrants our attention. This chapter will discuss these inequities and the social justice implications for quality and equitable care outcomes. Dr. Nneka SederstromChapter 8. School nurses/pediatric concernsAuthor TBCChapter 9. Global Health Ethics: Nursing Voices from China and Brazil a. This chapter will highlight the voices of nurses in two of the countries most significantly affected by COVID-19: China and Brazil. It is important to learn from both countries and to discuss the similarities and differences in caring for their populations and the role of nurses in these countries. Drs. Ulrich and Grady will provide pre and post comment to the essaysChapter 10. Moving Forward: What Have We Learned? Where do we go from here? [Conclusion] (Opportunities to move forward). Small “words of wisdom” from several nurse leaders (President of ICN, President of Sigma Theta Tau International, Liz Stokes-ANA and others). We ask several national and international nurse leaders to provide us with “words of wisdom” to help us move forward from the pandemic. Drs. Ulrich and Grady will provide commentary on these segments and conclude with their own “words of wisdom” to For each of the chapters, we will ask the authors to include a section on how the lessons learned from COVID-19 might have emerged from prior pandemics and might apply to future pandemics

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Book SynopsisThis book is designed to train graduate students across disciplines within the fields of public health and medicine, with the goal of guiding them in the transition to independent researchers. It focuses on theories, principles, techniques, and methods essential for data processing and quantitative analysis to address medical, health, and behavioral challenges. Students will learn to access to existing data and process their own data, quantify the distribution of a medical or health problem to inform decision making; to identify influential factors of a disease/behavioral problem; and to support health promotion and disease prevention. Concepts, principles, methods and skills are demonstrated with SAS programs, figures and tables generated from real, publicly available data. In addition to various methods for introductory analysis, the following are featured, including 4-dimensional measurement of distribution and geographic mapping, multiple linear and logistic regression, Poisson regression, Cox regression, missing data imputing, and statistical power analysis. Table of Contents1. Introduction to Quantitative Epidemiology.- 2. Characters, Variables, Data, and Information.- 3. Quantitative Descriptive Epidemiology.- 4. Causal Exploration with Bivariate Analysis.- 5. Confirmation with Multiple Linear Regression.- 6. Multivariate Analyses of Categorical and Counting Data.- 7. Multivariate Analysis of Time to Event Data.- 8. Simultaneous Analysis of Two Correlated Predictors.- 9. Special Issues with Quantitative Epidemiology.- 10. Power Analysis.

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Book SynopsisThis book is designed to train graduate students across disciplines within the fields of public health and medicine, with the goal of guiding them in the transition to independent researchers. It focuses on theories, principles, techniques, and methods essential for data processing and quantitative analysis to address medical, health, and behavioral challenges. Students will learn to access to existing data and process their own data, quantify the distribution of a medical or health problem to inform decision making; to identify influential factors of a disease/behavioral problem; and to support health promotion and disease prevention. Concepts, principles, methods and skills are demonstrated with SAS programs, figures and tables generated from real, publicly available data. In addition to various methods for introductory analysis, the following are featured, including 4-dimensional measurement of distribution and geographic mapping, multiple linear and logistic regression, Poisson regression, Cox regression, missing data imputing, and statistical power analysis. Table of Contents1. Introduction to Quantitative Epidemiology.- 2. Characters, Variables, Data, and Information.- 3. Quantitative Descriptive Epidemiology.- 4. Causal Exploration with Bivariate Analysis.- 5. Confirmation with Multiple Linear Regression.- 6. Multivariate Analyses of Categorical and Counting Data.- 7. Multivariate Analysis of Time to Event Data.- 8. Simultaneous Analysis of Two Correlated Predictors.- 9. Special Issues with Quantitative Epidemiology.- 10. Power Analysis.

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Book SynopsisAs a follow-up to COVID-19 in New York City: an Ecology of Race and Class Oppression, which showed that decades of discriminatory public policies shaped the Bronx into the epicenter of the first wave of COVID-19, this book examines the build up to the crest and subsequent ebbing of the second wave of COVID-19 across the 62 counties of New York State (NYS) and 152 ZIP Code areas of the four central boroughs of New York City (NYC). Like its predecessor, the sequel examines the vulnerabilities that give rise to spikes in infection rates that form epicenters. Unlike the first wave, NYC was not the epicenter of the second wave; high-incident counties just outside NYS formed an extended initial epicenter and exported COVID-19 to neighboring counties of NYS. Rural NYS counties differed significantly from urban ones socioeconomically and in infection rates during the cresting period. Before the crest, no socioeconomic factor was associated with county infection rates; rather, the major associating factor was political and cultural: percent of the 2020 vote garnered by Trump. Rural counties voted heavily for Trump. This association disappeared post-crest by mid-January 2021. In NYC, the Bronx again behaved like a single high-incidence entity, unlike the other three boroughs that had patches of high and low infection incidence. Among the topics covered: The Second COVID Wave Washes Over New York State The Second Wave Storm-Surges Across New York City Discussion of County Data from the Second Wave of COVID-19 Parsing Meaning From the 152 ZIP Code Data The book closes with a prescription for pandemic response planning based on empowered communities and workers interacting with health departments as equals. The Recurrence of COVID-19 in New York State and New York City is a valuable resource for social epidemiologists, public health researchers of health disparities, those in public service tasked with addressing these problems, and infectious disease scientists who focus on spread in human populations of new zoonotic diseases. The brief also will find readership among students in these fields, civil rights scholars, science writers, medical anthropologists and sociologists, medical and public health historians, public health economists, and public policy scientists.Table of Contents1 The Sixty-Two Counties of New York State 2 The Second COVID Wave Washes Over New York State3 Socioeconomic/Demographic Context of Big Apple’s Four Main Boroughs4 The Second Wave Storm-Surges Across New York City5 Discussion of County Data from the Second Wave of COVID-196 Parsing Meaning From the 152 ZIP Code Data 7 What Is to Be Done?

