Basic Epidemiology And Biostatistics

This text is an easy-to-understand, application-oriented guidebook for learning the basic principles of epidemiologic investigation. Numerous opportunities are presented to apply and test learning through problems and application exercises. Answers are provided.

Basic epidemiology provides an introduction to the core principles and methods of epidemiology, with a special emphasis on public health applications in developing countries. This edition includes chapters on the nature and uses of epidemiology; the epidemiological approach to defining and measuring the occurrence of health-related states in populations; the strengths and limitations of epidemiological study designs; and the role of epidemiology in evaluating the effectiveness and efficiency of health care. The book has a particular emphasis on modifiable environmental factors and encourages the application of epidemiology to the prevention of disease and the promotion of health, including environmental and occupational health.

Basic Epidemiology and Biostatistics: A Practical Guide integrates biostatistics, epidemiology and their applications to public health, clinical, and social science projects. The book describes the role of epidemiological methods through selection of study design and project execution, interpretation optimum interpretation of statistical techniques, and the clinical/ public health significance of the results. The book also provides analysis of statistical software outcomes and their interpretations, includes guidance for critical evaluation of published scientific reports, and provides technical aspects for decision making and research communication. Basic Epidemiology and Biostatistics provides information that will help public health, health care, and biomedical researchers in planning of their research, its execution and in-depth analysis of the data, and presenting the output from statistical testing. Offers an amalgamation of epidemiology and biostatistics principles Presents a selection of optimum research methodology Provides guidance for the interpretation of data for statistical and clinical significance

This book provides not only the theory of biostatistics, but also the opportunity of applying it in practice. In fact, each chapter presents one or more specific examples on how to perform an epidemiological or statistical data analysis and includes download access to the software and databases, giving the reader the possibility of replicating the analyses described.

You'll find the latest on healthcare policy and financing, infectious diseases, chronic disease, and disease prevention technology.

Epidemiologic studies provide research strategies for investigating public health and scientific questions relating to the factors that cause and prevent ailments in human populations. Statistics in Epidemiology: Methods, Techniques and Applications presents a comprehensive review of the wide range of principles, methods and techniques underlying prospective, retrospective and cross-sectional approaches to epidemiologic studies. Written for epidemiologists and other researchers without extensive backgrounds in statistics, this new book provides a clear and concise description of the statistical tools used in epidemiology. Emphasis is given to the application of these statistical tools, and examples are provided to illustrate direct methods for applying common statistical techniques in order to obtain solutions to problems. Statistics in Epidemiology: Methods, Techniques and Applications goes beyond the elementary material found in basic epidemiology and biostatistics books and provides a detailed account of techniques:

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.

This book will familiarize your students with basic principles of epidemiology and biostatistics. Designed for use in a single course, it will clarify the distinction and complementary roles of epidemiology and biostatistics in a range of settings, and train students on the complementary roles epidemiology and biostatistics play in carrying out selected activities in the health professions.

Written by renowned epidemiologists and public health experts, this unique text provides complete, concise coverage of epidemiology, biostatistics, preventive medicine, and public health in clear, easy-to-understand terms. One convenient volume delivers must-know content in four complex areas—information that’s sure to be covered in today’s classrooms and on USMLE exams—presented with a clinical focus and real-life medical examples throughout. Depth of coverage, concise writing style, outstanding online review questions, a clinical emphasis ... these features and more make Jekel's your go-to resource for learning, study, and review. Focuses on clinical problem solving and decision making using epidemiologic concepts and examples. Contains more clinical cases throughout, including global examples. Offers expanded coverage of the impact of big data and precision medicine, as well as an updated and reorganized biostatistics section. Features quick-reference boxes that showcase key concepts and calculations, and dynamic illustrations that facilitate learning using a highly visual approach. Provides almost 300 multiple-choice chapter review questions and answers in print, with additional questions and more online at Student Consult. Aligns content to board blueprints for the USMLE as well as the three specialties certified by the American Board of Preventive Medicine: Occupational Medicine, and Public Health & General Preventive Medicine—and is recommended by the ABPM as a top review source for its core specialty examination. Enhanced eBook version included with purchase. Your enhanced eBook allows you to access all the text, figures, and references from the book on a variety of devices. Evolve Instructor site, with an image and table bank as well as chapter overviews as PowerPoints, is available to instructors through their Elsevier sales rep or via request at: https://evolve.elsevier.com.

