Dit project is alleen beschikbaar in het Engels.
Lyme Disease in Europe: Perspectives for Surveillance
This project aims to increase our understanding of the epidemiology, risks and impact of Lyme borreliosis in Europe. Identifying spatial and temporal patterns in the incidence of infections will allow us to make recommendations of improved (risk-based) surveillance, and will increase of public and institutional awareness of Lyme risks in those area where Borrelia is most likely to occur.
Lyme in Europe
Lyme borreliosis is one of the most prevalent vector-borne diseases in Europe. The disease is caused by Borrelia burgdorferi, which in Europe is mainly transmitted by the castor bean tick (Ixodes ricinus).
Almost all European countries collect data on the occurrence of Lyme borreliosis. However, differences in data collection and national surveillance systems compromise the comparability of incidence rates between countries. Available data are usually only representative for specific regions within a particular country.
Accordingly, highly divergent incidence rates for Lyme borreliosis have been reported not only between countries but also between regions within a country.
To create a better understanding of the epidemiology and impact of Lyme borreliosis in Europe, spatial and temporal trends of Borrelia infections – not only in humans but also in vectors and reservoir hosts – will need to be assessed at the European level and future trends should be monitored.
Tracking and projecting Lyme borreliosis
In order to increase our understanding of the epidemiology, risks and impact of Lyme borreliosis in Europe, we apply meta-analytical techniques and data simulation methods to quantify trends, spatial patterns and assess certainty estimates of Borrelia infections in humans as well as in vectors and reservoir hosts.
A structured literature review has been conducted to quantify trends, infection risks and surveillance gaps of Lyme borreliosis in the EU and affiliated countries. Spatial and temporal trends will be assessed using a combination of geographic modelling and spatial analysis techniques to make recommendations of improved (risk based) surveillance and an increase of public and institutional awareness of Lyme risks in those area where Borrelia is most likely to occur.