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Book SynopsisThis book discusses the theory and practice of teaching biostatistics to students in the life sciences, in particular medical and dental trainees and researchers, as well as its crucial importance to biomedical research and evidence-based health care. Specific tools and resources to biostatistics teaching (e.g., “R shiny”) are described, and how they can be used effectively to increase interaction with students and improve engagement with the subject. The book is structured into three parts: teaching and learning of statistics in medicine and allied health sciences; the move to online learning and online learning methods, especially in light of the impact of COVID-19; and computer tools and resources. It provides a unique insight into teaching biostatistics to medical and dental students from some of the most prominent biostatisticians who also have a very strong interest in biostatistics pedagogy. Biostatistics teaching is important for maintaining the quality of biomedical research and also in evidence-based medicine, both of which are key to the health and well-being of the world population. This book is particularly useful to readers who are new to the field of biostatistics teaching as well as to more experienced teachers as it presents the latest accounts of the teaching and learning of biostatistics, recent experiences of increased use of online teaching, and useful computer resources and tools for teaching biostatistics.Table of Contents1. A Survey of Biostatistics Teaching in Medicine and Dentistry in Higher Education in the UK2. Evidence-based practice teaching for undergraduate dental students3. Teaching Medical Statistics within the context of Evidence Based Medicine4. Teaching Null Hypothesis Significance Testing (NHST) in the Health Sciences: The Significance of Significance5. Teaching conceptual understanding of p-values and of confidence intervals, whilst steering away from common misinterpretations 6. Using directed acyclic graphs (DAGs) to represent the data generating mechanisms of disease and healthcare pathways: a guide for educators, students, practitioners and researchers7. Statistics without maths: using Random Sampling to teach Hypothesis Testing.8. COVID-19: Online not distant – MSc students’ feedback on an alternative approach to teaching ‘Research Methods and Introduction to Statistics’ at UCL Queen Square Institute of Neurology.9. Common misconceptions of online statistics teaching 10. Authentic project-based assessment using the Islands: Instructor’s view. 11. An interactive application demonstrating frequentist and Bayesian inferential frame-works12. Teaching data analysis to life scientists using “R” statistical software: challenges, opportunities, and effective methods13. Statistics in a world without science14. Killing me softly with your stats teaching: How much stats is too much stats?15. Life as a medical statistician.

