06040 - Epidemiology

Course Unit Page

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Good health and well-being Reduced inequalities Climate Action

Academic Year 2021/2022

Learning outcomes

By the end of the course the student should have gained an appreciation of the role of statistical methods and concepts in epidemiolgy. In particular the student should be able: - to plan an epidemiological study - to calculate and interpret relative risk, attributable risk, odds ratio in various types of epidemiological studies - to apply methods of adjusting odds ratios for confounding variables based on stratification, matching, logistic regression and Poisson regression - to use Kaplan-Meier method for the estimation of a survivor function

Course contents

Statistical methods for disease risks.

Confounding factors and stratified analysis.

Logistic regression model and Poisson regression: estimate and hypothesis tests.

Interpreting regression coefficients.

Residual analysis and goodness of fit.

Evaluation of diagnostic criteria.

Clinic and environmental epidemiology.

Meta-analysis of epidemiological studies.

Assessing health status in a population and evaluating therapies efficacy.

Readings/Bibliography

P.Armitage, G. BETTY, Statistica medica, Mc Graw Hill Libri Italia, Milano, 2007.

R.Beaglehole, R. Bonita, T. Kjellström, Epidemiologia di base, Edizione italiana a cura di G. Agazzotti, Editoriale Fernando Folini, Casalnoceto, 1997.

Testi di approfondimento

K.J. Rothman, Epidemiology: an introduction,Oxford University Press, 2nd ed, 2013.

D. W. Hosmer , S. Lemeshow Applied logistic regression, J. Wiley & Sons, , 2013.

D. Kleinbaum, Survival analysis, Springer Verlag, 2012.

Teaching methods

Lectures

Computer lab

Assessment methods

The exam, common to the course of Biostatisics, aims at testing the student's achievement of the following learning outcomes:

• deep knowledge of the statstical methods described and discussed during the lectures

• ability to use these methods in the analysis of biometrical data

• ability to use the obtained results for the quantitative interpretation of an epidemiological or clinical study.

The exam is common to the course of Biostatistics and is a computer plus an oral test. The aim of the computer test is to verify practical competences in the statistical analysis of health data. The oral test is related to the teaching objectives under a theoretical perspective.
The oral examination can be taken only when the computer test is passed and during at most two successive exam sessions. The exam is globally passed when both tests are sufficient. The final evaluation, given in marks out of 30, represents an average of the results obtained from both the exams.

Teaching tools

Blackboard, PC, Video projector

Office hours

See the website of Rossella Miglio

See the website of Federico Banchelli