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Epidemiology Kept Simple: An Introduction to Traditional and Modern Epidemiology, 2nd Edition

ISBN: 978-0-471-40028-8
436 pages
September 2003
Epidemiology Kept Simple: An Introduction to Traditional and Modern Epidemiology, 2nd Edition (0471400289) cover image
Arranged to facilitate use and highlight key concepts, this clear and concise text also includes many practical exercises, case studies, and real-world applications. Utilizing the modern biostatistical approach to studying disease, Epidemiology Kept Simple, Second Edition will provide readers with the tools to interpret epidemiological data, understand disease concepts, and prepare for board exams. The author fully explains all new terminology and minimizes the use of technical language, while emphasizing real-life practice in modern public health and biomedical research settings.
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Preface to the Second Edition.

Preface to the First Edition.

Acknowledgments.

1. Epidemiology Past and Present.

1.1 Epidemiology, Public Health, and Health.

1.2 Uses of Epidemiology.

1.3 Epidemiologic Transition.

1.4 Selected Historical Figures and Events.

2. Causal Concepts.

2.1 Natural History of Disease.

2.2 Spectrum of Disease and “the Iceberg”.

2.3 Causal Concepts.

2.4 Epidemiologic Variables.

3. The Infectious Disease Process.

3.1 The Infectious Disease Process.

3.2 Herd Immunity.

4. Screening for Disease.

4.1 Introduction.

4.2 Reproducibility.

4.3 Validity.

4.4 Relation Between Prevalence of Disease and Predictive Value of a Test.

4.5 Selecting a Cutoff for Positive and Negative Test Results.

4.6 Summary.

Chapter Addendum (Case Study): Screening for Antibodies to the Human Immunodeficiency Virus.

5. Case Definitions and Disease Classification.

5.1 Case Defin itions.

5.2 International Classification of Disease.

5.3 Artifactual Fluctuations in Reported Rates.

5.4 Summary.

6. Incidence and Prevalence.

6.1 Background.

6.2 Incidence Proportion (Risk, Cumulative Incidence).

6.3 Incidence Rate (Incidence Density).

6.4 Prevalence.

7. Rate Adjustment.

7.1 Introduction.

7.2 Direct Adjustment.

7.3 Indirect Adjustment.

7.4 Adjustment for Multiple Factors.

7.5 Summary.

8. Measures of Association and Potential Impact.

8.1 Introduction.

8.2 Absolute Measures of Association.

8.3 Relative Measures of Association.

8.4 Measures of Potential Impact.

9. Types of Epidemiologic Studies.

9.1 Stages of Study and Hypothesis Statement.

9.2 Taxonomy of Study Design.

10. Experimental Study Designs.

10.1 Introduction.

10.2 Selected Concepts.

10.3 Clinical Trials as a Point of Reference.

11. Observational Study Designs.

11.1 Introduction.

11.2 Aggregate-Level (Ecological) Studies.

11.3 Cross-Sectional Studies.

11.4 Cohort Studies.

11.5 Case–Control Studies.

11.6 Comparison of Randomized Trials, Cohort Studies, and Case–Control Studies.

12. Error in Epidemiologic Research.

12.1 Introduction.

12.2 Random Error.

12.3 Systematic Error.

13. Confidence Intervals and p Values.

13.1 Introduction.

13.2 Confidence Intervals.

13.3 p Values.

13.4 Minimum Bayes Factors.

14. Mantel–Haenszel Methods.

14.1 Ways to Prevent Confounding.

14.2 Simpson’s Paradox.

14.3 Mantel–Haenszel Methods for Risk Ratios.

14.4 Mantel–Haenszel Methods for Other Measures of Association.

15. Statistical Interaction.

15.1 Two Types of Interaction.

15.2 Chi-Square Test for Statistical Interaction.

15.3 Strategy for Stratified Analysis.

16. From Association to Causation.

16.1 Introduction.

16.2 Report of the Advisory Committee to the U.S. Surgeon General, 1964.

16.3 Hill’s Framework.

17. Survival Analysis.

17.1 Introduction.

17.2 Stratifying Rates by Follow-up Time.

17.3 Actuarial Method of Survival Analysis.

17.4 Kaplan–Meier Method of Survival Analysis.

17.5 Comparing the Survival Experience of Two Groups.

18. Current Life Tables.

18.1 Introduction.

18.2 Complete Life Table.

18.3 Abridged Life Table.

19. Random Distribution of Cases in Time and Space.

19.1 Introduction.

19.2 The Poisson Distribution.

19.3 Goodness of Fit of the Poisson Distribution.

19.4 Summary.

20. Outbreak Investigation.

20.1 Background.

20.2 Investigatory Steps.

Chapter Addendum 1 (Case Study): Drug–Disease Outbreak.

Chapter Addendum 2 (Case Study): Food-Borne Outbreak in Rhynedale, California.

Appendix 1. 95% Confidence Limits for Poisson Counts.

Appendix 2. Tail Areas in the Standard Normal (Z) Distribution: Double There Areas for Two-Sided p Values.

Appendix 3. Right-Tail Areas in Chi-Square Distributions.

Appendix 4. Case Study—Cigarette Smoking and Lung Cancer.

Appendix 5. Case Study—Tampons and Toxic Shock Syndrome.

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B. Burt (“Bud”) Gerstman has a Ph.D. in Epidemiology and Comparative Pathology from the University of California, Davis, a MPH in Epidemiology from the University of California at Berkeley, and a Doctor of Veterinary Medicine degree from Cornell University. He teaches courses in epidemiology, biostatistics, and public health statistics at San Jose State University in Northern California. Before coming to SJSU in 1990, he was a Fellow of the National Institutes of Health - U.S. Public Health Service Epidemiology Training Program and a member of the faculty at the Graduate School at National Institutes of Health. He has won numerous awards and is widely published. His most recent project was the development and publication of an epidemiology textbook and he is currently at work on a text on data analysis.
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"…remains a key textbook for introducing the subject to students and self-learners with little previous exposure to epidemiology or health-related research." (Clinical Chemistry, November 2004)

“This is a fun book to read and provides a ‘light version’ of a specialty that often becomes ‘heavy’ and over burdensome...a wonderful beginning text and information source...Nicely done!” (Veterinary and Human Toxicology, Vol. 46, No. 2, April 2004)

"This should become THE epidemiology text."
--Paul M. Gahlinger, MD, PhD, Department of Family and Preventive Medicine, University of Utah

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Epidemiology Kept SimpleVisit the companion site for supplemental materials.
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