The consequences of childhood obesity are serious and far reaching, with both physical and psychological components that add to its complexity. Childhood Obesity: Contemporary Issues provides an up-to-date account of the increase of obesity in children, its causes, and its prevention. The expert editorial panel has chosen contributors with considerable practical and research experience. They explore why childhood obesity is so difficult to prevent and treat. Focusing less on clinical issues and more on environmental factors, the book brings together social, psychological, biological, and socio-biological approaches to the experience and problem of obesity. Delineating the scope and impact of childhood obesity, the book provides a unique view of the obese child. It examines the link between food intake and physical activity, which are the immediate determinants of energy balance, and discusses how to measure and assess them. The World Health Organization describes obesity as one of today's most blatantly visible - yet most neglected - public health problems. This book highlights obesity in children and discusses the need to develop multifactorial and multi-agency strategic plans to contain this epidemic.

Environmental epidemiology is the study of the environmental causes of disease in populations and how these risks vary in relation to intensity and duration of exposure and other factors like genetic susceptibility. As such, it is the basic science upon which governmental safety standards and compensation policies for environmental and occupational exposure are based. Profusely illustrated with examples from the epidemiologic literature on ionizing radiation and air ollution, this text provides a systematic treatment of the statistical challenges that arise in environmental health studies and the use of epidemiologic data in formulating public policy, at a level suitable for graduate students and epidemiologic researchers.
After a general overview of study design and statistical methods for epidemiology generally, the book goes on to address the problems that are unique to environmental health studies, special-purpose designs like two-phase case-control studies and countermatching, statistical methods for modeling exposure-time-response relationships, longitudinal and time-series studies, spatial and ecologic methods, exposure measurement error, interactions, and mechanistic models. It also discusses studies aimed at evaluating the public health benefits of interventions to improve the environment, the use of epidemiologic data to establish environmental safety standards and compensation policy, and concludes with emerging problems in reproductive epidemiology, natural and man-made disasters like global warming, and the global burden of environmentally caused disease. No other book provides such a broad perspective on the methodological challenges in this field at a level accessible to both epidemiologists and statisticians.

Evidence based medicine is at the core of modern medicine. It involves the integration of individual clinical expertise with the best available clinical evidence from systematic research and patient's values and expectations. Systematic reviews offer a summary of the best available evidence. They are the most reliable and comprehensive statement about what works. Written by clinical academics from Australia, UK, USA, and Switzerland, this contributed volume introduces the readers to the principles and practice of systematic reviews and meta-analysis. It covers the various steps involved in systematic reviews including development of a focused question and the strategy for conducting a comprehensive literature search, identifying studies addressing the underlying question, assessment of heterogeneity and the risk of bias in the included studies, data extraction, and the approach to meta-analysis. Crucial issues such as selecting the model for meta-analysis, generating and interpreting forest plots, assessing the risk of publication bias, cautions in the interpretation of subgroup and sensitivity analyses, rating certainty of the evidence using GRADE guideline, and standardized reporting of meta-analysis (PRISMA) are covered in detail. Every attempt is made to keep the narrative simple and clear. Mathematical formulae are avoided as much as possible. While the focus of this book is on systematic reviews and meta-analyses of randomised controlled trials (RCTs), the gold standard of clinical research, the essentials of systematic reviews of non-RCTs, diagnostic test accuracy studies, animal studies, individual participant data meta-analysis, and network meta-analysis are also covered. Readers from all faculties of medicine will enjoy this comprehensive and reader friendly book to understand the principles and practice of systematic reviews and meta-analysis for guiding their clinical practice and research.

This completely revised and updated edition of an outstanding text addresses the fundamental knowledge of epidemiological methods and statistics that can be applied to evolving systems, programs, technologies, and policies. This edition presents new chapters on causal thinking, ethics, and web resources, analyzes data on multinational increases in poverty and longevity, details the control of transmissible diseases, and explains quality management, and the evaluation of healthcare system performance.

