Epidemiology, the study of population health by means of group comparisons, is of increasing importance to health policy and medicine, but it has never before received sustained philosophical attention. This book is the first comprehensive philosophical treatment of the science of epidemiology, drawing together material on causation, causal inference, prediction, the interpretation of effect measures, the nature of disease, and legal uses of epidemiological evidence. Old philosophical problems are seen from new angles, especially general causation, causal explanation, and the use of causal knowledge to predict. The conceptual development of epidemiology is invigorated by a critical examination of foundational doctrines. Causal inference, interaction, the interpretation of measures of attributability, risk relativism, and the notion of multifactorial disease are all scrutinized. The attempted use of epidemiological evidence in legal context is also analyzed, along with the philosophical problems it throws up. This book is essential reading for any professional or lay reader with an interest in understanding the conceptual and methodological foundations of epidemiology, as well as its difficulties.

This book provides salient information on all aspects of influenza/flu viruses affecting animals and humans. It specifically reviews the properties and replication of influenza viruses; their evolution and emergence; epidemiology; role of migratory birds in disease transmission; clinical signs in humans, animals, and poultry; pathogenesis and pathogenicity; public health importance and potential threats; diagnosis; prevention and control measures; and pandemic preparedness. Influenza/flu viruses evolve continuously and jump species causing epidemics as well as pandemics in both human and animals. During the past 150 years, various strains of influenza virus like the Spanish flu, Asian flu, Hong Kong flu, bird flu, and swine flu were responsible for high mortality in humans as well as birds. High mutation rates, antigenic shifts, drifts, reassortment phenomena, and the development of antiviral drug resistance all contribute to ineffective chemotherapy and vaccines against influenza viruses. Due to their devastating nature, high zoonotic implications, and high mortality in humans and poultry, they have a severe impact on the socioeconomic status of countries. Disease awareness, rapid and accurate diagnosis, surveillance, strict biosecurity, timely adoption of appropriate preventive and control measures, and pandemic preparedness are crucial to help in decreasing virus transmission, thus reducing clinical cases, deaths, and pandemic threats.

Applying research into assessments of community theatre, epidemiology, and young people's shared and private stories using a wide range of methodologies, this book explores the potential efficacy of community theatre to prevent the spread of HIV/AIDS in Tanzania with reference to several other comparable sites in Africa.

Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of SEM are in the social sciences. In writing this textbook, the authors look to make SEM accessible to a wider audience of researchers across many disciplines, addressing issues unique to health and medicine. SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time and groups. It can be viewed as the merging of a conceptual model, path diagram, confirmatory factor analysis, and path analysis. In this textbook the authors also discuss techniques, such as mixture modeling, that expand the capacity of SEM using a combination of both continuous and categorical latent variables. Features: Basic, intermediate, and advanced SEM topics Detailed applications, particularly relevant for health and medical scientists Topics and examples that are pertinent to both new and experienced SEM researchers Substantive issues in health and medicine in the context of SEM Both methodological and applied examples Numerous figures and diagrams to illustrate the examples As SEM experts situated among clinicians and multidisciplinary researchers in medical settings, the authors provide a broad, current, on the ground understanding of the issues faced by clinical and health services researchers and decision scientists. This book gives health and medical researchers the tools to apply SEM approaches to study complex relationships between clinical measurements, individual and community-level characteristics, and patient-reported scales.

With this book, Siegel, an internationally known demographer and gerontologist, has made a unique contribution to the fledgling fields of health demography, and the demography and epidemiology of aging. The book represents a felicitous union of epidemiology, gerontology, and demography, and appears to be the first and only comprehensive text on this subject now available. Drawing on a wide range of sciences in addition to demography, gerontology, and epidemiology, including medical sociology, biostatistics, public policy, bioethics, and molecular biology, the author treats theoretical and applied issues, links methods and findings, covers the material internationally, nationally, and locally, and while focusing on the elderly, treats the entire life course. The methods, materials, and pespectives of demography and epidemiology are brought to bear on such topics as the prospects for future increases in human longevity, the relative contribution of life style, environment, genetics, and chance in human longevity, the measurement of the share of healthy years in total life expectancy, the role of population growth in the rising costs of health care, and the applications of health demography in serving the health needs of local communities. The separate chapters systematically develop the topics of the sources and quality of health data; mortality, life tables, and the measurement of health status; the interrelationships of health, on the one hand, and mortality, fertility, migration, and age structure, on the other; health conditions in the less developed countries; the concepts and theories of aging and projections of the aged population; and local health applications, public health policy, and bioethical issues in health demography. Given its comprehensiveness, clarity, interdisciplinary scope, and authencity, this book appeals to a wide range of users, from students and teachers of medical sociology, the demography of aging, and public health studies to practitioners in these areas, both as a text in health demography and the demography/epidemiology of aging, and as a reference work in these fields.

