Open Access
Modélisation de la survenue des vecteurs de la fièvre catarrhale ovine à l'aide des systèmes d'information géographiques et de la télédétection
Author(s) -
Hyvina Maria Andrade Martins,
T. Nunes,
Fernando Boinas
Publication year - 2009
Publication title -
revue d'élevage et de médecine vétérinaire des pays tropicaux/revue d'élevage et de médecine vétérinaire des pays tropicaux
Language(s) - English
Resource type - Journals
eISSN - 1951-6711
pISSN - 0035-1865
DOI - 10.19182/remvt.10062
Subject(s) - culicoides , cartography , geography , spatial analysis , vector (molecular biology) , geographic information system , ecology , biology , remote sensing , biochemistry , gene , recombinant dna
Bluetongue (BT) is an infectious non-contagious disease which mainly affects domestic ruminants. It is caused by an arbovirus (BTV) from the family Reoviridae and its transmission is commonly associated with an intermediate arthropod host from the genus Culicoides. Culicoides imicola is the main vector of BTV in the Mediterranean Basin. Entomological surveillance programmes make it possible to collect continuously data of vital importance for the spatial and temporal investigation of BT vector distribution. In May 2005, Portugal has implemented this programme, which is providing a considerable amount of data concerning the abundance, and spatial and temporal distribution of several Culicoides species. Remote sensing is the process of acquiring data about a geographical object through several aircrafts or satellites built-in sensors and thus allowing the collection of useful information to characterize biophysical, climatic and environmental variables. Some of these variables influence survival, development and dispersion of BT vectors. The combination of satellite imagery and entomological surveillance data using geographical information systems (GIS) helps to develop models for the prediction of spatial occurrence of disease vectors. These models might be useful to identify risk areas for disease transmission and are therefore important for the development of targeted sanitary control measures. Two mathematical approaches were selected to model the spatial occurrence of Culicoides imicola, i.e. discriminant analysis and logistic regression. Climatic, remotely sensed and national entomological data were used to build both models. Statistical packages and GIS were then used to implement these models. The discriminant analysis model was less accurate, presenting a sensitivity of 76.6% and a specificity of 75.3%. The logistic regression model was more robust and presented 80.9% sensitivity and 83.6% specificity. Descriptive spatial statistics were then calculated to characterize the landscape features associated with the presence/absence of BT vectors.