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Over the last decades, we have seen more than three dozen new infectious diseases appear, some of which could kill millions of people with one or two unlucky gene mutations or one or two unfavourable environmental changes. The risks of pandemics only increase as the human population grows; therefore to direct our future we should examine our past. Howard Phillips provides the first look into the history of epidemics in South Africa, probing lethal episodes which significantly shaped this society over three centuries.
Focusing on devastating diseases such as smallpox, bubonic plague, Spanish influenza, polio and HIV/Aids, Plague, Pox and Pandemics probes their origin, their catastrophic course and their consequences in both the short and long term. Their impact ranges from the demographic to the political, the social, the economic, the spiritual, the psychological and the cultural. As each of these epidemics occurred at crucial moments in the country's history - early in European colonisation, in the midst of the mineral revolution, during the South African War and World War I, as industrialisation was getting under way, and within the eras of apartheid and post-apartheid - the book also examines how these processes affected and were affected by the five epidemics, thereby adding important dimensions to an understanding of each.
To those who read this book, South African history will not look the same again.
What is the nature of epidemiology? Why is epidemiology so important in the context of health, and particularly public health, in South Africa? How can it help us answer important questions in clinical medicine and public health? Epidemiology: A Research Manual for South Africa 3e provides lecturers with useful resources on which to base introductory Epidemiology and Research Methods courses and helps to answer these questions. Written by South African experts, Epidemiology: A Research Manual for South Africa 3e is aimed at undergraduate or postgraduate students encountering epidemiology and, more generally, quantitative public health research methods for the first time. Epidemiology is taught within the following programmes: MBChB, BCur, Diploma: Primary Health Care, and National Diploma: Environmental Health. It enables readers to evaluate data critically and to report their findings lucidly and accurately.
Cut to the facts about coronavirus in Corona, False Alarm?, the runaway German bestseller. In June 2020, Corona, False Alarm? exploded into the German market, selling 200,000 copies and 75,000 e-books in six weeks. No other topic dominates our attention as much as coronavirus and COVID-19, the infectious disease it triggers. There's been a global deluge of contradictory opinions, fake news, and politically controlled information. Differing views on the dangers posed by the pandemic have led to deep division and confusion, within governments, society, and even among friends and family. In Corona, False Alarm?, award-winning researchers Dr. Sucharit Bhakdi and Dr. Karina Reiss give clarity to these confusing and stressful times. They offer analysis of whether radical protective measures-including lockdown, social distancing, and mandatory masking-have been justified, and what the ramifications have been for society, the economy, and public health. Dr. Bhakdi and Dr. Reiss provide dates, facts, and background information, including: How Covid-19 compares with previous coronaviruses and the flu virus What infection numbers and the death rate really tell us The challenges around lockdown: Were the protective measures justified? Mandatory mask-wearing: Does the science support it? Does the race for vaccine development make sense? What are the chances of success? Will the vaccine be safe? Will people accept it? Corona, False Alarm? provides you with sound information and substantiated facts-and encourages you to form your own opinion on the corona crisis.
Now in its tenth edition, the Oxford Handbook of Clinical Medicine has been fully revised, with five new authors on the writing team bringing content fresh from the bedside. Space has been breathed into the design, with more core material at your fingertips in quick-reference lists and flow diagrams, and key references have been honed to the most up-to-date and relevant. Each page has been updated to reflect the latest changes in practice and best management, and the chapters on gastroenterology, history and examination, infectious disease, neurology, and radiology have been extensively revised. Unique among medical texts, the Oxford Handbook of Clinical Medicine is a complete and concise guide to the core areas of medicine that also encourages thinking about the world from the patient's perspective, offering a holistic, patient-centred approach. Loved and trusted by millions for over three decades, the Oxford Handbook of Clinical Medicine continues to be a truly indispensable companion for the practice of modern medicine.