With the exception of a few tropical medicine schools worldwide, current medical education programs include almost zero discussion of the interface between infectious diseases and entomology. That is why this book was initially published in the first edition almost 17 years ago. The third edition of this valuable infectious disease entomology book updates all existing chapters with the newest scientific developments described in the medical and entomological literature in addition to covering 10 entirely new topics not addressed in previous editions, which include: * arthropod identification controversies * early beginnings of public health and disease control * red-meat allergy * updates on vaccine development for dengue and malaria * discussion of Chikungunya and Zika viruses * American Boutonnneuse Fever * the newest controversies in Lyme disease * recent findings of viruses in ticks * bed bug bite reactions * Morgellons disease (an imaginary infectious disease)

While biomedical researchers may be able to follow instructions in the manuals accompanying the statistical software packages, they do not always have sufficient knowledge to choose the appropriate statistical methods and correctly interpret their results. Statistical Thinking in Epidemiology examines common methodological and statistical problems in the use of correlation and regression in medical and epidemiological research: mathematical coupling, regression to the mean, collinearity, the reversal paradox, and statistical interaction. Statistical Thinking in Epidemiology is about thinking statistically when looking at problems in epidemiology. The authors focus on several methods and look at them in detail: specific examples in epidemiology illustrate how different model specifications can imply different causal relationships amongst variables, and model interpretation is undertaken with appropriate consideration of the context of implicit or explicit causal relationships. This book is intended for applied statisticians and epidemiologists, but can also be very useful for clinical and applied health researchers who want to have a better understanding of statistical thinking. Throughout the book, statistical software packages R and Stata are used for general statistical modeling, and Amos and Mplus are used for structural equation modeling.

In the past, disease pattern mapping depended on census tracts based on political units, such as states and counties. However, with the advent of geographic information systems (GIS), researchers can now achieve a new level of precision and flexibility in geographic locating. This emerging technology allows the mapping of many different kinds of geographies, including disease rates in relation to pollution sources. Geocoding Health Data presents a state-of-the-art discussion on the current technical and administrative developments in geographic information science. In particular, it discusses how geocoded residential addresses can be used to examine the spatial patterns of cancer incidence, staging, survival, and mortality. The book begins with an introduction of various codes and their uses, including census geographic, health area, and street level codes. It goes on to describe the specific application of geocodes to cancer, detailing methods, materials, and technical issues. The text illustrates how to compile data maps for analysis and addresses issues, such as mismatch correction and data quality. It describes the current state of geocoding practices and discusses the use of individually geocoded cancer incidences in spatial epidemiology, distance estimation and spatial accessibilities, and tips for handling non-geocoded cases. Special consideration is given to privacy and confidentiality issues by focusing on disclosure limitation methods. With recent disease outbreaks and escalating concerns about bioterrorism, interest in the application of GIS to individual data is growing. The fundamental concepts presented by this book are of great value to anyone trying to understand the causes, prevention, and control of cancer as well as a variety of other diseases.

Statistical Analysis of Contingency Tables is an invaluable tool for statistical inference in contingency tables. It covers effect size estimation, confidence intervals, and hypothesis tests for the binomial and the multinomial distributions, unpaired and paired 2x2 tables, rxc tables, ordered rx2 and 2xc tables, paired cxc tables, and stratified tables. For each type of table, key concepts are introduced, and a wide range of intervals and tests, including recent and unpublished methods and developments, are presented and evaluated. Topics such as diagnostic accuracy, inter-rater reliability, and missing data are also covered. The presentation is concise and easily accessible for readers with diverse professional backgrounds, with the mathematical details kept to a minimum. For more information, including a sample chapter and software, please visit the authors' website.

The book "Parasitic Zoonoses" emphasizes a veterinary and public health perspective of zoonotic parasites. This book is suitable for higher undergraduate and graduate students of zoonoses and public health, veterinary parasitology, parasite epidemiology; public health workers; public health veterinarians; field veterinarians, medical professionals and all others interested in the subject. More than 15 protozoa and 50 other parasitic diseases are zoonotic in nature and all these diseases have been discussed in detail. The first chapter is concerned with classification of zoonotic parasites, food borne, vector borne and occupation related zoonotic parasites. The remaining chapters cover etiology, epidemiology, life cycle, transmission, clinical signs, diagnosis, prevention and control of zoonotic parasites. The text is illustrated with a large number of coloured figures. An alphabetical bibliography for every disease has also been included so that readers have access to further information.

"Provides current models, tools, and examples for the formulation and evaluation of scientific hypotheses in causal terms. Introduces a new method of model parametritization. Illustrates structural equations and graphical elements for complex causal systems."

