This book grew out of the discussions and presentations that began during the Workshop on Emerging and Reemerging Diseases (May 17-21, 1999) sponsored by the Institute for Mathematics and its Application (IMA) at the University of Minnesota with the support of NIH and NSF. The workshop started with a two-day tutorial session directed to ecologists, epidemiologists, immunologists, mathematicians, and scientists interested in the study of disease dynamics. The core of this second volume, Volume 126, covers research contributions on the use of dynamical systems (deterministic discrete, delay, PDEs, and ODEs models) and stochastic models in disease dynamics. Contributions motivated by the study of diseases like influenza, HIV, tuberculosis, and macroparasitic like schistosomiasis are also included. This second volume requires additional mathematical sophistication, and graduate students in applied mathematics, scientists in the natural, social, and health sciences, or mathematicians who want to enter the field of mathematical and theoretical epidemiology will find it useful. The collection of contributors includes many who have been in the forefront of the development of the subject.

First published in 1889, this book provides a guide to vital statistics- the science of numbers applied to the life-history of communities and nations- in relation to medical problems. Chapters cover a wide variety of categories including population, births and deaths, sickness, occupation and mortality, and mortality from special diseases.

Despite adults' best preventive efforts, childhood obesity is on the rise in most areas of the world, and with it the prevalence of Type 2 diabetes, hypertension, cardiovascular disease, and other formerly adult-onset conditions. Epidemiology of Obesity in Children and Adolescents takes the global ecological approach that is needed to understand the scope of the problem and its multiple causes and mechanisms, and to aid in developing more effective prevention and intervention programs. In the book's first half, experts present a descriptive summary of youth obesity trends in ten world regions, broken down by age group, gender, socioeconomic status, and risk factors. Complementing these findings, part two reviews the evidence base regarding the variables, separately and in combination, having the most significant impact on young people's development of obesity, including: * Genetic and nutrigenomic factors. * Environmental and psychosocial factors, such as family shopping and eating habits and access to healthful foods. * Neuroendocrine regulation. * Prenatal and neonatal factors (e.g., gestational diabetes of the mother). * Dietary factors, from nutrient content to young people's food preferences. * Physical activity versus sedentary behavior. Epidemiology of Obesity in Children and Adolescents is necessary reading for the range of professionals involved in curtailing this epidemic, including public health specialists, epidemiologists, pediatricians, nurses, nutritionists, psychologists, health educators, and policymakers.

This book grew out of the discussions and presentations that began during the Workshop on Emerging and Reemerging Diseases (May 17-21, 1999) sponsored by the Institute for Mathematics and its Application (IMA) at the University of Minnesota with the support of NIH and NSF. The workshop started with a two-day tutorial session directed to ecologists, epidemiologists, immunologists, mathematicians, and scientists interested in the study of disease dynamics. The core of this first volume, Volume 125, covers tutorial and research contributions on the use of dynamical systems (deterministic discrete, delay, PDEs, and ODEs models) and stochastic models in disease dynamics. The volume includes the study of cancer, HIV, pertussis, and tuberculosis. Beginning graduate students in applied mathematics, scientists in the natural, social, or health sciences or mathematicians who want to enter the fields of mathematical and theoretical epidemiology will find this book useful.

This book provides a practical guide to analysis of simple and complex method comparison data, using Stata, SAS and R. It takes the classical Limits of Agreement as a starting point, and presents it in a proper statistical framework. The model serves as a reference for reporting sources of variation and for providing conversion equations and plots between methods for practical use, including prediction uncertainty.Presents a modeling framework for analysis of data and reporting of results from comparing measurements from different clinical centers and/or different methods.Provides the practical tools for analyzing method comparison studies along with guidance on what to report and how to plan comparison studies and advice on appropriate software.Illustrated throughout with computer examples in R.Supported by a supplementary website hosting an R-package that performs the major part of the analyses needed in the area.Examples in SAS and Stata for the most common situations are also provided.Written by an acknowledged expert on the subject, with a long standing experience as a biostatistician in a clinical environment and a track record of delivering training on the subject.

Biostatisticians, clinicians, medical researchers and practitioners involved in research and analysis of measurement methods and laboratory investigations will benefit from this book. Students of statistics, biostatistics, and the chemical sciences will also find this book useful.

This book describes some recent trends in GCM research on different subject areas, both theoretical and applied. This includes tools and possibilities for further work through new techniques and modification of existing ones. A growth curve is an empirical model of the evolution of a quantity over time. Growth curves in longitudinal studies are used in disciplines including biology, statistics, population studies, economics, biological sciences, sociology, nano-biotechnology, and fluid mechanics. The volume includes original studies, theoretical findings and case studies from a wide range of applied work. This volume builds on presentations from a GCM workshop held at the Indian Statistical Institute, Giridih, January 18-19, 2014. This book follows the volume Advances in Growth Curve Models, published by Springer in 2013. The results have meaningful application in health care, prediction of crop yield, child nutrition, poverty measurements, estimation of growth rate, and other research areas.