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Book SynopsisThis book addresses the origins, determinants and magnitude of the global problem of sedentary behaviour, along with concise yet in-depth solutions for tackling it. As a consequence of major technological advances in modern society, many people find themselves in environments characterized by prolonged sedentary behaviour. Building on the contributions of leading experts in the field, the new edition of this book presents updated knowledge about sedentary behaviour, its medical and public health significance, its correlates and determinants, measurement techniques, and recommendations for addressing this behaviour at the individual, community, environmental, and policy level. The book encompasses current research linking the COVID-19 pandemic to increased levels of sedentary behavior, and it covers global and planetary health aspects of sedentary behavior, highlighting sustainable development goals such as health and well-being for all. Applying a cross-disciplinary methodology, the book avoids considering physical activity and sedentary behavior as a single continuum, which potentially hampers progress in confronting widespread levels of sedentariness. Rather, the book helps readers better understand how sedentary and physically active behavior co-occur and how the two behaviours have distinct contributing factors. Building on the contributions of distinguished international experts in the field, this thorough resource is a valuable asset and challenges professionals, researchers, students, and practitioners alike to adopt new strategies and expand their reach.Table of ContentsPart I. Fundamentals of Sedentary Behaviour Epidemiology1. Introduction to Sedentary Behaviour EpidemiologyCarmen Jochem, Daniela Schmid, and Michael F. Leitzmann2. The Descriptive Epidemiology of Sedentary BehaviourHannah Ahrensberg, Christina B. Petersen, Jane Nereah Wesonga Jacobsen, Mette Toftager,and Adrian E. Bauman3. Measurement of Sedentary Behaviour in Population StudiesBarbara Ainsworth, Fabien Riviere, and Alberto Florez-Pregonero4. Analysis and Interpretation of Sedentary Behaviour DataWeimo ZhuPart II. Health Effects of Sedentary Behaviour5. Physiological Responses to Sedentary BehaviourAna J. Pinto, Audrey Bergouignan, and Paddy C. Dempsey6. Genetics of SedentarinessYahua Zi, Hidde P. van der Ploeg, and Eco J.C. de Geus7. Sedentary Behaviour, Diabetes, and the Metabolic SyndromeJoseph Henson, Charlotte L. Edwardson, Paddy C. Dempsey, Melanie J. Davies, and ThomasYates8. Sedentary Behaviour and Cardiovascular DiseaseEmmanuel Stamatakis, Leandro F.M. Rezende, and Juan Pablo Rey-Lopez9. Sedentary Behaviour and CancerChristopher T.V. Swain, Terry Boyle, Shahid Mahmood, and Brigid M. Lynch10. Sedentary Behaviour and DepressionMark Hamer and Lee Smith11. Sedentary Behaviour and AdiposityCarmen Jochem, Daniela Schmid, and Michael F. Leitzmann12. Sedentary Behaviour and Psychosocial Health Across the Life CourseLee Smith and Mark Hamer13. Sedentary Behaviour and AgeingDawn A. Skelton, Juliet A. Harvey, Calum F. Leask, and Jennifer Scott14. Sedentary Behaviour and MortalityAshleigh R. Homer, and David W. DunstanPart III. Understanding Sedentary Behaviour and Promoting Reductions in Time SpentSedentary15. An Ecological Model for Understanding and Influencing Sedentary BehaviourNyssa T. Hadgraft, David W. Dunstan, and Neville Owen16. Sedentary Behaviour at the Individual Level: Correlates, Theories, and InterventionsStuart J.H. Biddle17. Specific Interventions Targeting Sedentary Behaviour in Children and AdolescentsJo Salmon, Harriet Koorts, Lauren Arundell, and Anna Timperio18. Workplace Programs Aimed at Limiting Occupational SittingGenevieve N. Healy, Samantha K Stephens, and Ana D. Goode19. Approaches to Decrease Sedentary Behaviour Among the ElderlyAnn M. Swartz and Whitney A. Welch20. Interventions Directed at Reducing Sedentary Behaviour in Persons with Pre-existingDisease or DisabilityStephanie A. Prince21. Specific Approaches to Reduce Sedentary Behaviour in Persons with Overweight/ObesityKatherine E. DeVivo, Dori E. Rosenberg, Sara H. Marchese, and Christine A. Pellegrini22. Programmes Targeting Sedentary Behaviour Among Ethnic Minorities and ImmigrantsMelicia C. Whitt-Glover, Amanda A. Price, and Breana Odum23. Sedentary Behaviour at the Community Level: Correlates, Theories, and InterventionKrista S. Leonard, Sarah L. Mullane, Mark A. Pereira, and Matthew P. Buman24. Sedentary Behaviour and the Social and Physical EnvironmentTrish Gorely, Simone A Tomaz, and Gemma C. Ryde25. Targeting Sedentary Behaviour at the Policy LevelAnthony D. Okely, Megan Hammersley, and Salome Aubert26. Dynamics of Sedentary Behaviours and Systems-Based Approach: Future Challenges andOpportunities in the Life Course Epidemiology of Sedentary BehavioursSebastien F.M. Chastin, Sofie Compernolle, Marieke De Craemer, Jean-Michel Oppert, andGreet Cardon27. From a Public to a Global and Planetary Health Perspective on Sedentary BehaviourEpidemiologyCarmen Jochem, Michael Leitzmann28. Ergonomic Support for Physiologically Correct SittingJoachim Grifka29. Limitations in Sedentary Behaviour Research and Future Research NeedsDaniela Schmid, Carmen Jochem, and Michael F. Leitzmann

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Book SynopsisThis book addresses the description and analysis of occurrence data frequently encountered in epidemiological studies. With the occurrence of Covid-19, people have been exposed to the analysis and interpretation of epidemiological data. To be informed consumers of this information, people need to understand the nature and analysis of these data. Effort is made to emphasize concepts rather than mathematics. Subjects range from description of the frequencies of disease to the analysis of associations between the occurrence of disease and exposure. Those analyses begin with simple associations and work up to complex relationships that involve the control of extraneous characteristics. Analyses rely on the statistical software R, which is freeware in wide use by professional epidemiologists and other scientists.Table of ContentsIntroduction to R.- Measures of Disease Frequency.- Measures of Association.- 2x2 Tables.- Life Tables.- Control of Confounding.

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Book SynopsisPatients with pain emanating from their spines represent some of the most frequent and challenging cases for physical therapists. Here is a comprehensive and practical introduction to the management of back pain and restricted spinal function caused by intervertebral disk damage. The authors provide evidence-based, clinically oriented strategies for the diagnosis and therapeutic treatment of disk injury in the lumbar, thoracic, and cervical spinal regions. The text gives an overview of research studies on the effects of physical therapy on back pain, step-by-step guidance on examination and conservative and postoperative physical therapy procedures, and detailed discussion of rehabilitation and prevention of further disk damage. Key Features: Extensive coverage of examination, from patient history to tests for assessing spinal movement to nerve conduction Precise instructions and useful pointers on treatment methods aid in daily practice Chapter on basic principles of anatomy, physiology, and epidemiology offer foundational knowledge Crucial information on approaches for rehabilitation and injury prevention, including strengthening, coordination exercises, and conditioning Case studies present clinical examples that guide the reader through the full course of therapy 70 clear line drawings illustrate how to maintain correct posture; avoid poor posture; and protect and train muscles, nerves, and joints Physical Therapy for Intervertebral Disk Disease is a complete guide to the diagnosis and physiotherapeutic treatment of problems resulting from intervertebral disk damage. Practitioners and students of physical therapy, rehabilitation medicine, and occupational therapy will read this book cover to cover and refer to it regularly when working to relieve back pain and restore full capacity in their patients.Table of ContentsChapter 1: Introduction Chapter 2: General Principles Chapter 3: Medical Diagnosis and Treatment Chapter 4: Diagnosis in Physical Therapy Chapter 5: Therapy Chapter 6: Lumbar Spine Chapter 7: Thoracic Spine Chapter 8: Cervical Spine Chapter 9: Rehabilitation and Prevention Chapter 10: Diseases Occurring in Association With Prolapsed Disks Chapter 11: Psychosocial Risk Factors Chapter 12: Selected Studies on the Topic of Spinal Disorders Chapter 13: Significance, Types, and Objectives of Clinical Studies