The concepts of estimands, analyses (estimators), and sensitivity are interrelated. Therefore, great need exists for an integrated approach to these topics. This book acts as a practical guide to developing and implementing statistical analysis plans by explaining fundamental concepts using accessible language, providing technical details, real-world examples, and SAS and R code to implement analyses. The updated ICH guideline raises new analytic and cross-functional challenges for statisticians. Gaps between different communities have come to surface, such as between causal inference and clinical trialists, as well as among clinicians, statisticians, and regulators when it comes to communicating decision-making objectives, assumptions, and interpretations of evidence. This book lays out a path toward bridging some of these gaps. It offers A common language and unifying framework along with the technical details and practical guidance to help statisticians meet the challenges A thorough treatment of intercurrent events (ICEs), i.e., postrandomization events that confound interpretation of outcomes and five strategies for ICEs in ICH E9 (R1) Details on how estimands, integrated into a principled study development process, lay a foundation for coherent specification of trial design, conduct, and analysis needed to overcome the issues caused by ICEs: A perspective on the role of the intention-to-treat principle Examples and case studies from various areas Example code in SAS and R A connection with causal inference Implications and methods for analysis of longitudinal trials with missing data Together, the authors have offered the readers their ample expertise in clinical trial design and analysis, from an industrial and academic perspective.

This volume is comprised of papers presented at the Third International Conference on Pharmacoepidemiology, held September 9-11, 1987, in Minneapolis, Minnesota. The book is divided into four sections, which reflect the four themes of the conference: Social Impact of Pharmacoepidemiology; Drug Epidemiology and the Law; Drug Surveillance; and Drugs, Populations, and Outcomes: Specific Studies. The collection of papers discusses the social and legal impact of epidemiology, the system of checks and balances that is necessary for the field, the importance of core support for researchers, and the goal of an enlightened and informed public, including the media, consumer advocates, and the courts. Contributing authors offer perspectives from academia, practice, government, industry and the law. Numerous tables and figures are included to illustrate many of the papers within the text. This book offers substantial reading for epidemiologists and individuals interested in the field of pharmacoepidemiology.

With COVID-19 sweeping across the globe with near impunity, it is thwarting governments and health organizations efforts to contain it. Not since the 1918 Spanish Flu have citizens of developed countries experienced such a large-scale disease outbreak that is having devastating health and economic impacts. One reason such outbreaks are not more common has been the success of the public health community, including epidemiologists and biostatisticians, in identifying and then mitigating or eliminating the outbreaks. Monitoring the Health of Populations by Tracking Disease Outbreaks: Saving Humanity from the Next Plague is the story of the application of statistics for disease detection and tracking. The work of public health officials often crucially depends on statistical methods to help discern whether an outbreak may be occurring and, if there is sufficient evidence of an outbreak, then to locate and track it. Statisticians also help collect critical information, and they analyze the resulting data to help investigators zero in on a cause for a disease. With the recent outbreaks of diseases such as swine and bird flu, Ebola, and now COVID-19, the role that epidemiologists and biostatisticians play is more important than ever. Features: * Discusses the crucial roles of statistics in early disease detection. * Outlines the concepts and methods of disease surveillance. * Covers surveillance techniques for communicable diseases like Zika and chronic diseases such as cancer. * Gives real world examples of disease investigations including smallpox, syphilis, anthrax, yellow fever, and microcephaly (and its relationship to the Zika virus). Via the process of identifying an outbreak, finding its cause, and developing a plan to prevent its reoccurrence, this book tells the story of how medical and public health professionals use statistics to help mitigate the effects of disease. This book will help readers understand how statisticians and epidemiologists help combat the spread of such diseases in order to improve public health across the world.

This comprehensive text covers the use of SAS for epidemiology and public health research. Developed with students in mind and from their feedback, the text addresses this material in a straightforward manner with a multitude of examples. It is directly applicable to students and researchers in the fields of public health, biostatistics and epidemiology. Through a hands on approach to the use of SAS for a broad number of epidemiologic analyses, readers learn techniques for data entry and cleaning, categorical analysis, ANOVA, and linear regression and much more. Exercises utilizing real-world data sets are featured throughout the book. SAS screen shots demonstrate the steps for successful programming.

SAS (Statistical Analysis System) is an integrated system of software products provided by the SAS institute, which is headquartered in California. It provides programmers and statisticians the ability to engage in many sophisticated statistical analyses and data retrieval and mining exercises. SAS is widely used in the fields of epidemiology and public healthresearch, predominately due to its ability to reliably analyze very large administrative data sets, as well as more commonly encountered clinical trial and observational research data. "

Cardiovascular Implications of Stress and Depression provides an in-depth examination on how exposure to stress influences risk for cardiovascular disease and how depression is associated with this relationship. This authoritative volume examines causal pathways linking stress, depression and cardiovascular disease. In addition, it provides mechanistic insights into how environmental stress can lead to cardiovascular diseases. Current information about mechanistic factors, clinical and epidemiological aspects, and management issues associated with stress/depression are presented. These insights demonstrate how the mechanisms behind chronic stress and depression lead to cardiovascular diseases. In addition, their role in existing diseases (such as obesity, hypertension, and diabetes) is explored.

