This textbook offers a comprehensive analysis of medical decision making under uncertainty by combining Test Information Theory with Expected Utility Theory. The book shows how the parameters of Bayes' theorem can be combined with a value function of health states to arrive at informed test and treatment decisions. The authors distinguish between risk-neutral, risk-averse and prudent decision makers and demonstrate the effects of risk preferences on physicians' decisions. They analyze individual tests, multiple tests and endogenous tests where the test outcome is chosen by the decision maker. Moreover, the topic is examined in the context of health economics by introducing a trade-off between enjoying health and consuming other goods, so that the extent of treatment and thus the potential improvement in the patient's health becomes endogenous. Finally, non-expected utility models of choice under risk and uncertainty (i.e. ambiguity) are presented. While these models can explain observed test and treatment decisions, they are not suitable for normative analyses aimed at providing guidance on medical decision making.

This book provides a timely examination of the Ebola pandemic in Sierra Leone from four different standpoints: 1) a social standpoint that focuses on the way in which the vulnerable Sierra Leonian population viewed the pandemic in light of their cultural beliefs, memories of past wars and narratives and actions of the government; 2) a good governance standpoint that exposes lapses in health governance and the general unpreparedness of the government and international community to deal with the outbreak; 3) a scientific research standpoint that looks at the role played by the Sierra Leone's Lassa Fever Research Laboratories as a main hub for the investigation, monitoring and evaluation of communicable diseases in the Mano River Union countries; and 4) an international politics standpoint that examines the development of a new bio-security international apparatus involving a wide range of international actors and institutions.

The primary objective of this book is to study some of the research topics in the area of analysis of complex surveys which have not been covered in any book yet. It discusses the analysis of categorical data using three models: a full model, a log-linear model and a logistic regression model. It is a valuable resource for survey statisticians and practitioners in the field of sociology, biology, economics, psychology and other areas who have to use these procedures in their day-to-day work. It is also useful for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. The importance of sample surveys today cannot be overstated. From voters' behaviour to fields such as industry, agriculture, economics, sociology, psychology, investigators generally resort to survey sampling to obtain an assessment of the behaviour of the population they are interested in. Many large-scale sample surveys collect data using complex survey designs like multistage stratified cluster designs. The observations using these complex designs are not independently and identically distributed - an assumption on which the classical procedures of inference are based. This means that if classical tests are used for the analysis of such data, the inferences obtained will be inconsistent and often invalid. For this reason, many modified test procedures have been developed for this purpose over the last few decades.

In medical and health care the scientific method is little used, and statistical software programs are experienced as black box programs producing lots of p-values, but little answers to scientific questions. The pocket calculator analyses appears to be, particularly, appreciated, because they enable medical and health professionals and students for the first time to understand the scientific methods of statistical reasoning and hypothesis testing. So much so, that it can start something like a new dimension in their professional world. In addition, a number of statistical methods like power calculations and required sample size calculations can be performed more easily on a pocket calculator, than using a software program. Also, there are some specific advantages of the pocket calculator method. You better understand what you are doing. The pocket calculator works faster, because far less steps have to be taken, averages can be used. The current nonmathematical book is complementary to the nonmathematical "SPSS for Starters and 2nd Levelers" (Springer Heidelberg Germany 2015, from the same authors), and can very well be used as its daily companion.

This book covers all the topics found in introductory descriptive statistics courses, including simple linear regression and time series analysis, the fundamentals of inferential statistics (probability theory, random sampling and estimation theory), and inferential statistics itself (confidence intervals, testing). Each chapter starts with the necessary theoretical background, which is followed by a variety of examples. The core examples are based on the content of the respective chapter, while the advanced examples, designed to deepen students' knowledge, also draw on information and material from previous chapters. The enhanced online version helps students grasp the complexity and the practical relevance of statistical analysis through interactive examples and is suitable for undergraduate and graduate students taking their first statistics courses, as well as for undergraduate students in non-mathematical fields, e.g. economics, the social sciences etc.

This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvagar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in "big data" situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on future research directions, the contributions will benefit graduate students and researchers in computational biology, statistics and the machine learning community.