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Book SynopsisUnique resource provides foundation for worldwide prevention, diagnosis, and treatment of orthopaedic fracturesClinical Epidemiology of Orthopaedic Trauma, Third Edition by renowned orthopaedic surgeon and researcher Yingze Zhang and an impressive cadre of contributors expands on the widely acclaimed prior editions. Leveraging an epidemiological database with the distinction of being the largest domestic and foreign sample volume of orthopaedic trauma, this remarkable book expands on the epidemiology of fractures in China, with national incidence rates new to this edition. It offers a wealth of information that will impact treatment planning, future allocation of resources in trauma care, and initiatives in preventive medicine, worldwide.Comprehensive in scope, the new edition provides unparalleled insights into the current state of Chinese orthopaedic surgery. The book features evaluation of every fracture seen and treated at a m

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Book SynopsisThis book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the “Challenge of Big Data and Applications of Statistics,” in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences. The invited contributions addressed rich topics closely related to big data analysis in the data sciences, reflecting recent advances and major challenges in statistics, business statistics, and biostatistics. Subsequently, the six editors selected 19 high-quality presentations and invited the speakers to prepare full chapters for this book, which showcases new methods in statistics and data sciences, emerging theories, and case applications from statistics, data science and interdisciplinary fields. The topics covered in the book are timely and have great impact on data sciences, identifying important directions for future research, promoting advanced statistical methods in big data science, and facilitating future collaborations across disciplines and between theory and practice.Table of Contents*Under attachments tab*

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Book SynopsisThe lifestyles and socio-economic status that are prevalent in regions of the world with limited resources form the background for the unique features of neoplastic diseases in these areas, where the majority of the world population lives. The predominance of the world’s retroviral burden of in these areas further compounds the nature and challenges of the cancer there. Much of the international cancer literature covers the nature and challenges of the disease as seen in high-income regions of the world, thereby giving a skewed view of the global cancer challenges. As the low- and middle-income regions of the world transition from communicable to non communicable disease patterns, there is a need for a corresponding paradigm shift, with increased emphasis on what the world needs to know about non communicable diseases, including cancer, where the disease is hitherto poorly documented. The main goal of the proposed book is to contribute to this outcomes.Table of ContentsPart IV: Future Perspectives Chapter 10 – Strategies for progress Abstract Section 10.1.0: The role of international partnership in the development of global health systems Section 10.1.1: Models of humanitarian global outreach in health care Section 10.1.2: The concept of “convergence” and the future of health care research Section 10.1.3.0: The concept of global health Section 10.1.3.1: Models of global health partnership in cancer control Section 10.1.3.2: The tiered resource stratification framework of the Breast Health Global Initiative (BHGI) Network Section 10.1.3.3: ASCO’s resource-stratified guidelines for the management of invasive cervical cancer Section 10.1.3.4: NCCN framework for resource stratification for invasive cervical cancer Section 10.1.3.5: Resource-stratified approaches in the primary prevention of cervical cancer Section 10.1.3.5.1 ASCO resource-stratified guideline for the primary prevention of cervical cancer Section 10.1.3.6: Resource-stratified approaches in the secondary prevention of cervical cancer Section 10.1.3.4.1: Selected Global Health Activities for promoting cancer control/Health Volunteers Overseas (HVO) Section 10.1.3.4.2 Global Curriculum and Mentoring Program Section 10.1.3.4.3: Global Curriculum and Mentoring Program/International Development and Education Award Section 10.1.3.4.4: Proposal for recognizing global oncology as an academic field Section 10.2: Overcoming barriers to progress in the control of cancer and retroviral diseases, including HIV/AIDS Section 10.2.1: Prioritizing strategies for universal health coverage Section 10.2.1.1: mHealth Strategies for Universal Health Coverage Section 10.2.1.2: Community Health Insurance Coverage as a strategy for Universal Health Care Section 10.2.1.3: Innovation in provider training as a strategy in UHC Section 10.2.2: The role of politics in attainment of Universal Health Coverage Section 10.2.3: The role of science and engineering in human welfare Section 10.2.3.1: The role of science Section 10.2.3.1.1: Science advocacy Section 10.2.3.1.2: Science education in low- and middle-income countries Section 10.2.3.1.3 Examples of the transforming effect of science in LMICs Section 10.2.3.1.3.1 Impact of science on the emergence of South Korea Section 10.2.3.1.3.2: Impact of science on Middle-Eastern cooperation Section 10.2.3.1.3.3: Impact of the US-Cuba scientific diplomacy Section 10.2.3.1.3.4: Boosting science in Singapore Section 10.2.3.1.3.5: India boosts its ambitious space program Section 10.2.3.2: Transforming the practice of engineering to meet global health needs Section 10.2.3.3 Models in innovation with potentials for cancer and HIV/AIDS control in LMICs Section 10.2.3.3.1: Affordable, weather durable x-ray machine Section 10.2.3.3.2: Affordable cancer immunotherapy in Cuba Section 10.2.3.3.3: The smart village for rural electrification Section 10.2.3.3.4: HIV/AIDS control in China Section 10.3: The future of control of cancer and retroviral diseases Page 1055: Section 10.3.1: From the National Cancer Act to the 21st Century Cures Act Page 1059: Section 10.3.2: Advances in lung cancer prevention Page 1062: Section 10.3.3: Ending the HIV/AIDS pandemic Page 1063: Section 10.3.4: Finding a cure for AIDS – a possible convergence of cancer and HIV/AIDS researchIndex

