The objectives of this course are to provide a detailed understanding of the basic principles of epidemiology including:
- diverse array of study designs, and their theoretical interrelatedness, available in clinical and epidemiologic research;
- importance of measurement;
- different types of measures of disease occurrence;
- methods to measure risk factor ("exposure") - disease ("outcome") association;
- measures of attributable risk;
- interaction;
- approaches to identify and minimize selection, measurement and confounding bias; and
- conceptual motivation for more sophisticated methods (e.g., regression or marginal structural approaches) to manage confounding, which are increasingly common tools in epidemiologic analyses.
- Instructor: Kristen
- Instructor: Trisha Hue
- Instructor: Jeffery Martin
- Instructor: Megha Mehrotra
- Instructor: Ann Schwartz
CAVEAT: The most important objective is to help you understand the interaction between clinical research and clinical medicine. How does (or should) information previously obtained on groups of patients inform clinical decisions on individuals?
A. Attitudes
- Increased confidence and comfort approaching journal articles.
- Preference for evidence over authority.
- Desire for independent learning.
- An "ecologic" view of clinical medicine that acknowledges limitations of knowledge and resources.
- An appreciation of the fun and satisfaction of learning and teaching this material.
B. Knowledge
- Understanding the diagnostic process.
- Understanding measures of interobserver agreement.
- Risk (and costs) of diagnostic, screening, and prognostic tests.
- Interpreting diagnostic data; quantifying information and refining probability estimates from results of dichotomous and continuous tests.
- Common biases of studies of diagnostic, prognostic and screening tests.
- Quantifying effects of treatments using experimental and observational studies.
- Bayesian understanding of P-values and confidence intervals.
- Challenges to evidence-based medicine.
C. Skills
- Calculation of and comfort with sensitivity and specificity.
- Calculation of posterior probability and test thresholds using likelihood ratios.
- Calculation of and comfort with risk ratios, odds ratios, number needed to treat.
- Critical appraisal of clinical research articles.
- Instructor: Benjamin Breyer
- Instructor: Joshua Galanter
- Instructor: Miriam Laker
- Instructor: Thomas Newman
- Instructor: Martina Steurer
Instruction in intermediate and advanced concepts in infectious disease epidemiology. Topics include social network analysis, vaccine efficacy, epidemic dynamics, evaluation of communicable disease interventions, surveying hard-to-reach populations, prophylaxis and mass drug administration.
- Instructor: Joelle Brown
- Instructor: Meghan Morris
- Instructor: George Rutherford
Instruction in basic demographic methods, including population dynamics, fertility, mortality, migration, urbanization, aging, and family structure. The emphasis will be on how and why understanding these factors is important for public health practitioners.
- Instructor: Nadia Diamond-Smith
Introduction to the concepts, principles, and methods for the visualization and analysis of spatially referenced health data. Lectures, discussion and assignments will highlight spatial data analysis techniques with applications in malaria and other infectious and non-infectious diseases prevalent in international settings.
- Instructor: Ricardo
- Instructor: Adam Bennett
- Instructor: Alemayehu
- Instructor: Jennifer Smith
- Instructor: Hugh Sturrock
This course is an introduction to the study of biostatistics. We cover types of data, their summarization, exploration and explanation. Also, we look at concepts of probability and their role in explaining uncertainty. We end with coverage of inference applied to means, proportions, regression coefficients and contingency tables. Throughout the course, the software program Stata will be used.
- Instructor: Isabel Elaine Allen
- Instructor: Judith Hahn
- Instructor: Alison Huang
This is a fourth course in statistics, covering advanced methods for building and evaluating regression models. The emphasis is on methods which cut across common families of regression models in biostatistics: predictor selection, model diagnostics and model comparison. The statistics package Stata will be used throughout the course.
- Instructor: Dave Glidden
- Instructor: Barbara Grimes
This course is open to all UCSF personnel with active MyAccess accounts at no charge. Students must enroll in the course to view the materials. Please email cdunne@psg.ucsf.edu to be enrolled in this course.