This volume contains refereed papers by participants in the two weeks on Clinical Trials and one week on Epidemiology and the Environment held as part of the six weeks workshop on Statistics in the Health Sciences Applications at the Institute for Mathematics and its Applications (IMA) in the summer of 1997. Donald Berry was in charge of the weeks on clinical trials, and Elizabeth Halloran organized the week on epidemiology and the environment. The collection includes a major contribution from Jamie Robins, Andrea Rotnitzky, and Daniel Scharfstein on sensitivity analysis for selection bias and unmeasured confounding in missing data and causal and inference models. In another paper, Jamie Robins presents a new class of causal models called marginal structural models. Alan Hubbard, Mark van der Laan, and Jamie Robins present a methodology for consistent and efficient estimation of treatment-specific survival functions in observational settings. Brian Leroux, Xingye Lei, and Norman Breslow present a new mixed model for spatial dependence for estimating disease rates in small areas. Andrew Lawson and Allan Clark demonstrate Markov Chain Monte Carlo methods for clustering in spatial epidemiology. Colin Chen, David Chock, and Sandra Winkler present a simulation study examining confounding in estimation of the epidemiologic effect of air pollution. Dalene Stangl discusses issues in the use of reference priors and Bayes factors in analyzing clinical trials. Stephen George reviews the role of surrogate endpoints in cancer clinical trials.

The main purpose of this book is to describe ways of assessing forensic science evidence and the means of communicating this assessment to a court of law. A clear exposition of probability from the Bayesian perspective is provided. The underlying theme of the book is the emphasis on the importance, for the assessment of the value of associative evidence linking a suspect and a crime scene, or the comparison of two probabilities, the first being that of the evidence if the suspect is guilty, the second being that of the evidence if the suspect is innocent. Edited as a joint venture between a statistician and a forensic scientist, contributions from leading researchers in the area have been brought together. Technical expressions are kept to a minimum, with those wanting more information on a particular statistical test being referred to standard textbooks as and when necessary. The editor's aim is to ensure that proper attention is placed on the courts to consideration of the probability of the evidence of association if the suspect is innocent as well as to this probability if the suspect is guilty. The work is intended for forensic science practitioners, legal practitioners, stati

Covid-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting against the virus, enormously tap on the power of AI and its data analytics models for urgent decision supports at the greatest efforts, ever seen from human history. This book showcases a collection of important data analytics models that were used during the epidemic, and discusses and compares their efficacy and limitations. Readers who from both healthcare industries and academia can gain unique insights on how data analytics models were designed and applied on epidemic data. Taking Covid-19 as a case study, readers especially those who are working in similar fields, would be better prepared in case a new wave of virus epidemic may arise again in the near future.

*Provides an overview of statistical and analytic methodologies in real-world evidence to generate insights on healthcare, with a special focus on the pharmaceutical industry *Examines timely topics of high relevance to industry such as bioethical considerations, regulatory standards and compliance requirements *Highlights emerging and current trends, and provides guidelines for best practices *Illustrates methods through examples and use-case studies to demonstrate impact *Provides guidance on software choices and digital applications for successful analytics.

Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient's individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest. Features: All you need to know to correctly make an online risk calculator from scratch Discrimination, calibration, and predictive performance with censored data and competing risks R-code and illustrative examples Interpretation of prediction performance via benchmarks Comparison and combination of rival modeling strategies via cross-validation Thomas A. Gerds is a professor at the Biostatistics Unit at the University of Copenhagen and is affiliated with the Danish Heart Foundation. He is the author of several R-packages on CRAN and has taught statistics courses to non-statisticians for many years. Michael W. Kattan is a highly cited author and Chair of the Department of Quantitative Health Sciences at Cleveland Clinic. He is a Fellow of the American Statistical Association and has received two awards from the Society for Medical Decision Making: the Eugene L. Saenger Award for Distinguished Service, and the John M. Eisenberg Award for Practical Application of Medical Decision-Making Research.