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Book SynopsisDieses essential befasst sich mit der einfachen linearen Regression, der simpelsten Form von Regressionsmodellen, in der für die Modellbildung nur eine einzige Einflussvariable berücksichtigt wird. Leser finden in diesem Buch die Methode der kleinsten Quadrate zur Schätzung der Modellparameter, Residualanalysen zur Überprüfung der Modellannahmen sowie weitere statistische Verfahren zur Beurteilung des Modells. Zudem erfahren sie, wie das Modell als ein Prognoseinstrument eingesetzt werden kann. Somit erwerben Leser eine solide Grundlage zum Verständnis komplexer Regressionsansätze, bei denen mehrere Variablen die Zielgröße beeinflussen und nichtlineare Zusammenhänge vorliegen.Table of ContentsDefinition des einfachen Regressionsmodells.- Überprüfung der Modellvoraussetzungen.- Beurteilung des Modells durch den Korrelations- und den Determinationskoeffizienten.- Regressionsgerade als ein Instrument für eine Prognose.- Umkehrregression.

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Book SynopsisMeinhard Kieser vermittelt anhand realer Beispiele die grundlegenden Prinzipien der Fallzahlberechnung und demonstriert deren Anwendung. Für die häufigsten Anwendungssituationen werden die entsprechenden Fallzahlberechnungsformeln hergeleitet. Einsteiger haben somit die Möglichkeit, die Grundlagen der Fallzahlplanung zu erlernen und einzuüben. Es werden außerdem die statistischen Hintergründe der Formeln und allgemeinere Zusammenhänge erläutert und Hinweise gegeben, was bei jeder Fallzahlberechnung beachtet werden sollte. Damit geht das essential deutlich über eine reine Formelsammlung hinaus und ist eine wertvolle Ergänzung für Personen, die bereits in der medizinischen Forschung tätig sind und Erfahrung bei der Fallzahlberechnung gesammelt haben.Table of ContentsDas Prinzip der Fallzahlberechnung.- Fallzahlberechnung für Zwei- und Mehr-Gruppen-Vergleiche bei normalverteilter und binärer Zielgröße.- Ausblick auf weitere Methoden zur Fallzahlberechnung in anderen Anwendungssituationen.- Hinweise auf Aspekte, die bei jeder Fallzahlberechnung beachtet werden sollten.

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Book SynopsisThis book deals with the prediction of possible future scenarios concerning the COVID-19 pandemic. Based on the well-known SIR model by Kermack and McKendrick a compartment model is established. This model comprises its own assumptions, transition rates and transmission dynamics, as well as a corresponding system of ordinary differential equations. Making use of numerical methods and a nonstandard-finite-difference scheme, two submodels are implemented in Matlab in order to make parameter estimations and compare different scenarios with each other.Table of ContentsIntroduction.- The Severe Acute Respiratory Syndrome Corona Virus Type 2.- The SIR Model in Epidemic Modelling.- The SARS-CoV-2-fitted SEIR Model.- Model Specifications.- Parameter Estimation in MAT LAB.- Markov Chain Epidemic Models.- R´esum´.

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Book Synopsis​Die auftretenden Varianten von SARS-CoV-2 beschleunigen durch ihre höheren Übertragungsraten die globale COVID-19-Pandemie, wodurch dringend neue therapeutische Angriffsziele benötigt werden. Hierbei wurde die antivirale Wirkung von Fluoxetin - einem Antidepressivum - gegen SARS-CoV-2 entdeckt. Mithilfe biochemischer und bildgebenden Methoden wurde der antivirale Wirkmechanismus von Fluoxetin näher analysiert und die saure Ceramidase als SARS-CoV-2 Wirtsfaktor charakterisiert. Veröffentlichte Studien zeigten, dass auch Aspirin eine antivirale Wirkung gegen Erkältungsviren, wie Rhinoviren und Influenzaviren zeigt. Diese antivirale Wirkung wurde in Bezug auf SARS-CoV-2 in Zellkultur und einem patienten-nahen 3D-Infektionsmodell untersucht und bestätigt. Um die Pathologie einer SARS-CoV-2-Infektion zu verstehen, wurde der Eintrittsweg des Virus in das Gehirn untersucht. Im Gegensatz zu anderen Viren überwindet SARS-CoV-2 die Blut-Hirnschranke ohne T-Zellen oder Makrophagen. Ebenso wurde der Einbau eines lipophilen Fluoreszenzfarbstoffs in die Virusmembran etabliert, womit die direkte Markierung verschiedener Viren trotz ihrer unterschiedlicher Membranzusammensetzung möglich ist. Mit superauflösender Mikroskopie (SIM) wurde der virale Eintritt verschiedener umhüllter Viren visualisiert.Table of ContentsEinleitung.- Materialien.- Methoden.- Ergebnisse.- Diskussion.- Eigene Publikationsliste.- Literaturverzeichnis.