When an epidemic strikes, media outlets are central to how an outbreak is framed and understood. While reporters construct stories intended to inform the public and convey essential information from doctors and politicians, news narratives also serve as historical records, capturing sentiments, responses, and fears throughout the course of the epidemic.Constructing the Outbreak demonstrates how news reporting on epidemics communicates more than just information about pathogens; rather, prejudices, political agendas, religious beliefs, and theories of disease also shape the message. Analyzing seven epidemics spanning more than two hundred years -- from Boston's smallpox epidemic and Philadelphia's yellow fever epidemic in the eighteenth century to outbreaks of diphtheria, influenza, and typhoid in the early twentieth century -- Katherine A. Foss discusses how shifts in journalism and medicine influenced the coverage, preservation, and fictionalization of different disease outbreaks. Each case study highlights facets of this interplay, delving into topics such as colonization, tourism, war, and politics. Through this investigation into what has been preserved and forgotten in the collective memory of disease, Foss sheds light on current health care debates, like vaccine hesitancy.
With its charismatic leader George Custer and its memorable encounters with Plains Indians, including the Battle of the Little Bighorn, the Seventh Cavalry serves as the iconic regiment in the post-Civil War U.S Army. Voluminous written documentation as well as archaeological and osteological research suggest that the soldiers of the Seventh represented a cross section of the men who joined the army as a whole at the time. In Health of the Seventh Cavalry, editors P. Willey and Douglas D. Scott and their co-contributors - experts in history, medicine, human biology, epidemiology, and human osteology - examine the Seventh's medical records to determine the health of the nineteenth-century U.S. Army, and the prevalence and treatment of the numerous conditions that plagued soldiers during the Indian Wars. Building on previous comparisons of archaeological evidence and medical records, Willey and Scott follow multiple lines of inquiry to assess the health of the Seventh, from its organization in 1866 to its 1884 station on the Northern Great Plains. Pairing general overviews of nineteenth- and twentieth-century health care with essays on malaria, injuries, post-traumatic stress disorder, and other specific ailments, Health of the Seventh Cavalry provides fresh insights into the health, disease, and trauma that the regiment experienced over two decades. More than 100 tables, graphs, and maps track the troops' illnesses and diseases by month, season, year, and location, as well as their stress periods, desertions, and deaths. A glossary of medical terms rounds out the volume. As an ideal exemplar of regiments of its time, the Seventh Cavalry affords scholars and enthusiasts a better understanding of nineteenth-century health and medicine. This volume reveals the struggles that the post-Civil War Seventh, and the entire U.S. Army, faced on the battlefield and elsewhere.
SAS programming is a creative and iterative process designed to empower you to make the most of your organization's data. This friendly guide provides you with a repertoire of essential SAS tools for data management, whether you are a new or an infrequent user. Most useful to students and programmers with little or no SAS experience, it takes a no-frills, hands-on tutorial approach to getting started with the software. You will find immediate guidance in navigating, exploring, visualizing, cleaning, formatting, and reporting on data using SAS and JMP. Step-by-step demonstrations, screenshots, handy tips, and practical exercises with solutions equip you to explore, interpret, process and summarize data independently, efficiently and effectively.
Intended for ethologists and sociologists, this text examines the problem of defining the "meaning of illness", an interpretation developed within a society which can itself be studied and interpreted from without, from a variety of viewpoints depending on the academic discipline to which observation has been allocated; to ethnology, for example, the observation of linear-based societies; to sociology, that of industrial societies. The fact that these distinctions today are called into question is of little importance. They encourage a questioning of the relationships between the respective methods and objectives of the different disciplines. The local interpretation of illness is one thing, but it is quite possible that the interpretation of this interpretation could vary, depending on whether it was the product of different methods - (anthropological, sociological, historical) or on whether it was applied to different societies. The situation may become even more complicated, since the question can always be raised as to whether types of method and types of society are linked, whether one type of society implies one type of method.
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.