Examines the advent, during the mid-nineteenth century in Britain, of techniques of infectious disease surveillance, now one of the most powerful sets of tools in modern public health. Intrusive Interventions is a history and critical study of public health in the Victorian and Edwardian period. Drawing on an array of archival sources from across provincial England and London, it investigates the emergence and consolidation of a set of government policies that came to be known as infectious disease surveillance, including compulsory infectious disease notification, domestic quarantine, mandatory removal to a hospital, contact tracing, and the disinfection of homes and belongings. Although these were a set of spatialized practices implemented in diverse settings such as hospitals, schools, and disinfecting stations, their effect was to retrain the gaze of public health onto domestic space and in the process both disrupt and reinforce the centrality of the family and domesticity in Victorian and Edwardian culture. Examining political ideologies of freedom and individuality as well associal policy, medical theory, laboratory research, material culture, and public health practice, author Graham Mooney argues that infectious disease surveillance reconfigured late nineteenth-century hygienic norms and forms of citizenship. Public health practice had to be continually reshaped in order to negate the political fallout of a tendency toward coercion and unwanted interference -- debates that, as the author of this important study points out,continue to resonate today. Graham Mooney is Assistant Professor at the Institute of the History of Medicine, Johns Hopkins University.

Although medicine and sanitation in modernized countries are more advanced than ever before, over the past three decades we have seen the emergence of some 30 new diseases, such as HIV, SARS and Ebola. Lyme Disease, hepatitis C, Legionnaires' Disease and even Jacob-Creutzfeld, the human form of a disorder we know as "Mad Cow," have made headlines. We are also facing a resurgence of diseases once thought nearly eradicated, including tuberculosis and smallpox, and the persistence of rare disorders such as leprosy. In this work, Dr. Link explains the extent of new, resurgent, and resistant diseases defying the abilities of science and medicine, or often finding strength in globalization or other facets of modernization. Link also explains why such diseases are not prevented by our current systems, and why some rare diseases persist despite technology that could cure them. He offers insight into why we may not be able to predict or prevent factors such as mutations, and also shares thoughts about what we can do--as individuals, communities and countries--to reduce the dangers of disease. Including a basic review of elements that cause them--viruses, bacteria, parasites, and fungi among them--this work gives a brief history of human diseases and points out how the burden of disease has increased throughout the history of mankind. Diseases addressed in this book include, but are not limited to: BLMad Cow BLTuberculosis BLRabies BLSARS BLEbola BLLeprosy BLSmallpox BLDracunculiasis BLRingworm BLMalaria

This book is devoted to Corrado Gini, father of the Italian statistical school. It celebrates the 50th anniversary of his death by bearing witness to the continuing extraordinary scientific relevance of his interdisciplinary interests. The book comprises a selection of the papers presented at the conference of the Italian Statistical Society, Statistics and Demography - the Legacy of Corrado Gini, held in Treviso in September 2015. The work covers many topics linked to Gini's scientific legacy, ranging from the theory of statistical inference to multivariate statistical analysis, demography and sociology. In this volume, readers will find many interesting contributions on entropy measures, permutation procedures for the heterogeneity test, robust estimation of skew-normal parameters, S-weighted estimator, measures of multidimensional performance using Gini's delta, small-sample confidence intervals for Gini's gamma index, Bayesian estimation of the Gini-Simpson index, spatial residential patterns of selected foreign groups, minority segregation processes, dynamic time warping to study cruise tourism, and financial stress spill over. This book will appeal to all statisticians, demographers, economists, and sociologists interested in the field.

This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel's first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed.

In this intimate history of the extraordinary Black Plague pandemic that swept through the British Isles in 1665, Evelyn Lord focuses on the plague's effects on smaller towns, where every death was a singular blow affecting the entire community. Lord's fascinating reconstruction of life during plague times presents the personal experiences of a wide range of individuals, from historical notables Samuel Pepys and Isaac Newton to common folk who tilled the land and ran the shops. She brings this dark era to vivid life through stories of loss and survival from those who grieved, those who fled, and those who hid to await their fate.

