Course

Unit 1

Foundations of Epidemiology

• Introduction to Epidemiology: Definition, Scope, and Historical Context
• Measures of Disease Frequency: Incidence, Prevalence, and Mortality Rates
• Measures of Association: Relative Risk, Odds Ratio, and Attributable Risk
• Causality in Epidemiology: Bradford Hill Criteria and Causal Inference
• Sources of Epidemiological Data: Surveillance Systems and Health Registries

Unit 2

Study Designs in Epidemiology

• Overview of Epidemiological Study Designs
• Descriptive Studies: Ecological Studies and Cross-sectional Studies
• Analytical Studies: Cohort Studies and Case-Control Studies
• Experimental Studies: Randomized Controlled Trials
• Bias, Confounding, and Effect Modification in Epidemiological Studies

Unit 3

Foundations of Biostatistics

• Introduction to Biostatistics: Role in Public Health and Epidemiology
• Descriptive Statistics: Measures of Central Tendency and Dispersion
• Probability Distributions: Normal, Binomial, and Poisson Distributions
• Sampling Methods and Sample Size Calculation
• Hypothesis Testing and Confidence Intervals

Unit 4

Statistical Analysis Techniques

• t-tests and Analysis of Variance (ANOVA)
• Chi-square Tests and Fisher’s Exact Test
• Correlation and Simple Linear Regression
• Multiple Linear Regression and Logistic Regression
• Survival Analysis: Kaplan-Meier Curves and Cox Proportional Hazards Model

Unit 5

Applications in Public Health

• Screening and Diagnostic Tests: Sensitivity, Specificity, and Predictive Values
• Outbreak Investigation: Steps and Statistical Methods
• Clinical Trials: Design, Conduct, and Interpretation
• Systematic Reviews and Meta-analysisSuggested

Text Books / References

• Gordis, L. (2014). Epidemiology (5th ed.). Elsevier Saunders.
• Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. Centers for Disease Control and Prevention. (2012). Principles of Epidemiology in Public Health Practice (3rd ed.).
• Szklo, M., & Nieto, F. J. (2019). Epidemiology: Beyond the Basics (4th ed.). Jones & Bartlett Learning. Hennekens, C. H., & Buring, J. E. (1987). Epidemiology in Medicine. Lippincott Williams & Wilkins.
• Grimes, D. A., & Schulz, K. F. (2002). An overview of clinical research: the lay of the land. The Lancet, 359(9300), 57-61.
• Rosner, B. (2015). Fundamentals of Biostatistics (8th ed.). Cengage Learning. Pagano, M., & Gauvreau, K. (2018). Principles of Biostatistics (2nd ed.). CRC Press.
• Dawson, B., & Trapp, R. G. (2004). Basic & Clinical Biostatistics (4th ed.). Lange Medical Books/McGraw-Hill. Daniel, W. W., & Cross, C. L. (2018). Biostatistics: A Foundation for Analysis in the Health Sciences (11th ed.). Wiley. Vittinghoff, E., Glidden, D. V., Shiboski, S. C., & McCulloch, C. E. (2012). Regression Methods in Biostatistics: Linear,
• Logistic, Survival, and Repeated Measures Models (2nd ed.). Springer.
• Kleinbaum, D. G., & Klein, M. (2012). Survival Analysis: A Self-Learning Text (3rd ed.). Springer.
• Fletcher, R. H., Fletcher, S. W., & Fletcher, G. S. (2014). Clinical Epidemiology: The Essentials (5th ed.). Lippincott Williams & Wilkins.
• Gregg, M. B. (2008). Field Epidemiology (3rd ed.). Oxford University Press.
• Higgins, J. P. T., & Green, S. (Eds.). (2011). Cochrane Handbook for Systematic Reviews of Interventions (Version 5.1.0). The Cochrane Collaboration.
• Guyatt, G., Rennie, D., Meade, M. O., & Cook, D. J. (2015). Users’ Guides to the Medical Literature: A Manual for Evidence-Based Clinical Practice (3rd ed.). McGraw-Hill Education.

Prerequisite: 24SDS551 Health Policy & Systems Research Summary: This foundational course covers the essential concepts of epidemiology and biostatistics, providing students with the skills to investigate and interpret the distribution and determinants of health and disease in populations. Students will learn about study design, data collection, and statistical analysis techniques used in public health research. The course emphasizes the application of these methods to real-world health problems, enabling students to critically assess epidemiological studies and use biostatistical tools to inform public health decision- making.

Course Objectives

1. Understand and apply key epidemiological concepts including disease frequency, association, and causal inference in population health contexts.
2. Develop and critically assess appropriate study designs to investigate public health questions, with attention to bias, confounding, and effect modification.
3. Utilize foundational and advanced biostatistical techniques for data analysis, including hypothesis testing, regression models, and survival analysis.
4. Evaluate diagnostic and screening tools using quantitative measures such as sensitivity, specificity, and predictive values in public health practice.
5. Interpret, synthesize, and communicate epidemiological and statistical findings effectively for public health research, policy, and intervention.

Course Outcomes (COs)

CO1: Demonstrate the ability to apply core epidemiological measures and causal reasoning to assess population health using surveillance and registry data.

CO2: Design and evaluate epidemiological studies (descriptive, analytical, and experimental), accounting for bias, confounding, and effect modification.

CO3: Apply statistical analysis techniques including regression models and survival analysis to interpret real-world public health data.

CO4: Assess the validity and utility of diagnostic and screening tests using statistical criteria and explain their implications for clinical and public health practice.

CO5: Critically synthesize evidence from epidemiological literature and communicate findings to diverse audiences for public health action.

Skills:

• Epidemiological Reasoning: Ability to apply concepts such as incidence, prevalence, risk, and causal inference to assess health patterns and determinants in populations.
• Study Design and Appraisal: Competence in designing, evaluating, and critiquing epidemiological studies using appropriate methodologies and understanding sources of bias and confounding.
• Biostatistical Analysis: Proficiency in applying statistical techniques (e.g., regression, hypothesis testing, survival analysis) to analyze and interpret health data.
• Evidence Synthesis and Communication: Skills to critically appraise scientific literature and effectively communicate findings to scientific and policy audiences in support of public health decision-making.

-Program outcome PO – Course Outcomes CO Mapping

Program Specific Outcomes PSO – Course Objectives – Mapping

*CA – Can be Quizzes, Assignment, Projects, and Reports, and Seminar