The group of Quantitative Veterinary Epidemiology (QVE) of Wageningen University has its core business in generating and disseminating knowledge on the epidemiology of diseases in animals, especially in livestock.
The emphasis is on the transmission of infectious diseases within and between groups of animals and on factors that influence that transmission.
The acquired knowledge potentially leads to the implementation of adequate intervention strategies and sound advice to decision makers.
QVE has formal connections with the Animal Sciences Group in Lelystad and the Faculty of Veterinary Medicine in Utrecht. QVE also has shared projects with GD in Deventer (Animal Health Service) and RIVM in Bilthoven (National Institute for Public Health and the Environment).
Concerning the educational tasks, QVE is responsible for a number of basic and advanced course elements, student externships, student theses and PhD education related to veterinary epidemiology.
The research of the group mainly focuses on the development of transmission models for infectious agents in livestock, in which knowledge from theoretical biology, veterinary science, animal science, mathematics and statistics are integrated. Such models are supported with data from experiments or from field studies.
These models are being used for:
1. predicting the course of an epidemic (example: classical swine fever (CSF) epidemic in NL in 1997),
2. predicting the effects of interventions (example: CSF 1997),
3. development of disease control programs (example: eradication program for Aujeszky’s disease in pigs in NL),
4. development of monitoring programs (example: assessing the progress of the eradication of IBR in cattle in NL)
5. giving indications about the quality of the diagnostic test(s) in order to fight a disease successfully.
Emphasis in research is also given to:
1. fundamental aspects of diagnostic testing, as the quality of the diagnostics is essential for the success of a disease control program
2. identification and quantification of risk factors in order to select suitable interventions
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