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Book SynopsisBeispielreich baut dieses Buch Schritt für Schritt die statistischen Grundlagen moderner Datenanalysen auf. Im Gegensatz zu anderen einführenden Werken legt dieses Buch großen Wert auf einen umfassend gespannten Bogen, einen roten Faden, der alle Methoden zusammenführt. Dabei werden klassische statistische Methoden (etwa t-Test oder multiple Regression) als Spezialfall des Generalisierten Linearen Modells entwickelt. Entsprechend legt das Buch zunächst eine Grundlage in beschreibender Statistik, Verteilungen und maximum likelihood, aus der dann alle anderen Verfahren abgeleitet werden (ANOVA, multiple Regression). Jeder Schritt ist auf zwei Kapitel verteilt: Im ungradzahligen Kapitel wird anhand von vielen Beispielen und Abbildungen die Idee der statistischen Herangehensweise erläutert. Im sich daran anschließenden gradzahligen Kapitel wird die Umsetzung in der freien Statistiksoftware R gezeigt. Ein Kapitel zur Wissenschafts- und Forschungstheorie und eines zum Design von Experimenten und Stichprobeverfahren komplettiert dieses einleitende Werk. Das Buch legt großen Wert auf Verständlichkeit und Umsetzung. Mathematische Herleitungen treten demgegenüber stark in den Hintergrund. Jedes Kapitel enthält explizit ausgewiesene Lerninhalte, die durch Übungen zu jedem R-Kapitel geprüft werden können. Ein ausführliches Schlagwortverzeichnis inklusive der R-Funktionen macht das Buch auch als Nachschlagewerk nutzbar. Die zweite Auflage wurde ergänzt um Schätzung mittels der Momentenmethode, Residuendiagnostik für nicht-normalverteilte Daten und die erschöpfende Modellsuche.Table of ContentsStichprobenstatistik.- Stichprobenstatistiken in R.- Verteilungen, ihre Parameter und deren Schätzer.- Verteilungen, Parameter und Schätzer in R.- Korrelation und Assoziation.- Korrelation und Assoziation in R.- Regression - Teil I.- Regression in R Teil I.- Regression Teil II.- Regression in R Teil II.- Das Lineare Modell: t-Test und ANOVA.- Das Lineare Modell: t-Test und ANOVA in R.- Hypothesen und Tests.- Experimentelles Design.- Multiple Regression.- Multiple Regression in R.- Ausblick.

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Book SynopsisThis textbook offers a comprehensive analysis of medical decision-making under uncertainty by combining test information theory with expected utility theory. The authors show how the parameters of Bayes’ theorem can be combined with a value function of health states in order to arrive at informed test and treatment decisions in the face of diagnostic and therapeutic risks. Distinguishing between risk-neutral, risk-averse, and prudent decision-makers, they demonstrate the effects of risk preferences on medical decisions. Furthermore, they analyze individual and multiple tests as well as diagnostic models in which the decision-maker chooses the test outcome. The consequences of test and treatment decisions for the patient are encompassed by quality-adjusted life years (QALYs) and the standard economic model, which applies the willingness to pay for health approach. Lastly, non-expected utility models of choice under risk and uncertainty are presented. Although these models can explain some of the test and treatment decisions observed, they are less suitable for normative analyses aimed at providing guidance on medical decision-making. This third edition provides extensively revised versions of all chapters and reflects recent innovations in medical decision-making such as decision curve analysis. New chapters focus on the health economics of and revealed preferences in medical decisions. The book is intended for students of (health) economics and medicine as well as for medical decision-makers and physicians dealing with uncertainty in their test and treatment decisions.Table of ContentsChapter 1. Introduction.- Chapter 2. Basic Tools in Medical Decision Making.- Chapter 3. Basic Tools in Economics: Preferences, Expected Utility, Risk Aversion and Prudence.- Chapter 4. Treatment Decisions.- Chapter 5. Test and Treatment Decisions.- Chapter 6. Prudence and Medical Decision Making.- Chapter 7. Optimal Strategy for Multiple Diagnostic Tests.- Chapter 8. The Optimal Cut-off of a Diagnostic Test.- Chapter 9. The Total Value of Information of a Test.- Chapter 10. The Economics of Medical Decision Making.- Chapter 11. Valuing Health and Life.- Chapter 12. Revealed Preference in Medical Decisions.- Chapter 13. Imperfect Agency and Non-Expected Utility Models