This eye-opening study adds to the scarce scholarly literature on professional athletes, bringing empirical rigor to issues often clouded by mystery and hearsay. It identifies socioeconomic, demographic, and career variables as risk factors for mortality among former NBA and NFL players, along with hypotheses to be tested relating to elite athletes and other U.S. populations. A detailed multivariate analysis compares mortality factors, rates, and outcomes within and between the two leagues, comparing them also with the general U.S. male population. The findings and conclusions gleaned from this research offer possibilities for future research to improve health and quality of life in this specific athlete cohort, among athletes in general, in other groups, and in the larger society. Potential risk factors analyzed in this groundbreaking study: * Race * Body Mass Index (BMI) * U.S. birthplace region (Northeast, West, Midwest, South) * Years of playing experience * Playing position Mortality and Its Risk Factors among Professional Athletes will spark interest among professionals and researchers in public health, sports medicine, and epidemiology; current and former NBA and NFL players, their families, coaches, trainers, and union representatives; non-professional basketball and football players, athletes from other sports, and their families, coaches, and trainers; social scientists; policymakers; obesity researchers; parents of children who play contact sports; students, teachers, and researchers in occupational health and racial disparities; and health care providers.

Farming Human Pathogens: Ecological Resilience and Evolutionary Process introduces a cutting-edge mathematical formalism based on the asymptotic limit theorems of information theory to describe how punctuated shifts in mesoscale ecosystems can entrain patterns of gene expression and organismal evolution. The authors apply the new formalism toward characterizing a number of infectious diseases that have evolved in response to the world as humans have made it. Many of the human pathogens that are emerging out from underneath epidemiological control are 'farmed' in the metaphorical sense, as the evolution of drug-resistant HIV makes clear, but also quite literally, as demonstrated by avian influenza's emergence from poultry farms in southern China. The most successful pathogens appear able to integrate selection pressures humans have imposed upon them from a variety of socioecological scales. The book also presents a related treatment of Eigen's Paradox and the RNA 'error catastrophe' that bedevils models of the origins of viruses and of biological life itself.

A comprehensive introduction to behavioral and social science research methods in the health sciences

"Understanding and Conducting Research in the Health Sciences "is designed to develop and facilitate the ability to conduct research and understand the practical value of designing, conducting, interpreting, and reporting behavioral and social science research findings in the health science and medical fields. The book provides complete coverage of the process behind these research methods, including information-gathering, decision formation, and results presentation.

Examining the application of behavioral and social science research methodologies within the health sciences, the book focuses on implementing and developing relevant research questions, collecting and managing data, and communicating various research perspectives. An essential book for readers looking to possess an understanding of all aspects of conducting research in the health science field, "Understanding and Conducting Research in the Health Sciences "features: Various research designs that are appropriate for use in the health sciences, including single-participant, multi-group, longitudinal, correlational, and experimental designsStep-by-step coverage of single-factor and multifactor studies as well as single-subject and nonexperimental methodsAccessible chapter explanations, real-world examples, and numerous illustrations throughoutGuidance regarding how to write about research within the formatting styles of the American Medical Association and the American Psychological Association

The book is an excellent educational resource for healthcare and health service practitioners and researchers who are interested in conducting and understanding behavioral and social science research done within the health sciences arena. The book is also a useful resource for students taking courses in the fields of medicine, public health, epidemiology, biostatistics, and the health sciences.

In the last quarter century, advances in mass spectrometry (MS) have been at the forefront of efforts to map complex biological systems including the human metabolome, proteome, and microbiome. All of these developments have allowed MS to become a well-established molecular level technology for microorganism characterization. MS has demonstrated its considerable advantage as a rapid, accurate, and cost-effective method for microorganism identification, compared to conventional phenotypic techniques. In the last several years, applications of MS for microorganism characterization in research, clinical microbiology, counter-bioterrorism, food safety, and environmental monitoring have been documented in thousands of publications. Regulatory bodies in Europe, the US, and elsewhere have approved MS-based assays for infectious disease diagnostics. As of mid-2015, more than 3300 commercial MS systems for microorganism identification have been deployed worldwide in hospitals and clinical labs. While previous work has covered broader approaches in using MS to characterize microorganisms at the species level or above, this book focuses on strain-level and subtyping applications. In twelve individual chapters, innovators, leaders and practitioners in the field from around the world have contributed to a comprehensive overview of current and next-generation approaches for MS-based microbial characterization at the subspecies and strain levels. Chapters include up-to-date reference lists as well as web-links to databases, recommended software, and other useful tools. The emergence of new, antibiotic-resistant strains of human or animal pathogens is of extraordinary concern not only to the scientific and medical communities, but to the general public as well. Developments of novel MS-based assays for rapid identification of strains of antibiotic-resistant microorganisms are reviewed in the book as well. Microbiologists, bioanalytical scientists, infectious disease specialists, clinical laboratory and public health practitioners as well as researchers in universities, hospitals, government labs, and the pharmaceutical and biotechnology industries will find this book to be a timely and valuable resource.