The PCP's Bicentennial Edition Remington: The Science and Practice of Pharmacy, Twenty Third Edition, offers a trusted, completely updated source of information for education, training, and development of pharmacists. Published for the first time with Elsevier, this edition includes coverage of biologics and biosimilars as uses of those therapeutics have increased substantially since the previous edition. Also discussed are formulations, drug delivery (including prodrugs, salts, polymorphism. With clear, detailed color illustrations, fundamental information on a range of pharmaceutical science areas, and information on new developments in industry, pharmaceutical industry scientists, especially those involved in drug discovery and development will find this edition of Remington an essential reference. Intellectual property professionals will also find this reference helpful to cite in patents and resulting litigations. Additional graduate and postgraduate students in Pharmacy and Pharmaceutical Sciences will refer to this book in courses dealing with medicinal chemistry and pharmaceutics.

Aimed at all types of public health practitioners and theorists, this book is a compilation of methodological and application developments in spatial epidemiological approaches for environmental and public health studies in the Asia Pacific region. It aims to plug a gap in the literature that has seen a shortage of materials documenting the development of health GIS in this crucial part of the world.

A comprehensive overview of the effects of trichloroethylene toxicity caused by real-life exposure levels highlighting how exposure to trichloroethylene may contribute to the etiology of several idiopathic human diseases. Discussion will focus on different kinds of modeling and how they may be used to predict functional consequences and to dissect the contribution of different mechanistic pathways, including potential mechanisms of action for trichloroethylene toxicity in different organ systems. It will explore the role of epigenetic alterations in trichloroethylene toxicity, this provides important mechanistic information and may also provide the basis for intervention therapy. Chapters will also explain how the risks from trichloroethylene exposure may be greater in certain populations based on genetic predisposition, age of exposure and co-exposure to other chemicals With contributions from international experts in the field, Trichloroethylene: Toxicity and Health Risks is an essential resource for researchers and clinicians in toxicology, immunology, medicine and public health as well as industry and government regulatory scientists involved in safety and health protection and epidemiologists, highlighting the need for interdisciplinary cooperation in solving issues of environmental toxicity.

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.

This book comprehensively reviews various vector-borne diseases and their control methods. It discusses morphology, life history, and pathogenicity of protozoan and helminth parasites. Further, it analyzes host-parasite interactions and their adaptation within the host system for understanding parasitic infections. The book discusses the complex life cycle, biochemical adaptations, and molecular biology of the parasites. It investigates the immunological response to different infectious agents and explores new targets for combined therapeutic approaches. It also summarizes the evolution of parasitism and the ecology of parasites of the different phylum. Lastly, it provides information on vector biology emphasizing the role of basic vector research in developing future disease control methods and improving upon the existing approaches.

This innovative textbook brings together modern concepts in mathematical epidemiology, computational modeling, physics-based simulation, data science, and machine learning to understand one of the most significant problems of our current time, the outbreak dynamics and outbreak control of COVID-19. It teaches the relevant tools to model and simulate nonlinear dynamic systems in view of a global pandemic that is acutely relevant to human health. If you are a student, educator, basic scientist, or medical researcher in the natural or social sciences, or someone passionate about big data and human health: This book is for you! It serves as a textbook for undergraduates and graduate students, and a monograph for researchers and scientists. It can be used in the mathematical life sciences suitable for courses in applied mathematics, biomedical engineering, biostatistics, computer science, data science, epidemiology, health sciences, machine learning, mathematical biology, numerical methods, and probabilistic programming. This book is a personal reflection on the role of data-driven modeling during the COVID-19 pandemic, motivated by the curiosity to understand it.