Traditionally, the public health viewpoint on disability was geared toward primary prevention of disabling conditions or events. More recently, with the movement for disability rights and the emergence of disability studies, the challenge to the field has been to promote positive health outcomes in this underserved community. Such a change in public health culture must start at the educational level, yet training programs have generally been slow in integrating this perspective—with its potential for enriching the field—into their curricula. Public Health Perspectives on Disability meets this challenge with an educational framework for rethinking disability in public health study and practice, and for attaining the competencies that should accompany this knowledge. This reference balances history and epidemiology, scientific advances, advocacy and policy issues, real-world insights, and progressive recommendations, suiting it especially to disability-focused courses, or to add disability-related content to existing public health programs. Each chapter applies awareness and understanding of disabled persons’ experience to one of the core curriculum areas, including: Health services administration, Environmental health science and occupational health, Health law and ethics, The school as physical setting, Maternal, child, and family health, Disasters and disability. In Public Health Perspectives on Disability, faculty, researchers, administrators, and students in graduate schools of public health throughout the U.S. will find a worthy classroom text and a robust source of welcome—and much needed—change.

Jekel's Epidemiology, Biostatistics, Preventive Medicine, and Public Health is the only textbook that combines the disciplines of medical epidemiology, biostatistics, preventive medicine, and public health in one convenient resource. Written by renowned epidemiologists and public health experts, this text presents the information you need with a clinical focus, using real-life medical examples throughout. With review questions in each chapter to maximize knowledge retention and target key areas of review, it serves as an outstanding resource for USMLE prep - and is recommended by the American Board of Preventive Medicine as a top review source for its core specialty examination! Grasp and retain vital information easily thanks to quick-reference boxes that showcase key concepts and calculations; succinct text; and dynamic illustrations that facilitate learning in a highly visual approach. Spend more time reviewing and less time searching thanks to an extremely focused, "high-yield" presentation. Deepen your understanding of complex epidemiology and biostatistics concepts through clinically focused, real-life examples. Gauge your mastery of public health concepts and build confidence with case-based questions - now accessed online for a more interactive experience - that provide effective chapter review and help you target key areas for further study. Keep up with the very latest in public health and preventive health - areas that have shown great growth in recent years. New coverage includes the epidemiology of mental health disorders, disaster planning, health care reform, and the 'One Health' concept that highlights the indelible links among the health of people, other species, and the planet itself. Access the complete contents online at Student Consult, plus additional tables and images, supplemental information on the One Health Initiative, the latest childhood immunization schedules, chapter highlights in PowerPoint, 300 multiple-choice chapter review questions and answers, a 177-question comprehensive review exam, and more!

Background; Definitions of populations and samples; Measures of location and dispersion; Data presentation; The normal distribution; Mechanics of conducting medical investigations; Design of experiments; Preparing a study protocol; Designing a questionnaire; Coding of data; Introduction to demography in medicine; Procedures for hypothesis testing; Standard error of the mean; Hypothesis-testing concepts; Z and t test - Comparing two or more groups; Percentages and the binomial distribution; Chi square; Correlation and regression; Nonparametric techniques; Rates; ratios; and standardization; Relative risk and measures of strength of associaion; Survival curves; Bibliography; Appendix; Index.

This is a concise introduction to epidemiology and biostatistics written specifically for medical students and first-time learners of clinical research methods. It presents the core concepts of epidemiology and of biostatistics and illustrates them with extensive examples from the clinical literature. It is the only book on the market written to speak directly to medical students and first-time biomedical researchers by using language and examples that are easy to understand. This newly updated second edition is extensively rewritten to provide the clearest explanations and examples. There is also a sister-text, a 150-problem workbook of practice problems that can be purchased alongside this textbook. The author continues to provide a text that is attractively fast-paced and concise for use in condensed courses, such as those taught in medical school. The book is an excellent review for the epidemiology section of the United States Medical Licensing Examination Part I which all medical students must take at the end of the second year.

