CEPH Accreditation

D1. Graduate-Level Professional Foundational Public Health Knowledge (MPH, MSB, MSE)

D1.1. Explain public health history, philosophy and values

D1.2. Identify the core functions of public health and the 10 Essential Services

D1.3. Explain the role of quantitative and qualitative methods and sciences in describing and assessing a population’s health

D1.4. List major causes and trends of morbidity and mortality in the US or other community relevant to the school or program, with attention to disparities among populations, e.g., socioeconomic, ethnic, gender, racial, etc.

D1.5. Discuss the science of primary, secondary & tertiary prevention in population health, including health promotion, screening, etc

D1.6. Explain the critical importance of evidence in advancing public health knowledge

D1.7. Explain effects of environmental factors on a population’s health

D1.8. Explain biological and genetic factors that affect a population’s health

D1.9. Explain behavioral and psychological factors that affect a population’s health

D1.10. Explain the cultural, social, political and economic determinants of health and how the determinants relate to population health and health inequities

D1.11. Explain how globalization affects global burdens of disease

D1.12. Explain an ecological perspective on the connections among human health, animal health and ecosystem health (eg, One Health)

MSB Foundational Competencies

MSB1. Apply classic methods for continuous and categorical data analysis, including regression and other appropriate statistical approaches;

MSB2. Use computer-based statistical analysis package(s) to manage data;

MSB3. Develop visualized data using computer-based statistical analysis package(s);

MSB4. Analyze data employing computer-based statistical analysis package(s);

MSB5. Implement sample size and power calculations for a range of experimental designs;

MSB6. Interpret results of a health research study, including the relation to findings from other studies, potential biological or social mechanisms, study limitations, and public health implications;

MSB7. Communicate written and oral findings in a scientifically sound manner;

MSB8. Calculate epidemiological measures of association between risk factors and disease;

MSB9. Apply methods and strategies to evaluate and reduce bias in health research;

MSB10. Use criteria to distinguish between association and causality; and

MSB11. Apply ethical and regulatory standards to human subjects research.

Concentration in Population Health Analytics

PHA1. Design an epidemiologic study to address a question of interest;

PHA2. Describe practical considerations for the conduct of health research studies;

PHA3. Access publicly available data resources for population health research;

PHA4. Critically review the scientific literature, synthesize findings across studies, and make appropriate recommendations based on current knowledge; and

PHA5. Develop a clear description of the rationale, methods, results, and overall interpretation of an epidemiologic investigation.

Concentration in Statistical Bioinformatics

SB1. Develop computer files of high-dimensional data for analysis using high performance computing data management techniques;

SB2. Determine and execute appropriate statistical analyses, in particular techniques relevant to bioinformatics, to address a study question;

SB3. Access publicly available databases for bioinformatics research;

SB4. Develop statistical and bioinformatics analysis results in written, graphical and verbal format in response to an analysis request; and

SB5. Identify theoretical underpinnings of advanced statistical models.

Concentration in Statistical Methods and Practice:

SMP1. Develop computer files of raw data for analysis using data management and statistical analysis software

SMP2. Execute appropriate statistical analyses to address a study question;

SMP3. Apply classic methods for the analysis of time-to-event and clinical trial data;

SMP4. Develop statistical analysis results in written and verbal format in response to an analysis request; and

SMP5. Identify theoretical underpinnings of advanced statistical models.