The aim of this course is to provide students with the necessary knowledge and skills to be able to critique, design and conduct and human population based research, including observational studies and randomized controlled trials. More specifically, to provide advanced knowledge of statistical analysis for epidemiological data, study design and protocol development.

To define epidemiology and public health

To list the functions of public health

To describe the assessment of evidence of causation

To outline the process of population-based health management

To describe different public health programs

To discuss about the study design, sample size determination, sampling procedure, and data analysis for health science and epidemiology

At the end of the course, students should have the knowledge and skills to be able to:

Critically appraise and evaluate the design, analysis and interpretation of health science and epidemiological studies

Describe and discuss the role and contribution of epidemiology to health

Select, devise and develop appropriate study designs for health science and epidemiological research

Conduct appropriate statistical analyses for health and epidemiological data

Introduction: Some examples of health study; Selection of health problem for research; Framing different type of study design: prospective study, retrospective study, longitudinal study, experimental study, observational study, intervention study, single blind study, double blind study; Selection of study population and cases for the study; causal variables, confounder variables; Ethical issue related to health study.

Measuring Health and Disease: Sources of health statistics. Meaning and Concept. Biological variations. Health indicators classification. Morbidity concepts and measures. Illness, diseases and their classifications. Multiple causation of diseases The conquest and resurgence of infectious diseases. The biomedical basis of chronic diseases. Measuring diseases frequency and errors in measurement. Mortality. Nutrition in Bangladesh; special emphasis on infant and child nutrition.

Statistics in Epidemiology: Categorical response data in epidemiology and diagnosis-prognosis; OR, RR, NNT, PPR, NPR, sensitivity, specificity, true positive rate, true negative rate; ROC analysis; power, precision, sample size calculation.

Statistical Models in Epidemiology: Data Analysis and interpretation using statistical models. Linear regression model; log linear models, building and applying log linear models, log linear and logit models for ordinal variables; multinomial response models. Models for mixed health hazards; multilevel sources of variation. Analysis of repeated epidemiological outcomes.  Parametric and semiparametric models for complete and incomplete data in epidemiology, Cox proportional hazards model.

Mathematical Models in Epidemiology: Basic Concepts, SI Model Formulation, Solution and Interpretation, SIS Model with Constant Coefficient Formulation, Solution and Interpretation, SIS Model with Constant Coefficient is a function of time t, SIS Model with Constant Number of Carriers  Formulation, SIS Model When the Carrier is a Function of Time t, General Deterministic Model with Removal (SIR Model) Formulation, Solution of Model Equation Interpretation, Epidemic Model with Vaccination Solution of Model Equation

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Klien JP and Moeschberger, ML (2003): Survival Analysis: Techniques for Censored and Truncated Data. 2nd edi, Springer.

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Singh,B and Agarwal, N(2005), Bio-Mathematics, First Edition, Krishna Prokashan Media (p) Ltd., Meerat, India.

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