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Book SynopsisPandemie und Klimakrise rufen die herausragende Rolle der Wissenschaft und des wissenschaftlichen Wissens für Informierung und Orientierung der Gesellschaft sowie für die Beratung der Politik bei der Ausrichtung praktischer Maßnahmen ins Bewusstsein. In diesem Zusammenhang wird die Frage virulent, weshalb der Wissenschaft diese herausgehobene Rolle zukommt. Dass diese Frage trotz der vielbeschworenen Autorität der Wissenschaft alles andere als trivial ist, zeigt sich daran, dass Wissenschaftsskepsis und Relativierung wissenschaftlicher Resultate bis hin zur Wissenschaftsleugnung Einfluss gewinnen, sobald es um konkrete Fragen der Ausrichtung gesellschaftlichen Handelns an der Wissenschaft geht. Wodurch ist also Vertrauen in die durch die Wissenschaft ermittelten Fakten, die in ihren Modellen entworfenen Szenarien und ihre Ratschläge an Gesellschaft und Politik gerechtfertigt? Weshalb soll man der Wissenschaft in besonderem Maße vertrauen und auf ihren Ratschlag hören?Insgesamt sollen die Beiträge des Buches Aufschluss darüber geben, wodurch die Vertrauenswürdigkeit der Wissenschaft in ihrer modernen Form gerechtfertigt ist und an welche Bedingungen ihre besondere Rolle in der Gesellschaft geknüpft ist. Was kann Wissenschaft für die Gesellschaft leisten und wo liegen die Grenzen ihrer orientierenden Rolle? Was heißt es „auf die Wissenschaft zu hören“ und was sind die Bedingungen dafür, dass Menschen in einer demokratischen Gesellschaft sich wissenschaftliche Erkenntnisse aneignen und sie als Richtschnur für ihr Handeln verwenden?Table of Contents1 Glaubwürdigkeit der Wissenschaft.- 2 Über den Erfolg der Physik – Erkenntnisgewinn aus Empirie und Theorie.- 3 Chancen und Grenzen mathematischer Modelle in der Pandemiebewältigung.- 4 Klimawandel – mit dem Rücken zur Wand.- 5 Handlungsoptionen für den Klimaschutz im 21. Jahrhundert.- 6 Konzeptuelle Fragen in den Grundlagen der Klimawissenschaften.- 7 Weshalb wir Wissenschaften im Plural zur Entscheidungsfindung brauchen: Das Beispiel Energiewende.- 8 Wahrheit als Wert und Ziel der Wissenschaft?.- 9 Politikberatung und Wissenschaft.- 10 Wie statistischer Erkenntnisgewinn die Ethik verändert.- 11 Vertrauen in die Wissenschaft – was ist es und welche Grundlage hat es?.

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Book SynopsisVorwort.- 1 Einführung.- 2 Likelihood.- 3 Frequentistische Eigenschaften der Likelihood.- 4 Likelihood-Inferenz bei vektoriellem Parameter.- 5 Bayer-Inferenz.- 6 Modellwahl.- 7 Numerische Methoden zur Bayes-Inferenz.- 8 Prognose.- A Ergänzungen aus der Stochastik.- B Ergänzungen aus der linearen Algebra und Analysis.- C Ergänzungen aus der Numerik.- Literaturverzeichnis.- Index.

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Book SynopsisThe book is a reference book useful for undergraduates, postgraduates and research scholars of biological, ecological and medical sciences. The purpose of writing this book is to provide an accessible reference book on statistical techniques whose proper use will help students in withdrawing accurate results and able to interpret them logically. The methods described in this book are, of course, the same as those used in different disciplines, but things are made so user's friendly that even general readers will find this book useful. The s of the book have been organized in such a way that suits the course curriculum of various universities. In this book enough materials are provided to cover statistical techniques with examples which are ecological and biological based.Table of Contents1. Introduction to Statistics 2. Organisation of Data 3. Data Transformation 4. Descriptive Statistics: Measurement of Central Tendency 5. Descriptive Statistics: Measures of Dispersion 6. Descriptive Statistics: Data Distributions 7. Inferential Statistics: Confidence Intervals 8 Inferential Statistics: Parametric Tests of Significance 9 Inferential Statistics: Non-Parametric Tests of Significance 10 Inferential Statistics: Correlation and Regression 11 Presentation of Data 12 Choosing A Statistical Test

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Book SynopsisCOVID-19 has made differential impacts on countries and communities around the world. China, where COVID-19 started, has developed and utilized different types of technologies, including both traditional and disruptive technologies, to address the pandemic risks. Also, there have been many innovations in applying technologies in different contexts during the pandemic as well as in the post-pandemic recovery and preparedness aspects. This book covers some of these technological developments as well as the governance mechanisms for developing a technology and innovation ecosystem in a post-COVID-19 context in China. The book also explores the experiences and lessons learned from different types of technologies and their implementation in the post-COVID-19 period and highlights how they can be useful to prepare for future calamities.Table of ContentsChapter 1: Overview of Post COVID Scenario in China Chapter 2: Innovation and Technology Ecosystem: Historical Perspectives Chapter 3: Drones Activity in Epidemic Prevention and Prospects in the Post COVID-19 Chapter 4: Social Media Development and Application During Pandemic and Post-Pandemic from the Perspectives of Recovery and Preparedness Chapter 5: Towards a Digital China Through Digital Economy Chapter 6: Big Data and Its Implication in China Chapter 7: Robotics and Its Advancement in Modern China Chapter 8: Artificial Intelligence and its Importance in Post COVID-19 China Chapter 9: 5G and Its Implication to Communication in China Chapter 10: Evolution from IoT to IoE Era in China Chapter 11: Going Beyond the “Norm” in Technology and Innovation Apparatus in Emergency Situation: A Post COVID-19 Society