A one-stop guide for public health students and practitioners learning the applications of classical regression models in epidemiology This book is written for public health professionals and students interested in applying regression models in the field of epidemiology. The academic material is usually covered in public health courses including (i) Applied Regression Analysis, (ii) Advanced Epidemiology, and (iii) Statistical Computing. The book is composed of 13 chapters, including an introduction chapter that covers basic concepts of statistics and probability. Among the topics covered are linear regression model, polynomial regression model, weighted least squares, methods for selecting the best regression equation, and generalized linear models and their applications to different epidemiological study designs. An example is provided in each chapter that applies the theoretical aspects presented in that chapter. In addition, exercises are included and the final chapter is devoted to the solutions of these academic exercises with answers in all of the major statistical software packages, including STATA, SAS, SPSS, and R. It is assumed that readers of this book have a basic course in biostatistics, epidemiology, and introductory calculus. The book will be of interest to anyone looking to understand the statistical fundamentals to support quantitative research in public health. In addition, this book: • Is based on the authors’ course notes from 20 years teaching regression modeling in public health courses • Provides exercises at the end of each chapter • Contains a solutions chapter with answers in STATA, SAS, SPSS, and R • Provides real-world public health applications of the theoretical aspects contained in the chapters Applications of Regression Models in Epidemiology is a reference for graduate students in public health and public health practitioners. ERICK SUÁREZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. He received a Ph.D. degree in Medical Statistics from the London School of Hygiene and Tropical Medicine. He has 29 years of experience teaching biostatistics. CYNTHIA M. PÉREZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. She received an M.S. degree in Statistics and a Ph.D. degree in Epidemiology from Purdue University. She has 22 years of experience teaching epidemiology and biostatistics. ROBERTO RIVERA is an Associate Professor at the College of Business at the University of Puerto Rico at Mayaguez. He received a Ph.D. degree in Statistics from the University of California in Santa Barbara. He has more than five years of experience teaching statistics courses at the undergraduate and graduate levels. MELISSA N. MARTÍNEZ is an Account Supervisor at Havas Media International. She holds an MPH in Biostatistics from the University of Puerto Rico and an MSBA from the National University in San Diego, California. For the past seven years, she has been performing analyses for the biomedical research and media advertising fields.

A one-stop guide for public health students and practitioners learning the applications of classical regression models in epidemiology This book is written for public health professionals and students interested in applying regression models in the field of epidemiology. The academic material is usually covered in public health courses including (i) Applied Regression Analysis, (ii) Advanced Epidemiology, and (iii) Statistical Computing. The book is composed of 13 chapters, including an introduction chapter that covers basic concepts of statistics and probability. Among the topics covered are linear regression model, polynomial regression model, weighted least squares, methods for selecting the best regression equation, and generalized linear models and their applications to different epidemiological study designs. An example is provided in each chapter that applies the theoretical aspects presented in that chapter. In addition, exercises are included and the final chapter is devoted to the solutions of these academic exercises with answers in all of the major statistical software packages, including STATA, SAS, SPSS, and R. It is assumed that readers of this book have a basic course in biostatistics, epidemiology, and introductory calculus. The book will be of interest to anyone looking to understand the statistical fundamentals to support quantitative research in public health. In addition, this book: • Is based on the authors’ course notes from 20 years teaching regression modeling in public health courses • Provides exercises at the end of each chapter • Contains a solutions chapter with answers in STATA, SAS, SPSS, and R • Provides real-world public health applications of the theoretical aspects contained in the chapters Applications of Regression Models in Epidemiology is a reference for graduate students in public health and public health practitioners. ERICK SUÁREZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. He received a Ph.D. degree in Medical Statistics from the London School of Hygiene and Tropical Medicine. He has 29 years of experience teaching biostatistics. CYNTHIA M. PÉREZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. She received an M.S. degree in Statistics and a Ph.D. degree in Epidemiology from Purdue University. She has 22 years of experience teaching epidemiology and biostatistics. ROBERTO RIVERA is an Associate Professor at the College of Business at the University of Puerto Rico at Mayaguez. He received a Ph.D. degree in Statistics from the University of California in Santa Barbara. He has more than five years of experience teaching statistics courses at the undergraduate and graduate levels. MELISSA N. MARTÍNEZ is an Account Supervisor at Havas Media International. She holds an MPH in Biostatistics from the University of Puerto Rico and an MSBA from the National University in San Diego, California. For the past seven years, she has been performing analyses for the biomedical research and media advertising fields.