This book examines how legal causation inference and epidemiological causal inference can be harmonized within the realm of jurisprudence, exploring why legal causation and epidemiological causation differ from each other and defining related problems. The book also discusses how legal justice can be realized and how victims' rights can be protected. It looks at epidemiological evidence pertaining to causal relationships in cases such as smoking and the development of lung cancer, and enables readers to correctly interpret and rationally use the results of epidemiological studies in lawsuits. The book argues that in today's risk society, it is no longer possible to thwart the competence of evidence using epidemiological research results. In particular, it points out that the number of cases that struggle to prove a causal relationship excluding those using epidemiological data will lead to an increase in the number of lawsuits for damages that arise as a result of harmful materials that affect our health. The book argues that the responsibility to compensate for damages that have actually occurred must be imputed to a particular party and that this can be achieved by understanding causal inferences between jurisprudence and epidemiology. This book serves as a foundation for students, academics and researchers who have an interest in epidemiology and the law, and those who are keen to discover how jurisprudence can bring these two areas together.

This volume focuses on Global Catastrophic Biological Risks (GCBRs), a special class of infectious disease outbreaks or pandemics in which the combined capacity of the world's private and government resources becomes severely strained. These events, of which the 1918 influenza pandemic is emblematic, cause severe disruptions in the normal functioning of the world, exact heavy tolls in terms of morbidity and mortality, and lead to major economic losses. GCBRs can be caused by any type of microorganism, and myriad contextual factors can influence their impact. Additionally, there are cascading questions that arise in connection with GCBR prediction, preparation, and response. This book gathers contributions from thought leaders who discuss the multi-faceted approaches needed in order to address this problem. From understanding the special characteristics of various microbes to financing challenges, the volume provides an essential primer on a neglected but highly relevant topic. Physicians, scientists, policymakers, public health practitioners and anyone with an interest in the field of pandemics, emerging infectious disease, biosecurity, and global health security will find it a valuable and insightful resource.

In the second edition of An Introduction to the Geography of Health, Helen Hazen and Peter Anthamatten explore the ways in which geographic ideas and approaches can inform our understanding of health. The book's focus on a broad range of physical and social factors that drive health in places and spaces offers students and scholars an important holistic perspective on the study of health in the modern era. In this edition, the authors have restructured the book to emphasize the theoretical significance of ecological and social approaches to health. Spatial methods are now reinforced throughout the book, and other qualitative and quantitative methods are discussed in greater depth. Data and examples are used extensively to illustrate key points and have been updated throughout, including several new extended case studies such as water contamination in Flint, Michigan; microplastics pollution; West Africa's Ebola crisis; and the Zika epidemic. The book contains more than one hundred figures, including new and updated maps, data graphics, and photos. The book is designed to be used as the core text for a health geography course for undergraduate and lower-level graduate students and is relevant to students of biology, medicine, entomology, social science, urban planning, and public health.

This text presents epidemiologic methods for studying injuries and evaluating interventions to prevent them. It explains how to formulate research questions, the sources of reliable and valid data, and the best choice of research methods. The difficulties of applying rates and ratios to the evaluation of programs are discussed, and the use of economic concepts and policy analysis is covered. It provides specific objectives for research in the various stages of injury control planning and implementation, including the types of data needed to reach the objectives. This third edition is fully updated throughout with new studies used as discussion examples. The chapters have been reorganised into more precise topic areas, for ease of reference.

