Blizard Institute

Teaching menu


Rating: 15 credits

Prerequisites: None (however, at the beginning of the course, all students will be invited to undergo a self-assessment math test in order to evaluate their ability to follow the mathematical concepts within the course. Extra support will be given to those who will not pass the test)

Lectures: 1 hour per week semester A

Seminars: 2 hours per week semester A

Assessment: short answer test (100%)  


Module Aims and Outline:
This course is designed to be a highly interactive course aimed at introducing the students to the basic concepts of epidemiology and statistics. The course will mainly explore the theoretical issues underlying epidemiological research, however, practical skills will be thought in the module to reinforce the understanding of key concepts. During the course the students will firstly learn to interpret, apply and calculate measures of diseases and exposures in populations; then the core of the curse focuses on study design (including applications and specific sources of bias). As a result, by the end of the course, the students are able to critical appraise scientific epidemiological papers listing their strengths and limitations and identifying potential pitfalls in interpreting epidemiological data: chance, bias, confounding, and effect modification. Students are also introduced to the basic principle underlying causality assessment in epidemiology.

Learning Outcomes:
By the end of the course students will be able to:

  • Interpret, apply, and calculate measures of disease incidence and prevalence, and univariate measures of exposure-disease association (odds ratio, relative and absolute risk)
  • List potential source of epidemiological data on health status and health service utilisation and assess their strength and limitation
  • Understand the principles underlying the four main study designs (cross-sectional, case-control, cohort, and interventional) and apply the appropriate study design for a given scientific question
  • Critical appraise scientific epidemiological papers and list strengths and limitations of each of the four study designs
  • Identify and quantify potential pitfalls in interpreting epidemiological data: chance, bias, confounding, and effect modification
  • Enumerate principles for assessing causality in epidemiology
  • Extrapolate relevant figures from epidemiological studies for conveying a public health message, and critically evaluate analogous figures reported by the media

Saracci R (2010). Epidemiology – A very short introduction. Oxford University Press, New York

Rothman KJ (2012). Epidemiology – An introduction. Oxford University Press, New York

Aschengrau A, Seage GR III (2014) Epidemiology in Public Health. Jones & Bartlett earning, Burlington

Carneiro I, Howard N (2005) Introduction to Epidemiology. Open University Press, Maidenhead

Porta M (2008) A dictionary of Epidemiology. Oxford University Press, New York

Return to top