Reflecting a sea change in how empirical research has been conducted over the past three decades, Foundations of Agnostic Statistics presents an innovative treatment of modern statistical theory for the social and health sciences. This book develops the fundamentals of what the authors call agnostic statistics, which considers what can be learned about the world without assuming that there exists a simple generative model that can be known to be true. Aronow and Miller provide the foundations for statistical inference for researchers unwilling to make assumptions beyond what they or their audience would find credible. Building from first principles, the book covers topics including estimation theory, regression, maximum likelihood, missing data, and causal inference. Using these principles, readers will be able to formally articulate their targets of inquiry, distinguish substantive assumptions from statistical assumptions, and ultimately engage in cutting-edge quantitative empirical research that contributes to human knowledge.
The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
The success of the Apgar score demonstrates the astounding power of an appropriate clinical instrument. This down-to-earth book provides practical advice, underpinned by theoretical principles, on developing and evaluating measurement instruments in all fields of medicine. It equips you to choose the most appropriate instrument for specific purposes. The book covers measurement theories, methods and criteria for evaluating and selecting instruments. It provides methods to assess measurement properties, such as reliability, validity and responsiveness, and interpret the results. Worked examples and end-of-chapter assignments use real data and well-known instruments to build your skills at implementation and interpretation through hands-on analysis of real-life cases. All data and solutions are available online. This is a perfect course book for students and a perfect companion for professionals/researchers in the medical and health sciences who care about the quality and meaning of the measurements they perform.
Correctly understanding and using medical statistics is a key skill for all medical students and health professionals. In an informal and friendly style, Medical Statistics from Scratch provides a practical foundation for everyone whose first interest is probably not medical statistics. Keeping the level of mathematics to a minimum, it clearly illustrates statistical concepts and practice with numerous real-world examples and cases drawn from current medical literature. Medical Statistics from Scratch is an ideal learning partner for all medical students and health professionals needing an accessible introduction, or a friendly refresher, to the fundamentals of medical statistics.
The role that the social and behavioural sciences play in the daily practice of dentistry is now an essential part of all dentistry training, but it can often seem distant from the reality of daily clinical practice. Dentists often ask: what is sociology? Why do I need to know about psychology? Why do I need sociology and psychology to be an effective dentist? How can they help improve my clinical practice? This new textbook answers these important questions and shows how the social and behavioural sciences can inform the practice of dentistry and allied healthcare services in the twenty-first century. It provides a comprehensive, accessible introduction to sociology and psychology for students and members of the dental team with no prior knowledge of the subject, and although the book assumes little or no previous knowledge of psychology or sociology, it also provides enough depth to meet the needs of those with some background in these fields. Throughout, the links between sociology and psychology and everyday practice are emphasized and explained and theoretical concepts are put into the context of everyday clinical work. The authors have extensive experience in teaching and researching the social and behavioural sciences from undergraduate to post-doctoral levels. This book will be an indispensable teaching aid within dental health education, and other allied health and social care disciplines.
Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including, matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.
Genetic Association Studies is designed for students of public health, epidemiology, and the health sciences, covering the main principles of molecular genetics, population genetics, medical genetics, epidemiology and statistics. It presents a balanced view of genetic associations with coverage of candidate gene studies as well as genome-wide association studies. All aspects of a genetic association study are included, from the lab to analysis and interpretation of results, but also bioinformatics approaches to causality assessment. The role of the environment in genetic disease is also highlighted. Genetic Association Studies will enable readers to understand and critique genetic association studies and set them on the way to designing, executing, analyzing, interpreting, and reporting their own.
This innovative book presents the latest insights into hamstring strain injuries (HSI), one of the most common problems in elite and recreational sport, with a unique focus on prevention and rehabilitation. The research within this area has evolved rapidly over the past 10 years and this text offers a comprehensive overview of the recent and most relevant advances. It fills a gap in the literature, since other books focus on muscle injuries in general and their surgical treatment.Structured around the current evidence in the field, it includes sections on functional anatomy and biomechanics; basic muscle physiology in relation to injury and repair; assessment of risk factors; and factors associated with hamstring strains. It also discusses considerations in relation to acute and chronic injuries and hamstring injury prevention, including pre-season and in-season interventions, as well as management strategies and rehabilitation protocols. The final chapter is devoted to additional interventions when conservative rehabilitation and injury prevention fail. Written by renowned experts in the field, this book will be of great interest to sports physiotherapists, sports physicians, physical trainers and coaches.
