Veterinary Epidemiology

As one of the very few online medical courses in veterinary epidemiology that is available, this course is highly suitable for veterinary researchers with an interest in epidemiology, who want to understand the concepts of epidemiology and apply these concepts in data analysis. It is taught by epidemiologists from the Faculty of Veterinary Medicine, and forms part of the MSc Epidemiology program of the UMC Utrecht and Utrecht University.

Learn the basic principles of veterinary epidemiology

The aim of this 12-weeks course is to make you familiar with all the basic principles of veterinary epidemiology. In every learning unit, a specific veterinary epidemiology topic will be discussed, illustrated and combined with practical data analysis tasks and/or reading assignments, for an interactive learning experience.

Concepts and data analysis

This course consists of two parts. The first part will make you familiar with the concepts of veterinary epidemiology illustrated by basic computer practicals. The second part will teach you epidemiological data analysis in more depth, by using open-source statistical software R. 

Veterinary Epidemiology is part of MSc Epidemiology Postgraduate Online; the online MSc program in Epidemiology offered by Utrecht University, University Medical Center Utrecht, MSc Epidemiology and Elevate Health.

Learning objectives

By the end of the course, you will be able to:

  • Understand the basic principles of veterinary epidemiology
  • Use theoretical concepts of veterinary epidemiology in practice
  • Perform basic test evaluations and sample size calculations
  • Organize and perform veterinary epidemiological studies
  • Understand the basics of outbreak investigation and risk analysis
  • Understand and evaluate epidemiological publications
  • Know the basics of infectious disease modeling

Course topics

  • Study designs

In this initial session, the most important study designs for veterinary epidemiology will be discussed and their uses explained.

  • Disease causation and association

First, you will discover the mechanisms leading to disease causation and learn how causes of a disease may be observed as associations. Next, you will learn to recognize and overcome a variety of hurdles to get back from associations to causality.

  • Diagnostic testing

You will explore various aspects of diagnostics tests, such as test characteristics, test interpretation, use of multiple tests, and testing at herd level. Attention will also be given to evaluation of new tests.

  • Sampling

This part covers various sampling schemes, and is for a large part devoted to calculating sample sizes for some basic sampling schemes.

  • Stratified analysis

Stratified analysis is a basic approach to data. We will focus on why and how to divide data into strata (sub-sets) in order to facilitate analysis and interpretation. Effect modification and confounding are the key issues covered here.

  • Linear and logistic regression modeling

You will become familiar with the linear process, all the way from raw data all the way to model output. You will learn to understand the concept of linear regression modeling and you will also gain a basic understanding of logistic regression.

  • Model building, matching and coding

These summarizing topics will deal with some specific aspects of data handling, such as analysis tools for matched data.

  • Outbreak analysis

You will be introduced to a structured general approach to outbreak investigations, not particularly related to infectious OIE list diseases.

  • Risk analysis

This basic introduction will illustrate where epidemiology meets risk analysis. The stepwise risk analysis approach is a very useful tool for herd health-related veterinary advice.

  • Infectious disease dynamics

We will deal with some basic infectious disease models and important parameters (e.g. the SIR [Susceptible, Infections, Removed] model,  the basic reproduction number, and the transmission rate). We will also cover the analysis of simple observational data sets, and the principles of transmission experiments. Simulations will be used to illustrate important design aspects of a disease surveillance program.

Learning methods

The whole Veterinary Epidemiology course will take place online. The following learning methods will be used:

  • Interactive web lectures
  • Reading book chapters
  • Individual assignments
  • Discussions
  • Group assignments
  • Individual computer-based practical assignments

Course Deadlines

Week 0
Sunday before start date - introduce yourself

Week 1
Sunday – complete Learning Unit 1

Week 2
Sunday – complete Learning Unit 2

Week 3
Sunday – complete Learning Unit 3

Week 4
Sunday – complete Learning Unit 4

Week 5
Sunday – complete Learning Unit 5

Week 6
Sunday – complete Learning Unit 6

Week 7
Sunday – complete Learning Unit 7

Week 8
Sunday – complete Learning Unit 8

Week 9
Sunday – complete Learning Unit 9 and 10

Week 10
Sunday – complete Learning Unit 11

Week 11
Sunday – complete Learning Unit 12

Week 12
Sunday – complete Learning Unit 13 and 14

Week 14 (could differ per edition)
Final exam

Assignments & Examination

To successfully complete this course, you need to actively participate in the discussion forums and complete the learning unit assignments, including:

  • Individual and group assignments
  • A final assignment: this involves a final exam, consisting of open questions. You are allowed to redo the exam once.

Edition 2019: The final exam will take place on June 24th, 2019. The re-examination will take place on July 29th, 2019.

If you are able and willing to take the exam in Utrecht, the Netherlands, we are available to proctor the exam for you without any costs. If you have to take the exam from a different location, you need a proctor. This proctor may ask you to pay for their expenses. Please read more about proctoring on our specific webpage.

The exam is not compulsory. However, if you want to receive the Course Certificate and the credits, it is obligatory to take the exam.

It might be that, due to a force majeure situation, you cannot be present during the first exam moment. You must then, preferably prior to the first exam option, ask the academic counsellor for permission to be absent. Please note that the academic counsellor can ask for some form of proof of your absence (e.g. in case of illness) to establish if you are applicable for authorized absence. Jaco de Fockert-Koefoed, MSc is the academic counsellor you need to turn to through

In short, as of now, it is no longer possible to skip the first exam option and -automatically- enrol in the second (re-sit) exam. Unauthorized absence during the first exam period results in no longer being able to finish the course that college year.


As Veterinary Epidemiology is a university course, it is covered by academic accreditation. Upon passing the final exam, you will receive a recognized certificate from Utrecht University and the UMC Utrecht.  

Entry requirements

To enroll in this course, you need:

  • A BSc in Veterinary Medicine
  • Access to the program R
  • Sufficient proficiency in English reading and writing
  • Some basic statistical knowledge is recommended (please contact your Elevate Enrollment Advisor if in doubt)

Compulsory study materials

  • 'Veterinary Epidemiologic Research, Second Edition' by Ian Dohoo, Wayne Martin & Henrik Stryhn, 2010. ISBN-13: 978-0919013605

  • ‘Veterinary Epidemiology: An Introduction’ by Dirk Pfeiffer, 2010. ISBN: 978-1-4051-7694-1

Please note
As this is an online course, you do need access to an internet connection in order to be able to follow lectures, complete assignments and communicate with fellow participants.

This course is also available offline. Please visit the MSc Epidemiology website for more information.

Course staff


Pick a date for this course:
(Enrollment deadline: 29 March 2020 - 23:59 CET)
288 days left.

Quick overview

  • 30 Mar 2020 – 21 Jun 2020
  • 12 weeks
  • 14 hrs/wk
  • Academic Certificate
  • 6.0 EC
  • Online
  • English
  • Web lectures, exercises, group discussions
  • Desktop, Laptop, Smartphone, Tablet
  • 1285

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