It is a truism among biologists that an organism's phenotype is the product of both its genotype and its environment. An organism's genotype contains the total informational potential of the individual, while its environment shapes the expression of the ge- type, influences the rate of mutation and occurrence of modifications, and ultimately determines the likelihood that the genotype (or fractions thereof) will survive into the next generation. In the relationship between host and pathogen, therefore, each forms a part of the environment of the other, mutually influencing the biology of both partners on scales ranging from the life history of individuals to the fate of populations or entire species. Molecular biologists working on problems in pathogenesis generally think of the host organism as the pathogen's environment and perhaps occasionally consider the pathogen as part of the host's environment. However, because "environment" can be defined at many scales, so, too, can phenotypes: if a pathogen, as a species, is c- sidered to exist in a host, as a species, then among its phenotypes is the nature of the pandemic disease it can cause within the host community. The contributors to the proceedings of this NATO Advanced Research Workshop have treated the interplay of environment and genotype in the host-pathogen relationship and its relationship to the problem of emerging infectious disease at both the macroscopic and microscopic/ molecular levels along this continuum of scale (with some human history thrown in at times for good measure).

"Methods of Clinical Epidemiology" serves as a text on methods useful to clinical researchers. It provides a clear introduction to the common research methodology specific to clinical research for both students and researchers. This book sets out to fill the gap left by texts that concentrate on public health epidemiology and focuses on what is not covered well in such texts. The four sections cover methods that have not previously been brought together in one text and serves as a second level textbook of clinical epidemiology methodology. This book will be of use to postgraduate students in clinical epidemiology as well as clinical researchers at the start of their careers.

This book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike. Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK.

In recent decades radiobiologists' efforts have been directed at identifying the mechanisms of radiation effects; the general mechanisms have since been studied extensively. This book describes and analyzes radiation-induced adaptation as processes produced in cells, tissues, and populations. This viewpoint helps to understand the nature and factors of induced processes, to determine the characteristics of observed radiation effects and their limitations. The investigations presented here were founded on proper lab experiments, ecological studies of plant population growth near an operating nuclear power plant and a thorough epidemiological examination of human populations living in territories polluted fifty years ago, as well as on relevant published data. This research demonstrates the radiation-induced adaptation processes that continue even when the radiation itself is no longer at a critical background level. The investigations utilized the method of statistical modeling on the basis of distributions on the number of abnormalities. This method allows us to investigate the processes induced by low-dose factors when accompanied by Darwinian selection in different systems; the distribution parameters can then be used to study the characteristics of adaptation processes and system resistance. The consequences of background-level radiation continue to provoke debate, and the mathematical bases of the adaptation model are shown, while due consideration is paid to the components of adaptation: instability, selection, and proliferation. The book will be especially useful to specialists in radiation pollution, ecology, epidemiology, and radiology for studies of radiation-induced processes; the method presented here can also be adapted to investigate low-dose effects in other fields. In addition, the book presents a number of reviews in the fields of radiation biology, including pioneering investigations in Russia which were previously unavailable to Western scientists.

Plasma decontamination is a rapidly expanding area of modern science and engineering. An increasing number of engineers are using plasma methods for decontamination of chemical and biological agents. Plasma decontamination is effectively applied today to clean and sterilize different surfaces, high volume air and water streams, industrial exhausts, and even living tissue of animals and humans. This book provides a fundamental introduction to virtually all aspects of modern plasma decontamination, as well as the most recent technological achievements in the area.

The book is segmented into four specific sections of modern plasma decontamination: (1) plasma bio-decontamination, including disinfection and sterilization of surfaces, water and air streams; (2) plasma decontamination of chemical agents, including cleaning of air, water, and industrial exhaust gases from different pollutants and especially volatile organic compounds VOC; (3) plasma treatment of living tissue, including different subjects of plasma medicine from skin sterilization to tissue engineering; (4) major electric discharges applied for the plasma-assisted decontamination of chemical and biological agents.

Hardly a day goes by without news headlines concerning infectious disease threats. Currently the spectre of a pandemic of influenza A-H1N1 is raising its head, and heated debates are taking place about the pro s and con s of vaccinating young girls against human papilloma virus. For an evidence-based and responsible communication of infectious disease topics to avoid misunderstandings and overreaction of the public, we need solid scientific knowledge and an understanding of all aspects of infectious diseases and their control.

The aim of our book is to present the reader with the general picture and the main ideas of the subject. The book introduces the reader to methodological aspects of epidemiology that are specific for infectious diseases and provides insight into the epidemiology of some classes of infectious diseases characterized by their main modes of transmission. This choice of topics bridges the gap between scientific research on the clinical, biological, mathematical, social and economic aspects of infectious diseases and their applications in public health.

The book will help the reader to understand the impact of infectious diseases on modern society and the instruments that policy makers have at their disposal to deal with these challenges. It is written for students of the health sciences, both of curative medicine and public health, and for experts that are active in these and related domains, and it may be of interest for the educated layman since the technical level is kept relatively low."

