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This book covers classic epidemiological designs that use a reference/control group, including case-control, case-cohort, nested case-control and variations of these designs, such as stratified and two-stage designs. It presents a unified view of these sampling designs as representations of an underlying cohort or target population of interest. This enables various extended designs to be introduced and analysed with a similar approach: extreme sampling on the outcome (extreme case-control design) or on the exposure (exposure-enriched, exposure-density, countermatched), designs that re-use prior controls and augmentation sampling designs. Further extensions exploit aggregate data for efficient cluster sampling, accommodate time-varying exposures and combine matched and unmatched controls. Self-controlled designs, including case-crossover, self-controlled case series and exposure-crossover, are also presented. The test-negative design for vaccine studies and the use of negative controls for bias assessment are introduced and discussed.This book is intended for graduate students in biostatistics, epidemiology and related disciplines, or for health researchers and data analysts interested in extending their knowledge of study design and data analysis skills.This book Bridges the gap between epidemiology and the more mathematically oriented biostatistics books. Assembles the wealth of epidemiological knowledge about observational study designs that is scattered over several decades of scientific publications. Illustrates the performance of methods in real research applications. Provides guidelines for implementation in standard software packages (Stata, R). Includes numerous exercises, covering simple mathematical proofs, consideration of proposed or published designs, and practical data analysis.

Now in a fully revised Fourth Edition, Modern Epidemiology remains the gold standard text in this complex and evolving field. This edition continues to provide comprehensive coverage of the principles and methods for the design, analysis, and interpretation of epidemiologic research. Featuring a new format allowing space for margin notes, this edition • Reflects both the conceptual development of this evolving science and the increasing role that epidemiology plays in improving public health and medicine. • Features new coverage of methods such as agent-based modeling, quasi-experimental designs, mediation analysis, and causal modeling. • Updates coverage of methods such as concepts of interaction, bias analysis, and time-varying designs and analysis. • Continues to cover the full breadth of epidemiologic methods and concepts, including epidemiologic measures of occurrence and effect, study designs, validity, precision, statistical interference, field methods, surveillance, ecologic designs, and use of secondary data sources. • Includes data analysis topics such as Bayesian analysis, probabilistic bias analysis, time-to-event analysis, and an extensive overview of modern regression methods including logistic and survival regression, splines, longitudinal and cluster-correlated/hierarchical data analysis, propensity scores and other scoring methods, and marginal structural models. • Summarizes the history, specialized aspects, and future directions of topical areas, including among others social epidemiology, infectious disease epidemiology, genetic and molecular epidemiology, psychiatric epidemiology, injury and violence epidemiology, and pharmacoepidemiology.

Epidemiology: A Research Manual for South Africa offers an applied introduction to epidemiological research methods, for students of various health science disciplines who are required to conduct or reference epidemiological research. Directed at readers who are new to epidemiological theory and practice, the text explains fundamental concepts and methods in a manner that is clear and accessible. The text offers a step-by-step guide to the development of a research protocol and the application of epidemiological methods, and addresses specific content areas and methodologies that are important in contemporary epidemiological research. Examples focus on the South African setting, highlighting regional conditions, diseases and health services. This fourth edition is comprehensively revised to reflect current knowledge and practice, and reflects greater emphasis on the complex burden of disease in South Africa as well as the use of routinely available health data for research purposes. The text includes new chapters on reproductive and perinatal epidemiology as well as injury epidemiology, and offers many new, local examples.

Published in 1986: This book tells the story of how various persons and groups have successfully dealt with a type of problem which may threaten the lives and health of every group of humans – every community. The problem is that of a polluted environment.

