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This textbook provides the basic concepts of epidemiology while preparing readers with the skills of applying statistical tools in real-life situations. Students, in general, struggle with statistical theories and their practical applications. This book makes statistical concepts easy to understand by focusing on real-life examples, case studies, and exercises. It also provides step-by-step guides for data analysis and interpretation using standard statistical software such as SPSS, SAS, R, Python, and GIS as appropriate, illustrating the concepts. Through the book's 23 chapters, readers primarily learn how to apply statistical methods in epidemiological studies and problem-solving. Among the topics covered: Clinical Trials Epidemic Investigation and Control Geospatial Applications in Epidemiology Survival Analysis and Applications Using SAS and SPSS Systematic Review and Meta-Analysis: Evidence-based Decision-Making in Public Health Missing Data Imputation: A Practical Guide Artificial Intelligence and Machine Learning Multivariate Linear Regression and Logistics Regression Analysis Using SAS Each chapter is written by eminent scientists and experts worldwide, including contributors from institutions in the United States, Canada, Bangladesh, India, Hong Kong, Malaysia, and the Middle East. Statistical Approaches for Epidemiology: From Concept to Application is an all-in-one book that serves as an essential text for graduate students, faculty, instructors, and researchers in public health and other branches of health sciences, as well as a useful resource for health researchers in industry, public health and health department professionals, health practitioners, and health research organizations and non-governmental organizations. The book also will be helpful for graduate students and faculty in related disciplines such as data science, nursing, social work, environmental health, occupational health, computer science, statistics, and biology. .

Epidemiology. --- Statistics. --- Public health. --- Public Health. --- Applied Statistics. --- Epidemiology Statistical methods.

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Statistics as Topic --- Biometry --- Epidemiology --- Cohort Studies --- Cohort analysis --- methods --- Statistical methods --- Statistics as Topic - methods --- Biometry - methods --- Epidemiology - Statistical methods --- EPIDEMIOLOGY --- STATISTICS & NUMERICAL DATA

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Epidemiology --- Oncology. Neoplasms --- Mathematical statistics --- Kanker --- Medisch onderzoek --- Cancer --- Recherche médicale --- Research --- Statistical methods --- Proefdieren. Kanker. --- Cancer. Recherche scientifique. --- Animaux de laboratoire. Cancer. --- Kanker. Wetenschappelijk onderzoek. --- Cancer - Research - Statistical methods --- Cancer - Epidemiology - Statistical methods --- NEOPLASMS --- WORLD HEALTH ORGANIZATION --- EPIDEMIOLOGY --- STATISTICS

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Mathematical and Statistical Estimation Approaches in Epidemiology compiles t- oretical and practical contributions of experts in the analysis of infectious disease epidemics in a single volume. Recent collections have focused in the analyses and simulation of deterministic and stochastic models whose aim is to identify and rank epidemiological and social mechanisms responsible for disease transmission. The contributions in this volume focus on the connections between models and disease data with emphasis on the application of mathematical and statistical approaches that quantify model and data uncertainty. The book is aimed at public health experts, applied mathematicians and sci- tists in the life and social sciences, particularly graduate or advanced undergraduate students, who are interested not only in building and connecting models to data but also in applying and developing methods that quantify uncertainty in the context of infectious diseases. Chowell and Brauer open this volume with an overview of the classical disease transmission models of Kermack-McKendrick including extensions that account for increased levels of epidemiological heterogeneity. Their theoretical tour is followed by the introduction of a simple methodology for the estimation of, the basic reproduction number,R . The use of this methodology 0 is illustrated, using regional data for 1918–1919 and 1968 in uenza pandemics.