When plague broke out in Manchuria in 1910 as a result of transmission from marmots to humans, it struck a region struggling with the introduction of Western medicine, as well as with the interactions of three different national powers: Chinese, Japanese, and Russian. In this fascinating case history, William Summers relates how this plague killed as many as 60,000 people in less than a year, and uses the analysis to examine the actions and interactions of the multinational doctors, politicians, and ordinary residents who responded to it. Summers covers the complex political and economic background of early twentieth-century Manchuria and then moves on to the plague itself, addressing the various contested stories of the plague's origins, development, and ecological ties. Ultimately, Summers shows how, because of Manchuria's importance to the world powers of its day, the plague brought together resources, knowledge, and people in ways that enacted in miniature the triumphs and challenges of transnational medical projects such as the World Health Organization.

In the 1970s it seemed infectious diseases had been conquered, but today global epidemics seem to pose a new, more sinister, threat. This fascinating study explores these new infectious diseases, such as Swine Flu, SARS and AIDS, and the re-emergence of old threats, and discusses their role in society.

Statistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine. This volume demonstrates these methods with their conceptual underpinnings and illustration through analysis of real and simulated data. These methods are immediately applicable to the practice of personalized medicine, which is a medical paradigm that emphasizes the systematic use of individual patient information to optimize patient health care. This is the first single source to provide an overview of methodology and results gathered from journals, proceedings, and technical reports with the goal of orienting researchers to the field. The first chapter establishes context for the statistical reader in the landscape of personalized medicine. Readers need only have familiarity with elementary calculus, linear algebra, and basic large-sample theory to use this text. Throughout the text, authors direct readers to available code or packages in different statistical languages to facilitate implementation. In cases where code does not already exist, the authors provide analytic approaches in sufficient detail that any researcher with knowledge of statistical programming could implement the methods from scratch. This will be an important volume for a wide range of researchers, including statisticians, epidemiologists, medical researchers, and machine learning researchers interested in medical applications. Advanced graduate students in statistics and biostatistics will also find material in Statistical Methods for Dynamic Treatment Regimes to be a critical part of their studies.

Medically unexplained somatic symptoms are problematic in psychiatry, primary care settings, and other clinical areas. The burden they impose on health-care systems constitutes a significant public health problem. At the international symposium "Rethinking Somatoform Disorders," this problem was addressed by specialists working in somatoform disorders, psychiatric nosology, epidemiology, and biological and cross-cultural psychiatry. The meeting was the third of the Keio University International Symposia for Life Sciences and Medicine, in collaboration with the World Health Organization and the World Psychiatric Association.

Reactions to pandemics are unlike any other global emergency; with an emphasis on withdrawal and containment of the sight of the infected. Dealing with the historical and conceptual background of diseases in politics and international relations, this volume investigates the global political reaction to pandemic scares. By evaluating anxiety and the political response to pandemics as a legitimisation of the modern state and its ability to protect its citizens from infectious disease, Understanding the Politics of Pandemic Scares examines the connection between international health governance and the emerging Western liberal world order. The case studies, including SARS, Bird Flu and Swine Flu, provide an understanding of how the world order, global health governance and people's bodies interact to produce scares and panics. Aaltola introduces an innovative new concept of politosomatics' based on the relationship that links individual stress, strain, and fear with global circulations of power to evaluate increasingly global bio-political environments in which pandemics exist. This book will be of interest to students and researchers of International Relations, Global Health, International Public Health and Global Health governance.

Examining the principles and methods of research on the evaluation of factors affecting the outcome of illness, this book emphasizes diagnostic and therapeutic interventions--the factors most readily modified by health care providers. The author discusses various ways of structuring observations on patient groups, and appraises the nature and strength of inferences drawn from those observations. He also demonstrates how the results of this type of research--clinical epidemiologic research--can be incorporated into the decision-making process utilized in clinical medicine.
This book contains a concise account of topics such as the assessment of the use of diagnostics and screening tests and their role in improving the outcome of illness, the evaluation of therapeutic efficacy through experimental and nonexperimental studies, and a particularly useful chapter on assessment of therapeutic safety. It is an essential reference and guide to the quantitative assessment of the consequences of illness for clinicians in training or in practice.The new edition of Clinical Epidemiology greatly expands the chapter on randomized control trials, and includes a whole new chapter on meta-analysis, authored by Peter Cummings. Meta-analysis, the statistical synthesis of data from comparable studies, was unheard of 30 years ago, but with the advent of increased computer technology, the method has been steadily growing in importance in the epidemiology community.