A practical introduction to epidemiology, biostatistics, and research methodology for the whole health care community This comprehensive text, which has been extensively revised with new material and additional topics, utilizes a practical slant to introduce health professionals and students to epidemiology, biostatistics, and research methodology. It draws examples from a wide range of topics, covering all of the main contemporary health research methods, including survival analysis, Cox regression, and systematic reviews and meta-analysis—the explanation of which go beyond introductory concepts. This second edition of Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and Statistics also helps develop critical skills that will prepare students to move on to more advanced and specialized methods. A clear distinction is made between knowledge and concepts that all students should ensure they understand, and those that can be pursued further by those who wish to do so. Self-assessment exercises throughout the text help students explore and reflect on their understanding. A program of practical exercises in SPSS (using a prepared data set) helps to consolidate the theory and develop skills and confidence in data handling, analysis, and interpretation. Highlights of the book include: Combining epidemiology and bio-statistics to demonstrate the relevance and strength of statistical methods Emphasis on the interpretation of statistics using examples from a variety of public health and health care situations to stress relevance and application Use of concepts related to examples of published research to show the application of methods and balance between ideals and the realities of research in practice Integration of practical data analysis exercises to develop skills and confidence Supplementation by a student companion website which provides guidance on data handling in SPSS and study data sets as referred to in the text Quantitative Methods for Health Research, Second Edition is a practical learning resource for students, practitioners and researchers in public health, health care and related disciplines, providing both a course book and a useful introductory reference.

This book provides practical knowledge to clinicians and biomedical researchers using biological and biochemical specimen/samples in order to understand health and disease processes at cellular, clinical, and population levels. Concepts and techniques provided will help researchers design and conduct studies, then translate data from bench to clinics in attempt to improve the health of patients and populations. This book presents the extreme complexity of epidemiologic research in a concise manner that will address the issue of confounders, thus allowing for more valid inferences and yielding results that are more reliable and accurate.

Since publication of the first three editions of this hugely successful book, systematic methods of critical appraisal have been accepted as central to healthcare provision, both in critical applications and in a wider health services and community perspective. This new edition builds on the work of the previous editions by presenting a fully updated and accessible system of critical appraisal applicable to clinical, epidemiological, and public health studies, and related fields. The book outlines the systematic review process for the establishment of causal effect within single and multiple studies. Focusing primarily on study design, it covers randomized and non-randomized trials, cohort studies, case-control studies, and surveys, showing the presentation of results including person-time and survival analysis, and issues in the selection of subjects. It then describes the process of detection and assessment of selection biases, observation bias, confounding, chance variation, and how to determine internal validity and external validity (generalizability). Statistical methods are presented in an accessible way, illustrating applications to each study design. Positive features of causation including strength, dose-response, and consistency are also discussed. The final chapters provide six examples of critical appraisals of major studies, encompassing randomized trials, prospective and retrospective cohort studies, and case-control studies. Statistical issues are explained clearly without complex mathematics, and the most useful methods are summarized in the appendix, each with a worked example. Each main chapter includes self-test questions, with answers provided, making the book ideally suited to readers with no prior epidemiological or statistical knowledge. Developed over four editions, Critical Appraisal of Epidemiological Studies and Clinical Trials is an invaluable aid to the effective assessment of new studies in epidemiology, public health, research methods, evidence-based methods, clinical medicine, and environmental health; making it essential reading for postgraduates, practitioners, and policymakers in these fields.

Medical record databases are longitudinal patient record databases that are used by health care providers in caring for their patients and that are anonymized for the purpose of research. Data from such retrospective databases allow for investigations of specific subpopulations, thanks to their size and the length of time covered by them. The Disease Analyzer database (QuintilesIMS) is one of the major European databases. It encompasses real-world data in primary care practices. The Disease Analyzer database has been the basis of a large number of peer-reviewed scientific publications. This book presents several epidemiological and health-economic studies based on the Disease Analyzer database that were published between 2010 and 2016. The book will appeal to all medical, public health and health economic students who want to see examples of studies based on electronic medical records. Clinical and market access departments of pharma companies may also find this book a useful resource.