With ever-rising healthcare costs, evidence generation through Health Economics and Outcomes Research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. Accordingly, it is now customary for health technology assessment and reimbursement agencies to request for HEOR evidence, in addition to data from clinical trials, to inform decisions about patient access to new treatment options. While there is a great deal of literature on HEOR, there is a need for a volume that presents a coherent and unified review of the major issues that arise in application, especially from a statistical perspective. Statistical Topics in Health Economics and Outcomes Research fulfils that need by presenting an overview of the key analytical issues and best practice. Special attention is paid to key assumptions and other salient features of statistical methods customarily used in the area, and appropriate and relatively comprehensive references are made to emerging trends. The content of the book is purposefully designed to be accessible to readers with basic quantitative backgrounds, while providing an in-depth coverage of relatively complex statistical issues. The book will make a very useful reference for researchers in the pharmaceutical industry, academia, and research institutions involved with HEOR studies. The targeted readers may include statisticians, data scientists, epidemiologists, outcomes researchers, health economists, and healthcare policy and decision-makers.
Taking a comparative approach, this book investigates the ways in which obesity and its susceptibilities are framed in science and policy and how they might work better. Providing a clear, authoritative voice on the debate, the author builds on early work to engage further in ecological and complexity thinking in obesity. Many of the models that have emerged since obesity became a population-level issue are examined, including the energy balance model, and models used to examine human body fatness from a range of perspectives including evolutionary, anthropological, environmental, and political viewpoints. The book is ideal for those working on, or interested in, obesity science, health policy, health economics, evolutionary medicine, medical sociology, nutrition and public health who want to understand the shifts that have taken place in obesity science, policy, and intervention in the past forty years.
From the Department of Epidemiology at Johns Hopkins University and continuing in the tradition of award-winning educator and epidemiologist Dr. Leon Gordis, comes the fully revised 6th Edition of Gordis Epidemiology. This bestselling text provides a solid introduction to basic epidemiologic principles as well as practical applications in public health and clinical practice, highlighted by real-world examples throughout. New coverage includes expanded information on genetic epidemiology, epidemiology and public policy, and ethical and professional issues in epidemiology, providing a strong basis for understanding the role and importance of epidemiology in today's data-driven society. Covers the basic principles and concepts of epidemiology in a clear, uniquely memorable way, using a wealth of full-color figures, graphs, charts, and cartoons to help you understand and retain key information. Reflects how epidemiology is practiced today, with a new chapter organization progressing from observation and developing hypotheses to data collection and analyses. Features new end-of-chapter questions for quick self-assessment, and a glossary of genetic terminology. Provides more than 200 additional multiple-choice epidemiology self-assessment questions online. Enhanced eBook version included with purchase. Your enhanced eBook allows you to access all of the text, figures, and references from the book on a variety of devices.
A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question for this pre-identified population of patients, which treatment is best ? A comprehensive, coherent framework for network meta-analysis (mixed treatment comparisons) is adopted and estimated using Bayesian Markov Chain Monte Carlo methods implemented in the freely available software WinBUGS. Each chapter contains worked examples, exercises, solutions and code that may be adapted by readers to apply to their own analyses. This book can be used as an introduction to evidence synthesis and network meta-analysis, its key properties and policy implications. Examples and advanced methods are also presented for the more experienced reader. Methods used throughout this book can be applied consistently: model critique and checking for evidence consistency are emphasised. Methods are based on technical support documents produced for NICE Decision Support Unit, which support the NICE Methods of Technology Appraisal. Code presented is also the basis for the code used by the ISPOR Task Force on Indirect Comparisons. Includes extensive carefully worked examples, with thorough explanations of how to set out data for use in WinBUGS and how to interpret the output. N etwork Meta-Analysis for Decision Making will be of interest to decision makers, medical statisticians, health economists, and anyone involved in Health Technology Assessment including the pharmaceutical industry.
This 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.
Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
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