Re: Epidemiology Beyond The Basics Pdf
Sibyl Piccuillo
This text is a sophisticated treatment of the issues that arise and methods that are employed when epidemiologists seek to measure disease risk and to investigate the complex determinants of risk. The purpose is to serve as an intermediate text, a bridge between the basics and the specialized texts that focus on specific methods or research designs. The real contribution is that the authors integrate and unify the treatment of these methods and their interpretation from the perspective of experienced epidemiologists, not merely data analysts. They present the full range of issues in this book in a way that is accessible to all, yet they avoid oversimplification. The audience for this gap-filling book is diverse, spanning the range from students enrolled in a second course in epidemiology, to practitioners who may use the book as a reference, to teachers of epidemiology. The book fills a niche in the field of epidemiology texts because it represents a unified presentation of advanced concepts in measurement of risk and association within the context of the principal study designs. The concepts of bias, confounding, and interaction are addressed in depth, as is their impact on study validity and causative reasoning. The treatment of the impact of time, including age, secular trend, and cohort effects is excellent, as is the discussion of stratification and regression-based modeling in accounting for confounding and effect modification. I only wish the authors had included a chapter on screening and prevention. Although this book is likely to be a standard addition to the library of most students and practitioners in the field of epidemiology, its clarity and richness of content makeit attractive to any health professional. This book fills a unique niche and therefore has little direct competition. The books that overlap somewhat include Kahn and Sempos's Statistical Methods in Epidemiology (Monographs in Epidemiology and Biostatistics, Vol. 12), (Oxford Univ Press 1989) and Selvin's Statistical Analysis of Epidemiologic Data (Monographs in Epidemiology and Biostatistics, Vol. 25) (Oxford Univ Press, 1996). However, these are more descriptions of methods and thus lack the rich discussion of the role of these methods and the issues they address in the broader context of epidemiological reasoning.
This intermediate-level text explores key epidemiologic concepts and basic methods in more depth than basic texts. Moyses and Nieto (epidemilogy, Johns Hopkins School of Hygiene and Public Health) present nine chapters that discuss cohort and nested case-control studies, birth cohort analysis, ecological studies, cumulative incidence, measures of association, confounding, interaction, reliability and validity measure, forms of bias, and other topics. Complex concepts such as confounding, interactions, and statistical modeling are illustrated with graphics, diagrams, and examples. Annotation c. Book News, Inc., Portland, OR (booknews.com)
Reviewer: Robert McCarter, ScD (University of Maryland at Baltimore School of Medicine)
Description: This text is a sophisticated treatment of the issues that arise and methods that are employed when epidemiologists seek to measure disease risk and to investigate the complex determinants of risk.
Purpose: The purpose is to serve as an intermediate text, a bridge between the basics and the specialized texts that focus on specific methods or research designs. The real contribution is that the authors integrate and unify the treatment of these methods and their interpretation from the perspective of experienced epidemiologists, not merely data analysts. They present the full range of issues in this book in a way that is accessible to all, yet they avoid oversimplification.
Audience: The audience for this gap-filling book is diverse, spanning the range from students enrolled in a second course in epidemiology, to practitioners who may use the book as a reference, to teachers of epidemiology.
Features: The book fills a niche in the field of epidemiology texts because it represents a unified presentation of advanced concepts in measurement of risk and association within the context of the principal study designs. The concepts of bias, confounding, and interaction are addressed in depth, as is their impact on study validity and causative reasoning. The treatment of the impact of time, including age, secular trend, and cohort effects is excellent, as is the discussion of stratification and regression-based modeling in accounting for confounding and effect modification. I only wish the authors had included a chapter on screening and prevention.
Assessment: Although this book is likely to be a standard addition to the library of most students and practitioners in the field of epidemiology, its clarity and richness of content make it attractive to any health professional. This book fills a unique niche and therefore has little direct competition. The books that overlap somewhat include Kahn and Sempos's Statistical Methods in Epidemiology (Monographs in Epidemiology and Biostatistics, Vol. 12), (Oxford Univ Press 1989) and Selvin's Statistical Analysis of Epidemiologic Data (Monographs in Epidemiology and Biostatistics, Vol. 25) (Oxford Univ Press, 1996). However, these are more descriptions of methods and thus lack the rich discussion of the role of these methods and the issues they address in the broader context of epidemiological reasoning.
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Life course epidemiology seeks to understand how determinants of health and disease interact across the span of a human life, and has made significant contributions to understanding etiological mechanisms in many chronic diseases, including schizophrenia. The life course approach is ideal for understanding depression: causation in depression appears to be multifactorial, including interactions between genes and stressful events, or between early life trauma and later stress in life; timing of onset and remission of depression varies widely, indicating differing trajectories of symptoms over long periods of time, with possible differing causes and differing outcomes; and early life events and development appear to be important risk factors for depression, including exposure to acute and chronic stress in the first years of life. To better understand etiology and outcome of depression, future research must move beyond basic epidemiologic techniques that link specific exposures to specific outcomes and embrace life course principles and methods. Time-sensitive modelling techniques that are able to incorporate multiple interacting factors across long periods of time, such as structural equation models, will be critical in understanding the complexity of causal and influencing factors from early development to the end stages of life. Using these models to identify key pathways that influence trajectories of depression across the life course will help guide prevention and intervention.
This unit of study is intended for students who have completed Epidemiology Methods and Uses (or an equivalent unit of study) at a credit or higher level. It is designed to extend students' practical and theoretical knowledge of epidemiology beyond basic principles and in particular to give them a practical understanding of how epidemiological principles and practices are used in real world settings. Students are given an opportunity to acquire some of the practical knowledge and skills needed to undertake epidemiological research and also to consolidate their critical appraisal skills. Attendance is expected at ALL classes.
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
Here, I briefly introduce to you the authors and their written work published in Issue II of Consilience. These authors are students and professors of health, economics, social psychology, epidemiology, political science, transitional justice, Asian studies, and pastoral development. Like many of our readers, they are also development practitioners, who work at field study schools, research universities and with governmental agencies around the world.
To return to our understanding of sustainable development as thesustainability of opportunity, it is my hope that you will join us in commenting on each piece through this provided online medium and encouraging the growth of vast opportunities: in research methods, for actors involved in drafting policies, and in academic dialogue. We know that the opportunities must continue to grow in the context of real-world poverty alleviation projects, legislation for environmental governance, and provisions beyond basic needs.
The second, third and any subsequent fellowship years are devoted to developing your research expertise. Fellows enjoy access to top-notch research resources and facilities and benefit from the mentorship of our world-class research faculty while pursuing research projects that help to improve the outlook for patients at St. Jude and around the world.
Fellows interested in careers as clinical investigators gain formal clinical research training through early involvement in ongoing clinical trials within the institution. For example, fellows may participate in the development of new institutional protocols or conduct retrospective hypothesis-driven studies. We strongly encourage fellows in the clinical research track to pursue advanced degrees in clinical research or epidemiology.
This track is geared toward fellows aiming to become independent academic investigators. Fellows are trained in the techniques and methods used to illuminate the molecular mechanisms behind cancer or blood disorders or work to translate basic research findings into clinic-ready cures and diagnostic tools.