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. 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.
Hands-on means Hands-on in this course! We might even call it a master-class in veterinary epidemiological research. This course offers you the opportunity to practice and improve your skills in analyzing animal health data. You will go through the process of formulating a hypothesis, visualizing and analyzing data, interpretation the results, and reporting.
For this course you are allowed (and encouraged) to work on you own data set. This data set
needs to fulfil certain criteria:
• It is about epidemiology of animal diseases or a zoonosis
• You have access to the data
• The data analysis is not yet completed or you would like to investigate another subset of the data
• Preferably the data is gathered during observational research, but RCT’s or animal experiments can sometimes be interesting as well
Veterinary Epidemiology is broad concept therefore there were multiple online courses created. These courses can be ordered in a bundle. This bundle consists out of 3 online courses: Study Design for Veterinary Epidemiology, Epidemiology of Animal Infectious Diseases and Hands-on Veterinary Epidemiology. The bundle offers 20% discount, read more about it here.
By the end of the course, you will be able to:
• Perform the analyses required for a veterinary disease epidemiological research
• Interpret results in the context of the research question for veterinary disease epidemiological research
• Modelling approach and causal diagrams
• Descriptive statistics
• Analysis plan
• Uncertainty and model evaluation
During the course, you will be guided while working on this project by epidemiologists and statisticians. The week ends with presenting the results of your work both written and orally.
To enroll in this course, you need:
• Completed the course Modern Methods in Data Analysis (or equivalent course)
• Basic skill in R (or in another computer language such as Python or C++)
• Sufficient proficiency in English reading and writing
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