Project: Improving early detection of emerging vector borne diseases by using existing production and diagnostic data

/Key Words: Increased trade and subsequently movement of animals as well as climate change may lead to (re-) establishment of several vector-borne diseases in Europe. The recent outbreak of BTV in North-western Europe in 2006 and 2007 highlights this concern and requires effective surveillance systems for early detection of vector-borne diseases. It is important to consider current capabilities and future needs to effectively address surveillance, preparedness and response strategies for vector-borne diseases that emerge and may become prevalent. At several stages in the animal production chains data are recorded for several purposes such as management, quality controls, breeding and animal health care. Apart from their primary purpose for collection, these data could also be used for signalling changes in the epidemiological situation, which is hardly being performed as a tool in animal disease control. Signal theory methods and (real-time) time series analysis, could be adapted to such non-specific repeated data to detect a disease emergence in the absence of a previously identified pathogen. Vector-borne diseases are likely to exhibit a spatio-temporal distribution pattern of detected signals associated with the possible distribution and spread of vectors. The aims of this project are to develop and evaluate a monitoring and early detection system for emerging vector-borne diseases in cattle, based on indicators derived from existing data, such as production records and diagnostic data. The project will also aim for cross-border cooperation regarding monitoring and surveillance of animal health. The project will deliver statistical and modelling methods for existing production and diagnostic data to detect deviations from trends in time and space as indicators for emerging vector-borne diseases. These models will be used to design a surveillance system for early detection of emerging vector-borne diseases based on existing data. The surveillance systems for early detection of vector-borne diseases will be validated by using BTV as a case-study. The monitoring and surveillance systems (components) in the participating countries will be evaluated with scenario tree modelling and, where possible, economical (cost/benefit) impact will be determined. Eventually, a framework for an optimal mix per country and cooperation between the participating countries in a joint surveillance system for early detection of emerging vector-borne diseases will be proposed.

Acronym Early Detection Data
Duration 31/12/2013
Website visit project website
Network EMIDA
Call EMIDA 2009 Research Call

Project partner

Number Name Role Country
Veterinary and Agrochemical Research Centre Belgium
GD Animal Health Deventer Coordinator Netherlands
Nantes Atlantic College of Veterinary Medicine, Food Science and Engineering France