Epidemiology --Mathematics. --- Epidemiology --Statistical methods. --- Epidemiology --- Statistics as Topic --- Epidemiologic Methods --- Public Health --- Health Care Evaluation Mechanisms --- Investigative Techniques --- Mathematics --- Environment and Public Health --- Natural Science Disciplines --- Quality of Health Care --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Disciplines and Occupations --- Health Care Quality, Access, and Evaluation --- Health Care --- Mathematical Statistics --- Epidemiology & Epidemics --- Physical Sciences & Mathematics --- Health & Biological Sciences --- Statistical methods --- Emerging infectious diseases. --- Epidemiology. --- Medicine. --- Statistics. --- Statistical analysis --- Statistical data --- Statistical science --- Clinical sciences --- Medical profession --- Emerging infections --- New infectious diseases --- Re-emerging infectious diseases --- Reemerging infectious diseases --- Mathematics. --- Infectious diseases. --- Probabilities. --- Probability Theory and Stochastic Processes. --- Biomedicine general. --- Infectious Diseases. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Econometrics --- Diseases --- Public health --- Human biology --- Life sciences --- Medical sciences --- Pathology --- Physicians --- Communicable diseases --- Distribution (Probability theory. --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Health Workforce --- Statistics . --- Biomedicine, general. --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk

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The development of powerful computing environment and the geographical information system (GIS) in recent decades has thrust the analysis of geo-referenced disease incidence data into the mainstream of spatial epidemiology. This book offers a modern perspective on statistical methods for detecting disease clustering, an indispensable procedure to find a statistical evidence on aetiology of the disease under study. With increasing public health concerns about environmental risks, the need for sophisticated methods for analyzing spatial health events is immediate. Furthermore, the research area of statistical methods for disease clustering now attracts a wide audience due to the perceived need to implement wide-ranging monitoring systems to detect possible health-related events such as the occurrence of the severe acute respiratory syndrome (SARS), pandemic influenza and bioterrorism As an invaluable resource for a wide range of audience including public health researchers, epidemiologists and biostatistians, this book features: A concise introduction to basic concepts of disease clustering/clusters A historical overview of methods for disease clustering A detailed treatment of selected methods useful for practical investigation of disease clustering Analysis and illustration of methods for a variety of real data sets Toshiro Tango, Ph.D., is the Director of Department of Technology Assessment and Biostatistics of National Institute of Public Health, Japan. He has published a number of methodological and applied articles on various aspects of biostatistics. He is Past President of the Japanese Region of the International Biometric Society. He has served as Associate Editor for several journals including Statistics in Medicine and Biometrics.

Biometry -- methods -- Encyclopedias -- English. --- Genetic epidemiology -- Statistical methods. --- Genetics, Medical -- Encyclopedias -- English. --- Human genetics. --- Epidemiology --- Cluster analysis --- Statistics as Topic --- Public Health --- Decision Support Techniques --- Investigative Techniques --- Cluster Analysis --- Data Interpretation, Statistical --- Epidemiologic Methods --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Health Care Evaluation Mechanisms --- Medical Informatics Applications --- Environment and Public Health --- Quality of Health Care --- Medical Informatics --- Health Care --- Information Science --- Health Care Quality, Access, and Evaluation --- Mathematics --- Epidemiology & Epidemics --- Mathematical Statistics --- Physical Sciences & Mathematics --- Health & Biological Sciences --- Statistical methods --- Cluster analysis. --- Statistical methods. --- Mathematics. --- Cancer research. --- Public health. --- Epidemiology. --- Biostatistics. --- Probabilities. --- Statistics. --- Probability Theory and Stochastic Processes. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Public Health. --- Cancer Research. --- Correlation (Statistics) --- Multivariate analysis --- Spatial analysis (Statistics) --- Distribution (Probability theory. --- Oncology. --- Tumors --- Diseases --- Public health --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Statistics . --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Cancer research --- Community health --- Health services --- Hygiene, Public --- Hygiene, Social --- Public health services --- Public hygiene --- Social hygiene --- Health --- Human services --- Biosecurity --- Health literacy --- Medicine, Preventive --- National health services --- Sanitation