This book addresses the COVID-19 pandemic from a quantitative perspective based on mathematical models and methods largely used in nonlinear physics. It aims to study COVID-19 epidemics in countries and SARS-CoV-2 infections in individuals from the nonlinear physics perspective and to model explicitly COVID-19 data observed in countries and virus load data observed in COVID-19 patients. The first part of this book provides a short technical introduction into amplitude spaces given by eigenvalues, eigenvectors, and amplitudes.In the second part of the book, mathematical models of epidemiology are introduced such as the SIR and SEIR models and applied to describe COVID-19 epidemics in various countries around the world. In the third part of the book, virus dynamics models are considered and applied to infections in COVID-19 patients. This book is written for researchers, modellers, and graduate students in physics and medicine, epidemiology and virology, biology, applied mathematics, and computer sciences. This book identifies the relevant mechanisms behind past COVID-19 outbreaks and in doing so can help efforts to stop future COVID-19 outbreaks and other epidemic outbreaks. Likewise, this book points out the physics underlying SARS-CoV-2 infections in patients and in doing so supports a physics perspective to address human immune reactions to SARS-CoV-2 infections and similar virus infections.

This textbook and guide focuses on methodologies for bias analysis in epidemiology and public health, not only providing updates to the first edition but also further developing methods and adding new advanced methods. As computational power available to analysts has improved and epidemiologic problems have become more advanced, missing data, Bayes, and empirical methods have become more commonly used. This new edition features updated examples throughout and adds coverage addressing: Measurement error pertaining to continuous and polytomous variables Methods surrounding person-time (rate) data Bias analysis using missing data, empirical (likelihood), and Bayes methods A unique feature of this revision is its section on best practices for implementing, presenting, and interpreting bias analyses. Pedagogically, the text guides students and professionals through the planning stages of bias analysis, including the design of validation studies and the collection of validity data from other sources. Three chapters present methods for corrections to address selection bias, uncontrolled confounding, and measurement errors, and subsequent sections extend these methods to probabilistic bias analysis, missing data methods, likelihood-based approaches, Bayesian methods, and best practices.

From the President of the Research Society on Alcoholism In recent years, increasingly convincing evidence in support of a biobehavioral conceptual model of the etiology of alcoholism has emerged. In this model, the disorder is perceived as arising from the interaction of geneticlbiological vulnerability and psychosocial risk. Drinking, or alcohol-seeking, is a metric trait. Alcoholism, which is a state of abnormally intense alcohol-seeking be havior that, over time, leads to the alcohol dependence syndrome, lies at the extreme, high end of this quantitative measure. Metric traits are influenced by multiple genes; the extent of genetic loading of biological risk for alcoholism would be different in different individuals. Added to this kind of variability is the wide range of options for exposure to the psychosocial risk factors of heavy drinking provided by modern society. Further, environmental prov ocation also changes when life events change. It is not surprising, therefore, from the combination of the kinds of genetic and environmental variability described above that there is a wide array of patterns of expression of the disorder alcoholism, referred to by some as "alcoholisms. " In the search for understanding of underlying mechanisms and rational bases for potential therapy, it is important to focus our attention on the final common pathway of this disorder, alcohol-seeking behavior. This series, ever since its beginning in 1983, has been sensitive to the complexities of the interaction between biological and psychosocial risk factors in alcoholism."

Immunizationisoneofthegreatadvancesinpublichealth. Figure0. 1showsacamel with a solar-powered refrigerator on his back carrying vaccines across a hot desert to the far reaches of civilization. Many vaccines contain live viruses that need to be kept cold, or the vaccine viruses will die, and the vaccines will lose their ability to produce an immune response. Thus a continuous chain of refrigeration, the cold chain, from the origin to delivery of some vaccines needs to be maintained. The inspiration of the camel image is that it represents the dedication of the world to bring vaccines to everyone. The ?rst major success, and the origin of the word vaccination (vacca for cow), was Jenner's introducing cowpox-based vaccine against smallpox in the late 18th century. After nearly a century hiatus, at the end of the 19th century, inoculations against cholera, typhoid, plague (caused by bacteria) and rabies (caused by a virus) were developed. By the early 20th century, statisticians of the stature of Karl Pe- son, Major Greenwood, and Udny Yule were heartily involved in discussions of evaluating these vaccines in the ?eld. In the 1920s, new vaccines included pert- sis, diptheria, tetanus, and bacille Calmette-Guerin ' against tuberculosis. The 1930s saw development of yellow fever, in?uenza, and rickettsia vaccines. After World War II, the advent of cell cultures in which viruses could grow enabled production of polio vaccine and vaccines against measles, mumps, rubella, varicella, and a- novirus, among others (Plotkin et al 2008).