With the many advances in the control of infectious disease over the last 100 years, the role of epidemiology in public health has transformed significantly. Epidemiologic research now includes the study of acute and chronic diseases, as well as the events, behaviors, and conditions associated with health. From seasoned author Ray Merrill, this text explores how epidemiologic methods are conducted and interpreted. In four sections, Statistical Methods in Epidemiologic Research covers basic concepts in epidemiology and statistics, study designs, statistical techniques and applications, as well as special topics. Key Features: • Includes sections on how specific epidemiologic methods have resulted in findings that have influenced health policy and public health • Offers optional sections involving more advanced methods • At the end of each chapter, an applications section gives the student a clear picture of how epidemiologic methods are applied in real-world situations • Special emphasis is given to interpreting results • SAS code is presented in an appendix that corresponds to assessing selected methods.

Teaches Students How to Perform Spatio-Temporal Analyses within Epidemiological StudiesSpatio-Temporal Methods in Environmental Epidemiology is the first book of its kind to specifically address the interface between environmental epidemiology and spatio-temporal modeling. In response to the growing need for collaboration between statisticians and

This book addresses methodological aspects of epidemiological studies on maternal drug use in pregnancy. Discussing the existing sources of error and how they can produce incorrect conclusions, it examines various epidemiological techniques and assesses their strengths and weaknesses. These refer both to the identification of outcomes (with special emphasis on congenital malformations) and to the types of exposure (drug use). Further, the book discusses the problem of confounding and how to handle it, and provides a simple introduction to statistics. Special situations, e.g. different types of parental exposure, are examined. Lastly, the book discusses pharmacovigilance and the information problem, concluding with a short list of aspects to consider when one wants to evaluate a published paper in the field. Though the book is primarily intended for pharmacologists, gynecologists and obstetricians, it will benefit all doctors working in perinatal care.

An introduction to both the concepts and the application of contemporary epidemiological research with a specifically South African emphasis.

Designing Clinical Research sets the standard for providing a practical guide to planning, tabulating, formulating, and implementing clinical research, with an easy-to-read, uncomplicated presentation. This product incorporates current research methodology--including molecular and genetic clinical research--and offers an updated syllabus for conducting a clinical research workshop. Emphasis is on common sense as the main ingredient of good science. The book explains how to choose well-focused research questions and details the steps through all the elements of study design, data collection, quality assurance, and basic grant-writing.

Routine applications of advanced statistical methods on real data have become possible in the last ten years because desktop computers have become much more powerful and cheaper. However, proper understanding of the challenging statistical theory behind those methods remains essential for correct application and interpretation, and rarely seen in the medical literature. Modern Methods for Epidemiology provides a concise introduction to recent development in statistical methodologies for epidemiological and biomedical researchers. Many of these methods have become indispensible tools for researchers working in epidemiology and medicine but are rarely discussed in details by standard textbooks of biostatistics or epidemiology. Contributors of this book are experienced researchers and experts in their respective fields. This textbook provides a solid starting point for those who are new to epidemiology, and for those looking for guidance in more modern statistical approaches to observational epidemiology. Epidemiological and biomedical researchers who wish to overcome the mathematical barrier of applying those methods to their research will find this book an accessible and helpful reference for self-learning and research. This book is also a good source for teaching postgraduate students in medical statistics or epidemiology.

The book is organized so as to address in separate sections first the preparatory topics of medicine (clinical and epidemiological), science in general, and statistics (mathematical); then topics of epidemiological research proper; and, finally, topics of ‘meta-epidemiological'clinical research. In those two main sections, a further grouping is based on the distraction between objects and methods of study. In this framework, the particular topics are addressed both descriptively and quasi-prescriptively, commonly with a number of explicatory annotations.This book is intended to serve as a handbook for whomever is, in whatever way, concerned with epidemiological or ‘meta-epidemiological'clinical research. But besides this, it is also intended to serve as a textbook for students in introductory courses on ‘epidemiological'research – to which end there is a suggested hierarchy of the concepts that might reasonably be covered.