Viruses do not behave as other microbes; their life cycles require infecting healthy cells, commandeering their cellular apparatus, replicating and then killing the host cell. Methods for virus detection and identification have been developed only in the past few decades. These recently developed methods include molecular, physical, and proteomic techniques. All these approaches (Electron Microscopy, Molecular, Direct Counting, and Mass Spectrometry Proteomics) to detection and identification are reviewed in this succinct volume. It is written in approachable language with enough detail for trained professionals to follow and want to recommend to others. Key Features Covers common detection methods Reviews the history of detection from antiquity to the present Documents the strengths and weaknesses of various detection methods Describes how to detect newly discovered viruses Recommends specific applications for clinical, hospital, environmental, and public health uses

Striking a balance between theory, application, and programming, Biostatistics in Public Health Using STATA is a user-friendly guide to applied statistical analysis in public health using STATA version 14. The book supplies public health practitioners and students with the opportunity to gain expertise in the application of statistics in epidemiologic studies. The book shares the authors' insights gathered through decades of collective experience teaching in the academic programs of biostatistics and epidemiology. Maintaining a focus on the application of statistics in public health, it facilitates a clear understanding of the basic commands of STATA for reading and saving databases. The book includes coverage of data description, graph construction, significance tests, linear regression models, analysis of variance, categorical data analysis, logistic regression model, poisson regression model, survival analysis, analysis of correlated data, and advanced programming in STATA. Each chapter is based on one or more research problems linked to public health. Additionally, every chapter includes exercise sets for practicing concepts and exercise solutions for self or group study. Several examples are presented that illustrate the applications of the statistical method in the health sciences using epidemiologic study designs. Presenting high-level statistics in an accessible manner across research fields in public health, this book is suitable for use as a textbook for biostatistics and epidemiology courses or for consulting the statistical applications in public health. For readers new to STATA, the first three chapters should be read sequentially, as they form the basis of an introductory course to this software.

It is impossible to reflect on 2020 without discussing Covid-19. The term, literally meaning corona-(CO) virus (VI) disease (D) of 2019, has become synonymous with "the virus", "corona" and "the pandemic". The impact of the virus on our lives is unprecedented in modern human history, in terms of scale, depth and resilience. When compared to other epidemics that have plagued the world in recent decades, Covid-19 is often referred to as being much more "deadly" and is associated with advances in technology which scientists have described as "revolutionary". From politics to economics, spanning families and continents, Covid-19 has unsettled norms: cultural clashes are intensified, politics are even more polarized, and regional tensions and conflicts are on the rise. Global trade patterns and supply chains are increasingly being questioned and redrawn. The world is being atomized, and individuals are forced to accept the "new normal" in their routines. In an attempt to combat the virus and minimize its detrimental effects, countries have undertaken different preventive strategies and containment policies. Some have successfully curbed the spread of Covid-19, while many others remain in limbo, doing their best to respond to outbreaks in cases. To gain a better understanding of how to fight Covid-19, it is imperative to evaluate the success and failures of these approaches. Under what conditions is an approach successful? When should it be avoided? How can this information be used to avoid future pandemics? This volume offers informative comparative case studies that shed light on these key questions. Each country case is perceptively analyzed and includes a detailed timeline, allowing readers to view each response with hindsight and extrapolate the data to better understand what the future holds. Taken as a whole, this collection offers invaluable insight at this critical juncture in the Covid-19 pandemic.

APOLLO'S ARROW offers a riveting account of the impact of the coronavirus pandemic on American society as it unfolded in 2020, and on how the recovery will unfold in the coming years. Drawing on a combination of fascinating case studies and cutting-edge research from a range of scientific disciplines, bestselling author, physician, and sociologist Nicholas Christakis explores what it means to live in a time of plague -- an experience that is paradoxically uncommon to the vast majority of humans who are alive, yet deeply fundamental to our species as a whole. Unleashing new divisions in our society and new opportunities for cooperation, this 21st century pandemic has upended our society in ways that will test, but not vanquish, our already frayed culture's capacity to endure and thrive. Featuring many novel, provocative arguments and vivid examples ranging across medicine, history, sociology, epidemiology, data science, and genetics, APOLLO'S ARROW envisions what happens when the great force of a deadly germ meets the enduring reality of our evolved social nature.

