USC Schedule of Classes

Overview of behavioral theory and research in disease prevention and health promotion and in adaptation to chronic disease, including an introduction to measures of outcomes. Prerequisite: Admission to HBR Ph.D. Program or permission of instructor.

Overview and application of behavioral theories to the field of health education and promotion. Examines the determinants of health behavior and strategies for change at the individual, group and community level.

Overview of public health concepts and issues, including population health; ethics; health disparities, determinants, and systems of care; global health; policy; health promotion; environmental health.

Overview of program implementation challenges in global health contexts, including best practices for establishing effective cross-cultural collaborations, working with key leaders, and operationalizing complex interventions.

A practical examination of methods and data sources used to evaluate public health services and conduct policy research and evaluation within health care delivery systems.

Historical development of the American health care system; determinants of health care utilization; role of health care providers; health policy; public health services; and health care finance.

Concepts of biostatistics; appropriate uses and common misuses of health statistics; practice in the application of statistical procedures; introduction to statistical software including EXCEL, SPSS, nQuery. Laboratory.

Major parametric and non-parametric statistical tools used in biomedical research, computer packages including SAS. Includes laboratory. Lecture, 2 hours; laboratory, 2 hours.

Statistical methods for analysis of categorical data including dichotomous, ordinal, multinomial and count data, using Stata package. Includes laboratory.

Methods and applications for modeling longitudinal, time-to-event and multi- level data. Includes laboratory using R package. Lecture 2 hrs; laboratory 2 hrs. Prerequisites: PM-511b.

Terminology/uses of epidemiology and demography; sources/uses of population data; types of epidemiologic studies; risk assessment; common sources of bias in population studies; principles of screening. Recommended preparation: algebra

Study design, ascertainment of study objects, questionnaire development, various methodological issues in study design and interpretation including bias, measurement error, confounding and effect modification.

a: Density distribution and hazard functions; normal, chi-square, student's t and F distributions; and sampling procedures for single factor and multiple factor designs, distributions. Recommended preparation: working knowledge of multivariable calculus and familiarity with linear algebra.

International variations in health status with a focus on the impact of socioeconomic status, politics, environment, education and gender in etiology of illness, access to health care, progression of disease, and recovery.

An overview of environmental health, identifying issues in assessing effects of exposure on health and potential interventions for reducing adverse health risks. Prerequisite: PM-512

Genetic principles; design and analysis of family studies; introduction to likelihood estimation; segregation and linkage analysis; biomarkers of exposure, susceptibility, and disease; laboratory methods; susceptibility genes; association and linkage disequilibrium.

Overview of concepts, tools, data collection, analysis methods and designs used to evaluate health promotion programs. Examples from substance abuse prevention, family planning and reproductive health programs.

Overview of causative factors and demographic distribution of major chronic diseases in the western world. Epidemiologic concepts, methods and research design as applied to chronic disease prevention will be emphasized. Prerequisite: PM 512.

Exploratory and inferential techniques for multivariate data, Hotelling's T2, multivariate analysis of variance, classification analysis, principle components, cluster analysis, factor analysis. Involves computer use.

Stochastic failure process; parametric models for survival data; sample size estimation procedures for clinical trials; multivariate regression models for binary outcome and censored survival data; computer programs; multiple failure modes and competing risks.

Examine epidemiologic methods, concepts, and statistical approaches; case-study seminars with structured critiques of current literature on human-environment interactions affecting public health. Recommended preparation: PM-510 and PM-512.

Explores the fundamental concepts of cancer epidemiology, including the molecular basis, descriptive epidemiology, and historical and groundbreaking studies that have impacted the field.

Survey of effective community organizing and mobilization efforts in the U.S. and abroad, using participatory, organizational, community empowerment and public-private partnership models.

Introduction to leadership and management concepts, tools, and practices in the context of domestic and global public health and healthcare delivery settings.

Current public health issues and research topics relating to 21st century challenges and threats. Lessons learned and best practices to strengthen public health systems and enhance public health readiness and preparedness.