Bias analysis quantifies the influence of systematic error on an epidemiology study's estimate of association. The fundamental methods of bias analysis in epi- miology have been well described for decades, yet are seldom applied in published presentations of epidemiologic research. More recent advances in bias analysis, such as probabilistic bias analysis, appear even more rarely. We suspect that there are both supply-side and demand-side explanations for the scarcity of bias analysis. On the demand side, journal reviewers and editors seldom request that authors address systematic error aside from listing them as limitations of their particular study. This listing is often accompanied by explanations for why the limitations should not pose much concern. On the supply side, methods for bias analysis receive little attention in most epidemiology curriculums, are often scattered throughout textbooks or absent from them altogether, and cannot be implemented easily using standard statistical computing software. Our objective in this text is to reduce these supply-side barriers, with the hope that demand for quantitative bias analysis will follow.

In this new century mankind faces ever more challenging environmental and publichealthproblems,suchaspollution,invasionbyexoticspecies,theem- gence of new diseases or the emergence of diseases into new regions (West Nile virus,SARS,Anthrax,etc.),andtheresurgenceofexistingdiseases(in?uenza, malaria, TB, HIV/AIDS, etc.). Mathematical models have been successfully used to study many biological, epidemiological and medical problems, and nonlinear and complex dynamics have been observed in all of those contexts. Mathematical studies have helped us not only to better understand these problems but also to?nd solutions in some cases, such as the prediction and control of SARS outbreaks, understanding HIV infection, and the investi- tion of antibiotic-resistant infections in hospitals. Structuredpopulationmodelsdistinguishindividualsfromoneanother- cording to characteristics such as age, size, location, status, and movement, to determine the birth, growth and death rates, interaction with each other and with environment, infectivity, etc. The goal of structured population models is to understand how these characteristics a?ect the dynamics of these models and thus the outcomes and consequences of the biological and epidemiolo- cal processes. There is a very large and growing body of literature on these topics. This book deals with the recent and important advances in the study of structured population models in biology and epidemiology. There are six chapters in this book, written by leading researchers in these areas.

Quantitative Research Methods for Health Professionals: A Practical Interactive Course is a superb introduction to epidemiology, biostatistics, and research methodology for the whole health care community. Drawing examples from a wide range of health research, this practical handbook covers important contemporary health research methods such as survival analysis, Cox regression, and meta-analysis, the understanding of which go beyond introductory concepts. The book includes self-assessment exercises throughout to help students explore and reflect on their understanding and a clear distinction is made between a) knowledge and concepts that all students should ensure they understand and b) those that can be pursued by students who wish to do so. The authors incorporate a program of practical exercises in SPSS using a prepared data set that helps to consolidate the theory and develop skills and confidence in data handling, analysis and interpretation.

This book presents a logical system of critical appraisal, to allow readers to evaluate studies and to carry out their own studies more effectively. This system emphasizes the central importance of cause and effect relationships. Its great strength is that it is applicable to a wide range of issues, and both to intervention trials and observational studies. This system unifies the often different approaches used in epidemiology, health services research, clinical trials, and evidence-based medicine, starting from a logical consideration of cause and effect. The author's approach to the issues of study design, selection of subjects, bias, confounding, and the place of statistical methods has been praised for its clarity and interest. Systematic reviews, meta-analysis, and the applications of this logic to evidence-based medicine, knowledge-based health care, and health practice and policy are discussed. Current and often controversial examples are used, including screening for prostate cancer, publication bias in psychiatry, public health issues in developing countries, and conflicts between observational studies and randomized trials. Statistical issues are explained clearly without complex mathematics, and the most useful methods are summarized in the appendix. The final chapters give six applications of the critical appraisal of major studies: randomized trials of medical treatment and prevention, a prospective and a retrospective cohort study, a small matched case-control study, and a large case-control study. In these chapters, sections of the original papers are reproduced and the original studies placed in context by a summary of current developments.

