Epidemiology Kept Simple : An Introduction to Traditional and Modern Epidemiology

by Gerstman, B. Burt

• ISBN13: 9780471400288
• ISBN10: 0471400289
• Edition: 2nd
• Format: Paperback
• Copyright: 2003-09-04
• Publisher: Wiley-Liss

Summary

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.

Author Biography

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.

Table of Contents

Statistical Notation.

Preface to the Second Edition (Epidemiology Kept What?).

Preface to the First Edition (Who Studies Epidemiology and Why They Bother).

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. Disease and Causal Concepts.

2.1 Natural History of Disease.

2.2 The Spectrum of Disease and ""The Iceberg"".

2.3 Causal Concepts.

2.4 Epidemiologic Variables.

3. The Infectious Disease Process.

3.1 Reasons to Study the Infectious Disease Process.

3.2 The Infectious Disease Process.

3.3 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.

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

5. Case Definitions and Disease Classification.

5.1 Case Definitions.

5.2 The International Classification of Disease.

5.3 Artifactual Fluctuations in Reported Rates.

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.

8. 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.

9.3 Descriptive Studies vs. Analytic Studies.

10. Experimental Studies.

10.1 Introduction.

10.2 Selected Concepts.

10.3 Clinical Trials as a Point of Reference.

11. Observational Studies.

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. Types of Errors in Epidemiologic Research.

12.1 Introduction.

12.2 Random Error.

12.3 Systematic Error.

13 Confidence Intervals and p Values13.1 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 Introduction.

15.2 Chi-Square Test for Statistical Interaction.

15.3 A 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 pf 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.

20. Outbreak Investigation.

20.1 Background.

20.2 Investigatory Steps.

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

Chapter Addendum 2 (Case Study): A Foodborne Outbreak in Rhynedale, California.

Appendix 1. 95% Confidence Limits for Poisson Outbreak.

Appendix 2. Tai; Areas of the Standard Normal (Z) Distribution.

Appendix 3. Tai; Areas of Chi-Square Distributions.

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

Appendix 5. Case Study: Tampons and Toxic Shock Syndrome."