Understanding the underlying principles of statistical techniques and effectively applying statistical methods can be challenging for researchers at all stages of their career. This concise, practical guide uses a simple, engaging approach to take scientists and clinicians working in laboratory-based life science and medical research through the steps of choosing and implementing appropriate statistical methods to analyse results. The author draws on her extensive experience of advising students and researchers over the past 30 years, breaking down complex concepts into easy-to-understand units. Practical examples using free online statistical tools are included throughout, with illustrations and diagrams employed to keep jargon to a minimum. Sample size calculations and considerations are covered in depth, and the book refers to types of data from experiments that clinicians and lab-based scientists are likely to encounter. Straightforward, accessible and encouraging throughout, this is a go-to reference for researchers who want to achieve statistical autonomy.

Social capital is a widely acknowledged candidate for implementing beneficial democratic processes and promoting public health. Healthy ties. Social capital, population health and survival traces the path from the conceptualization to the implementation of social capital. To provide empirical proof of the effects of social capital on public health is a serious challenge and the main focus of the book. In the Nordic countries, personal identification codes linking data from various sources, nation-wide population registers, nationally representative and re-tested health surveys, and the long tradition of epidemiology submit to serve well the research into social capital and public health. Up-to-date longitudinal data on social capital and health outcomes are carefully described and reviewed in this book. In Finland, the Swedish-speaking minority is very long-lived and has better health as compared with the Finnish-speaking majority.

In this second edition of Infectious Diseases and Arthropods, Jerome Goddard summarizes the latest thinking about the biological, entomological, and clinical aspects of the major vector-borne diseases around the world. His book covers mosquito-, tick-, and flea-borne diseases, and a variety of other miscellaneous vector-borne diseases, including Chagas' disease, African sleeping sickness, onchocerciasis, scrub typhus, and louse-borne infections. The author provides for each disease a description of the vector involved, notes on its biology and ecology, distribution maps, and general clinical guidelines for treatment and control. Among the diseases fully discussed are malaria, dengue and yellow fevers, lymphatic filariasis, spotted fevers, ehrlichiosis, lyme disease, tularemia, and plague. Other arthropod-caused or related problems-such as myiasis, imaginary insect or mite infestations, and arthropod stings and bites-are also treated.
At a time when vector-borne diseases are spreading ever more widely, Infectious Diseases and Arthropods provides physicians, infectious disease specialists, medical entomologists, and public health officials with an up-to-date, readily accessible, gold-standard reference source.

This book is a compilation of some of the most remarkable contributions made by scientists currently working in Latin America to the understanding of virus biology, the pathogenesis of virus-related diseases, virus epidemiology, vaccine trials and antivirals development. In addition to recognizing the many fine virologists working in Latin America, Human Virology in Latin America also discusses both the state-of-the-art research and the current challenges that are being faced in the region, in hopes of inspiring young scientists worldwide to become eminent virologists.

This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are explained. Each section includes a set of exercises on the respective topics. Various functions and tools for the analysis of discrete survival data are collected in the R package discSurv that accompanies the book.

Growing public awareness of environmental hazards has increased the demand for investigations into the geographical distribution of disease. Data resulting from studies is not always straightforward to interpret and An Introductory Guide to Disease Mapping aims to explain the basic principles underlying the construction and analysis of disease maps.

• An introduction to new developments in disease mapping
• Comprehensive coverage of an active area of research and development
• Numerous case studies to highlight the application of the techniques discussed

This book describes the molecular biology, pathogenesis, epidemiology, and potential strategies for control of chikungunya virus (CHIKV) infection. It offers insight into the structure and functions of CHIKV proteins as they relate to host response, interaction with the arthropod vector, and vaccination. A detailed account of both the epidemiological outlook and the clinical syndrome of CHIKV infection is provided. The complex host-virus interaction and the signaling pathways that mediate such interactions are also covered. Throughout the book, graphics and charts are used to provide stimulating discussion on important findings in the field of chikungunyalogy. The chapters are written with a global perspective by experts of CHIKV from around the world. This project is especially significant given that CHIKV is a pathogen of worldwide public health concern. Although the presence of CHIKV infection is not global yet, worldwide dissemination is predicted in the future due largely to the lack of effective treatment/therapy, efficient control of transmission, and knowledge about mechanisms of pathogenesis. Additionally, globalization of CHIKV is predicated on its mode of dissemination (mosquito vector) and cross border travel and migration.