Orthopoxviruses Pathogenic for Humans covers those viruses capable of causing disease in man, including monkeypox, smallpox, cowpox, and vaccinia. The coverage of each virus is comprehensive, covering the biology, molecular biology, and ecology of the virus as well as the clinical and epidemiological aspects of these viruses in humans and animals. In addition, this volume highlights developments in genetic engineering that are paving the way for potential therapeutic treatments of these viruses.

Anyone who attempts to read genetics or epidemiology research literature needs to understand the essentials of biostatistics. This book, a revised new edition of the successful "Essentials of Biostatistics" has been written to provide such an understanding to those who have little or no statistical background and who need to keep abreast of new findings in this fast moving field. Unlike many other elementary books on biostatistics, the main focus of this book is to explain basic concepts needed to understand statistical procedures.

This Book: Surveys basic statistical methods used in the genetics and epidemiology literature, including maximum likelihood and least squares. Introduces methods, such as permutation testing and bootstrapping, that are becoming more widely used in both genetic and epidemiological research. Is illustrated throughout with simple examples to clarify the statistical methodology. Explains Bayes' theorem pictorially. Features exercises, with answers to alternate questions, enabling use as a course text.

Written at an elementary mathematical level so that readers with high school mathematics will find the content accessible. Graduate students studying genetic epidemiology, researchers and practitioners from genetics, epidemiology, biology, medical research and statistics will find this an invaluable introduction to statistics.

Although the spatial dimension of ecosystem dynamics is now widely recognized, the specific mechanisms behind species patterning in space are still poorly understood and the corresponding theoretical framework is underdeveloped. Going beyond the classical Turing scenario of pattern formation, Spatiotemporal Patterns in Ecology and Epidemiology: Theory, Models, and Simulation illustrates how mathematical modeling and numerical simulations can lead to greater understanding of these issues. It takes a unified approach to population dynamics and epidemiology by presenting several ecoepidemiological models where both the basic interspecies interactions of population dynamics and the impact of an infectious disease are explicitly considered. The book first describes relevant phenomena in ecology and epidemiology, provides examples of pattern formation in natural systems, and summarizes existing modeling approaches. The authors then explore nonspatial models of population dynamics and epidemiology. They present the main scenarios of spatial and spatiotemporal pattern formation in deterministic models of population dynamics. The book also addresses the interaction between deterministic and stochastic processes in ecosystem and epidemic dynamics, discusses the corresponding modeling approaches, and examines how noise and stochasticity affect pattern formation. Reviewing the significant progress made in understanding spatiotemporal patterning in ecological and epidemiological systems, this resource shows that mathematical modeling and numerical simulations are effective tools in the study of population ecology and epidemiology.

Recent advances in genetics over the last quarter of a century, especially in molecular techniques, have dramatically reduced the cost of determining genetic markers and hence opened up a field of research that is increasingly helping to detect, prevent and/or cure many diseases that afflict humans. In Statistical Human Genetics: Methods and Protocols expert researchers in the field describe statistical methods and computer programs in the detail necessary to make them more easily accessible to the beginner analyzing data. Written in the highly successful Methods in Molecular Biology (TM) series format, with examples of running the programs and interpreting the program outputs, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results from human genetic data collected in the laboratory. Thorough and as much as possible intuitive, Statistical Human Genetics: Methods and Protocols aids scientists in understanding the computer programs and analytical procedures they need to use.

Introductory Medical Statistics, now in its third edition, is an introductory textbook on basic statistical techniques. It is written for physicians, surgeons, radiation oncologists, medical physicists, radiographers, hospital administrators, medical statisticians in training, biochemists, and other professionals allied to medicine. It is suitable as a teaching text for clinicians working towards their professional examinations. It is also suitable for Maters degree courses in medical physics. The third edition has been extensively revised and expanded to include: Clinical trial design and analysis] Multivariate analysis Cox proportional hazards model McNemar, Wicoxon, Mann-Whitney, Kruskal-Wallis, Mantel-Haenszel, and Kappa tests Kaplan-Meier survival rates Sensitivity and Specificity Specification of treatment success, cure, and quality of life Risk specification Case-control and cohort epidemiological studies Glossary of terms The major change has been the advent of personal computing, so people rely on the power of their machine, and its software to number crunch. What is missing is that the software may not use the appropriate statistical error standard - Dick Mould

Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: Manipulating and transforming point, areal, and raster data, Bayesian hierarchical models for disease mapping using areal and geostatistical data, Fitting and interpreting spatial and spatio-temporal models with the integrated nested Laplace approximation (INLA) and the stochastic partial differential equation (SPDE) approaches, Creating interactive and static visualizations such as disease maps and time plots, Reproducible R Markdown reports, interactive dashboards, and Shiny web applications that facilitate the communication of insights to collaborators and policymakers. The book features fully reproducible examples of several disease and environmental applications using real-world data such as malaria in The Gambia, cancer in Scotland and USA, and air pollution in Spain. Examples in the book focus on health applications, but the approaches covered are also applicable to other fields that use georeferenced data including epidemiology, ecology, demography or criminology. The book provides clear descriptions of the R code for data importing, manipulation, modelling, and visualization, as well as the interpretation of the results. This ensures contents are fully reproducible and accessible for students, researchers and practitioners.

Apollo's Arrow offers a riveting account of the impact of the coronavirus pandemic as it swept through American society in 2020, and of how the recovery will unfold in the coming years. Drawing on momentous (yet dimly remembered) historical epidemics, contemporary analyses, and cutting-edge research from a range of scientific disciplines, bestselling author, physician, sociologist, and public health expert Nicholas A. 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. Unleashing new divisions in our society as well as opportunities for cooperation, this 21st-century pandemic has upended our lives in ways that will test, but not vanquish, our already frayed collective culture. Featuring new, 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.

"Global Health in Africa" is a first exploration of selected histories of global health initiatives in Africa. The collection addresses some of the most important interventions in disease control, including mass vaccination, large-scale treatment and/or prophylaxis campaigns, harm reduction efforts, and nutritional and virological research.
The chapters in this collection are organized in three sections that evaluate linkages between past, present, and emergent. Part I, "Looking Back," contains four chapters that analyze colonial-era interventions and reflect upon their implications for contemporary interventions. Part II, "The Past in the Present," contains essays exploring the historical dimensions and unexamined assumptions of contemporary disease control programs. Part III, "The Past in the Future," examines two fields of public health intervention in which efforts to reduce disease transmission and future harm are premised on an understanding of the past.
This much-needed volume brings together international experts from the disciplines of demography, anthropology, and historical epidemiology. Covering health initiatives from smallpox vaccinations to malaria control to HIV campaigns, "Global Health in Africa" offers a first comprehensive look at some of global health's most important challenges.
Contributors: James L. A. Webb, Jr.; Guillaume Lachenal; Jennifer Tappan; Tamara Giles-Vernick and Stephanie Rupp; Anne Marie Moulin; Myron Echenberg; Michel Garenne, Alain Giami, and Christophe Perrey; Sheryl McCurdy and Haruka Maruyama

This book describes a wide-ranging set of research approaches which have been used to study the health care problems of adults living in rural areas. It shows how these approaches can be used to define health care problems, measure levels of illness and health, and evaluate health care practices. For each approach, contributors provide a theoretical background from the health care delivery literature, details of how it can be carried out in the field, its strengths and weaknesses, and illustrative examples from both the literature and their own work.

This updated second edition of Molecular Typing in Bacterial Infections, presented in two volumes, covers both common and neglected bacterial pathogenic agents, highlighting the most effective methods for their identification and classification in the light of their specific epidemiology. New chapters have been included to add new species, as well as another view of how bacterial typing can be used. These books are valuable resources for the molecular typing of infectious disease agents encountered in both research and hospital clinical laboratory settings, as well as in culture collections and in the industry. Each of the 21 chapters provides an overview of specific molecular approaches to efficiently detect and type different bacterial pathogens. The chapters are grouped in five parts, covering respiratory and urogenital pathogens (Volume I), and gastrointestinal and healthcare-associated pathogens, as well as a new group of vector-borne and Biosafety level 3 pathogens including a description of typing methods used in the traditional microbiology laboratory in comparison to molecular methods of epidemiology (Volume II). Comprehensive and updated, Molecular Typing in Bacterial Infections provides state-of-the-art methods for accurate diagnosis and for the correct classification of different types which will prove to be critical in unravelling the transmission routes of human pathogens.