An introduction to the toolsets needed to create workable and reproducible datasets, conduct exploratory analysis and visualizations, learn from data, summarize and communicate analytic results.

Definition and chronology of natural and man-made disasters and their effects on the global community. Structure and organization of disaster management systems and the role of humanitarian organizations.

Ethical principles in the distribution of health resources, conduct of global public health research, and implementation of public health initiatives across different nations, cultures, religions.

An introduction to statistical methods for analyzing and interpreting spatially referenced data topics include: geostatistics, areal data, point pattern data and visualization.

An introductory course in the statistical methods used in the analysis of human genetic data.

Mammalian organ systems operation during health, and pathophysiologic analysis of related diseases with focus on muscle, respiratory, cardiovascular and renal systems. Faculty from basic and clinical sciences.

Study designs, exposure time response, longitudinal, spatial, ecologic correlation and mechanistic models, measurement error interactions, measurement error, public policy implications.

Provides students with hands on experience of the common methods used in conducting epidemiological studies, and designing and obtaining funding for research projects. Prerequisite: PM-512. Recommended preparation: PM 527.

Research leading to the master's degree. Maximum units which may be applied to the degree to be determined by the department. Graded CR/NC.

Introduces Masters and Ph.D. students in the Health Sciences to Machine Learning methods and their Biomedical applications.

Provides a rigorous introduction to statistical methods for analyzing data with a focus on regression modeling for continuous and binary outcomes.

Credit on acceptance of thesis. Graded IP/CR/NC.

Credit on acceptance of thesis. Graded IP/CR/NC.

Credit on acceptance of thesis. Graded IP/CR/NC.

Part-time or full-time, practical work experience in the students field of study. The internship must be located at an off-campus facility. Students are individually supervised by faculty.

Applied practical experience through field placement in federal, state, and/or local public health agencies/organizations, including community-based organizations; research and school-based settings.

Provides the culminating, integrative learning experience for students enrolled in the Master of Public Health program.

Psychosocial basis of health-hazardous lifestyle behaviors and preventive strategies. Recommended preparation PM-500, PM 515

Factor analytic and structural equation modeling approaches to health behavior research -- conceptual, practical and mathematical.

Theoretical basis and practical approaches for identifying, summarizing and interpreting current bodies of scholarly information addressing a defined research question.

Analysis of an external medical research or healthcare industry dataset; project/presentation based.

Special topics of current interest to provide background for research in biostatistics and epidemiology. Based largely on student dissertation research. Graded CR/NC.

First of three courses in CTR, a discipline that fosters multidirectional integration of basic, patient-oriented and population-based research with long-term goal of improving public health. Recommended preparation: PM 510.

Process of applying for research grants in health behavior research, including dissertation grants. Covers the structure of NIH and other grantmaking agencies, the grant review process, tailoring ideas to the grantmaker's priorities, research design, development of training and mentoring plans, and budgeting.

Independent research at an advanced level on a problem in the field of Health Behavior. Recommended preparation PM 604. Graded CR/NC.

Independent research at an advanced level on a problem in the field of Health Behavior. Graded CR/NC.

Independent research at an advanced level on a problem in the field of Health Behavior. Graded CR/NC.

Independent research at an advanced level on a problem in the field of Health Behavior.

Independent research at an advanced level on a problem in the field of health behavior. Graded CR/NC.

Short seminar presentations and discussions on issues accompanying the development of the field of health behavior and implementation of research in this field. Graded CR/NC.

Research applicable to the doctorate. Maximum units which may be applied to the degree to be determined by the department. Graded CR/NC.

Credit on acceptance of dissertation. Graded IP/CR/NC.

Credit on acceptance of dissertation. Graded IP/CR/NC.

Credit on acceptance of dissertation. Graded IP/CR/NC.

Credit on acceptance of dissertation. Graded IP/CR/NC.

Credit on acceptance of dissertation. Graded IP/CR/NC.