If you want to achieve something, if you want to write a book, paint a picture, be sure the center of your existence is somewhere else and that it's solidly grounded; only then will you be able to keep your cool and laugh at the attacks that are bound to come. ” P. Feyerabend This is a book about interdisciplinary public health reasoning and epidemic m- th elling, in general, and the study of the infamous 14 century AD Black Death d- aster, in particular. We focus on the intellectual context in which epidemic mod- ling takes place, in a way that accounts for the present-day interdisciplinary and multicultural trends in scientific inquiry. Like most scientific fields, public health research defines itself based on knowledge, which raises serious epistemic and cognitive issues. Therefore, we maintain that for public health modellers to fu- tion in an often complex environment, they should be aware of the divergent c- ceptions of knowledge and the technological changes that these imply, the mul- ple sources of information commonly available and their reliability, the different styles of thinking adopted by the disciplines involved, and the importance of - veloping sound interdisciplinary knowledge integration skills.

This is the first comprehensive text on the methodological issues in epidemiologic research on infectious diseases. It will be an invaluable resource both to students of epidemiology and to established researchers. The authors address such questions as: What needs to be considered when enrolling participants in a study of sexually transmitted diseases? What are common sources of measurement error in population-based studies of respiratory infections? What are some sources of existing data for epidemiologic studies of infectious diseases? Answers to these and many other related questions can be found in this well-organized, comprehensive and authoritative volume - the first to thoroughly address the methodologic issues in conducting epidimiologic research on infectious diseases. The book will be an ideal complement to texts on general epidemiology and infectious disease. An introductory section will make it accessible to a wide variety of disciplines by providing an overview of topics that are foundational to understanding infectious disease epidemiology, such as the immunology of infections, the biology of infectious diseases, and concepts of causation, transmission, and dynamics. The rest of the book is structured around sections on data sources and measurement; methods by transmission type; outbreak investigation and evaluation research; and special topics such as HIV/AIDS research, infections in the elderly, and research collaborations in developing countries.

Focusing on areas of public health practice in which the systematic application of epidemiologic methods can have a large and positive impact, this text applies traditional epidemiologic methods for determining disease etiology to the'real-life'applications of public health and health services research. Brownson and Petitti--true to their belief that epidemiology is the diagnostic discipline of public health--provide a much-needed book that bridges the gap between theoretical epidemiology and public health practice. Their uniquely comprehensive coverage includes a number of topics not traditionally addressed by other epidemiology texts. Twelve chapters offer a thorough, in-depth analysis of the important issues, methods, problems, and limitations within applied epidemiology. Following an introduction, three overview chapters detail study design and interpretation, outbreak and cluster investigations, and public health surveillance. The remaining chapters highlight key issues and provide practical recommendations on eight contemporary topics, such as community intervention trials, outcomes research, risk assessment, screening, and cost-benefit analysis. The editors--both very well-known researchers in the field--have compiled reviews with direct relevance to or a strong basis in epidemiology. All chapters have been authored by recognized authorities in the field of epidemiology and public health. Case studies of actual programs at the end of each chapter illustrate major points and provide a foundation for more detailed discussions. Applied Epidemiology is intended for practitioners in epidemiology, and students in epidemiology and related disciplines that rely heavily on epidemiologic methods and reasoning. It will be a practical and informative tool in academic institutions, federal agencies with significant educational missions, state and local public health agencies, and health care organizations.

In examining the relationship between nutritional exposure and disease aetiology, the importance of a carefully considered experimental design cannot be overstated. A sound experimental design involves the formulation of a clear research hypothesis and the identification of appropriate measures of exposure and outcome. It is essential that these variables can be measured with a minimum of error, whilst taking into account the effects of chance and bias, and being aware of the risk of confounding variables. The first edition of Design Concepts in Nutritional Epidemiology presented a throrough guide to research methods in nutritional epidemiology. Since publication of the 1st edition, we now have a much better understanding of the characteristics of nutritional exposure that need to be measured in order to answer questions about diet-disease relationships. The 2nd edition has been extensively revised to include the most up-to-date methods of researching this relationship. Included are new chapters on qualitative and sociological measures, anthropometric measures, gene-nutrient interactions, and cross-sectional studies. Design Concepts in Nutritional Epidemiology will be an essential text for nutritionists and epidemiologists, helping them in their quest to improve the quality of information upon which important public health decisions are made.