Over the past fifty years, the case-control method, and to a lesser extent its case-based variants, have become the most important tools for the investigator of health problems. The case control method is the study of persons with the disease and a suitable control group of persons who do not have the disease. The book helps readers address a number of general and specific questions dealing with the case-control and other case-based methods, including questions of how to design and implement a case-control study that minimizes biases, how to analyze the data to appropriately deal with confounding variables and help identify reactions, and how to interpret data and present the results from a case-control study.

In a series of case studies of sexually transmitted disease and HIV/AIDS from around Africa, contributors examine the social, cultural, and political-economic bases of risk, transmission, and response to epidemic disease. This book brings together major contributions to the historical study of epidemic disease in developing countries and considers how particular constellations of cultural, social, political, and economic factors in different countries have affected the historical patterns of disease and collective (official and community) response to them. This book is a companion volume to "Sex, Disease, and Society: A Comparative History of Sexually Transmitted Diseases and HIV/AIDS in Asia and the Pacific" (Greenwood, 1997).

From this endeavor to provide insight into the conjunctions and disjunctions between the histories of STDs and the AIDS pandemic in Sub-Saharan Africa certain common issues have emerged. These include medical ambiguity and epidemiologic diversity; cultural change; racism; gender, labor migration, and economic instability; and the practice of biomedicine and epidemiology in African contexts. All of these factors are embedded in the colonial legacy and post-colonial political economic conditions across the continent.

Now in its second edition, this book provides a state of the art overview on basic concepts of epigenetic epidemiology and a comprehensive review of the rapidly evolving field of human epigenetics. Epigenetics plays an important role in shaping who we are and contributes to our prospects of health and disease. Unlike our genetic inheritance, our epigenome is malleable throughout the lifecourse and is shaped by our environmental experiences. Population-based epidemiologic studies increasingly incorporate epigenetic components. These so called epigenome-wide association studies (EWAS) contribute substantially to our understanding of the relevance of epigenetic marks, such as DNA methylation, histone modification, and non-coding RNAs for disease causation. Written by leading experts in the field, the book opens with a comprehensive introduction of the principles of epigenetic epidemiology and discusses challenges in study design, analysis, and interpretation. It summarizes the latest advances in epigenetic laboratory techniques, the influence of age and environmental factors on shaping the epigenome, the epigenetic clock, and the role of epigenetics in the developmental origins hypothesis. The final part focuses on epigenetic epidemiology of various health conditions such as imprinting disorders, cancer, infectious diseases, inflammation and rheumatoid arthritis, asthma, metabolic disorder and vascular disease, as well as neurodevelopmental and psychiatric disorders. Given its scope, Epigenetic Epidemiology is an indispensable resource for researchers working in the field of human epigenetics.

The current textbook has been written as a help to medical / health professionals and students for the study of modern Bayesian statistics, where posterior and prior odds have been replaced with posterior and prior likelihood distributions. Why may likelihood distributions better than normal distributions estimate uncertainties of statistical test results? Nobody knows for sure, and the use of likelihood distributions instead of normal distributions for the purpose has only just begun, but already everybody is trying and using them. SPSS statistical software version 25 (2017) has started to provide a combined module entitled Bayesian Statistics including almost all of the modern Bayesian tests (Bayesian t-tests, analysis of variance (anova), linear regression, crosstabs etc.). Modern Bayesian statistics is based on biological likelihoods, and may better fit clinical data than traditional tests based normal distributions do. This is the first edition to systematically imply modern Bayesian statistics in traditional clinical data analysis. This edition also demonstrates that Markov Chain Monte Carlo procedures laid out as Bayesian tests provide more robust correlation coefficients than traditional tests do. It also shows that traditional path statistics are both textually and conceptionally like Bayes theorems, and that structural equations models computed from them are the basis of multistep regressions, as used with causal Bayesian networks.