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Book SynopsisThis book analyzes the development of medical big data projects in Japan.Japan is experiencing unprecedented population aging, and labor productivity has decreased accordingly. Big data analysis of the Japanese medical real-world database (RWD) has the potential to tackle this issue.To allow readers to gain an understanding of Japanese medical big data analysis, the book discusses the original Japanese system that generates medical RWDs in the hospital medical records system, the nationwide standardized health checkup system, and the public medical insurance system in Japan.After introducing four major big data projects in the healthcare–medical field in Japan, the book explains the importance of creating information standards to maintain data quality and to analyze medical big data. It enables readers to analyze which standards are installed in which RWDs, how the standards are maintained, and which issues are prevalent in Japan.This book also describes the ethical processes involved in big data projects involving medical RWDs in Japan.Table of Contents ​Overview NDB (National Database) MID-NET (Medical Information Database Network) DPC (Diagnosis Procedure Combination) Disease Registration Cohort Study with EMR(SS-MIX2) Standard Code Mapping and Data Quality Phenotyping Data Analysis on Real World Data Ethical Issues of Data Secondary Use in Japan

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Book SynopsisThis book provides an overview of statistical concepts and basic methodology for the study of genetics of human traits and diseases. It attempts to provide a step-by-step description of problem identification, study design, methodology of data collection, data exploration, data summarization and visualization, and more advanced analytical methods for inferring genetic underpinnings of human phenotypes. The book provides codes in R programming language for implementation of most of the statistical methods described, which will enable practitioners to perform analysis of data on their own, without having to mold the data to fit the requirements of commercial statistical packages. Useful to anyone engaged in studies to understand and manage good health, the book is a useful guide for sustainable development of humankind. Primarily intended for practicing biologists especially those who carry out quantitative biological research, in particular, human geneticists, the book is also helpful in classroom teaching.Table of ContentsIntroduction to analysis of human genetic data.- Basic understanding of single gene expression data.- Basic probability theory and inference.- Analysis of single gene expression data.- Analysis of gene expression data in a dependent set up.- Tying genomes with disease.- Some extensions of genetic association study.- Exploring multivariate data.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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Book SynopsisFinding effective methods for mosquito control remains one of the great global challenges facing this generation. Bio-mathematics, Statistics and Nano-Technologies: Mosquito Control Strategies brings together experts from a large array of disciplines in order to provide a comprehensive overview of cutting-edge techniques to model, analyse and combat mosquito-transmitted vector-borne diseases. Features Includes multiple case studies Suitable for scientists and professionals working on methods for mosquito control and epidemiology Provide a much-needed focal point for interdisciplinary discussion Trade Review"I am delighted to see the outputs of this European Union funded collaborative effort in this engaging book format, that is well targeted for both entomology students and vector control practitioners and demonstrates to those across a range of other disciplines how they might engage productively in the debate on how we evolve insect control over the next decades."—Professor Janet Hemingway, from the ForewordTable of Contents1. Introduction and Overview. Section I. Control of Mosquitoes and Their World: An Overview. 2. Practical Control Methods and New Techniques for Mosquito Control. 3. Concepts of the Best Management Practices for Integrated Pest, Mosquito, and Vector Management. 4. Overview of Personal Protection Measures Through the Innovative Use of Repellent-Textiles. 5. Biology, Surveillance and Control of Mosquito Vectors. Section II. Mathematical Modelling Immunity: An Overview based on Malaria. 6. Models of Acquired Immunity to Malaria: A Review. Section III. Mathematical Epidemiology including Mosquito Dynamics and Control Theory. 7. Multi-strain Host-vector Dengue Modelling: Dynamics and Control. 8. Mathematical Models and Optimal Control in Mosquito Transmitted Diseases. Section IV. Topological Studies: Topology Meets Mosquito Control. 9. On The Shape and Design of Mosquito Abatement Districts. Section V. Chemometric and Mathematical Approach for Modelling and Designing Mosquito Repellents. 10. A Multiplatform Chemometric Approach to Molecular and Mathematical Modeling of Mosquito Repellents. Section VI. Pharmacy Meets Mosquito Control: Using Pharmacological Tools Combating Mosquito Transmitted VBDs. 11. Pharmacological Approach to Combat Mosquito Transmitted Malaria. Section VII. Using Natural Oils Combatting Mosquitos: An Overview. 12. Plant based Repellents: Green Mosquito Control. 13. Micrcencapsulation of Essential Oils for Antimicrobial Function and Mosquito Repellency. Section VIII. Textiles and Paints as Mosquito Control Tools. 14. Mosquito Repellent against Anopheles SPP. and Aedes Aegypti on Cotton Fabric. 15. Silica-Based Organic-Inorganic Hybrid Treatments as Anti-Mosquito Textile Finishing. 16. Cotton and Polyester Fabrics Plasma Coated with Hydrogenated Amorphous Carbon Films. Section IX. Testing Methods for Treated Textiles with Mosquito-Repellents: An Overview. 17. Testing Methods for Mosquito-Repellent Treated Textiles. Section X. Case Studies: Putting the Knowledge into Action. 18. A Case Study: How the Rephaiah Project Combats Malaria in Young Children. 19. Strengthening the control of mosquito vectors in Cabo Verde; New Approaches to Improve Intervention Strategies.

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