78853 - EPIDEMIOLOGIA AMBIENTALE

Academic Year 2017/2018

  • Moduli: Rossella Miglio (Modulo 1) Massimo Ventrucci (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Bologna
  • Corso: First cycle degree programme (L) in Statistical Sciences (cod. 8873)

Learning outcomes

The aims of this course is to introduce the basic tools for the analysis of the relationship between environmental exposure and health effects.

Course contents

Module I

Introduction to environmental epidemiology.

Design. Evaluation of exposure. Evaluation of health effects.

Dose response relationship. Critical review of literature.

Case studies. Time series studies for short term effects of air pollution.

 

Module II

Introduction to spatial epidemiology. Source of data in spatial epidemiology studies: population, health, environment.

Descriptive statistics for spatial data. Spatial association measures for areal data: Moran index. Spatial correlation measures for geostatistical data: the Variogram.

Statistical modelling for spatially correlated data. Basics of Gaussian Markov Random Fields with applications to areal disease counts. Disease mapping models: lab and tutorials with R

Generalized additive models applied to studying the relationships between health and pollution: lab and tutorials with R.

Readings/Bibliography

Statistical Methods for Environmental Epidemiology with R. A Case Study in Air Pollution and Health (2008). Peng, R. D., Dominici, F.

Spatial Epidemiology: Methods and Applications (2001). Elliot et al.

Gaussian Markov Random Fields: Theory and Applications (2005).Rue H, Held L.

Generalized Additive Models: An Introduction with R (2006). Simon Wood.

Teaching methods

Lectures

Lab session

Assessment methods

The exam aims at testing the student's achievement of the learning outcomes related to the knowledge of the basic tool for the analysis of the relationship between environmental exposure and health effects. The exam is written.

The overall evaluation is based on the average of the outcome of the two modules and is expressed in marks out of 30. However, the final mark of the course will be awarded only if sufficiency has been reached in each of the two modules.

Teaching tools

PC / video projector

Office hours

See the website of Rossella Miglio

See the website of Massimo Ventrucci