Publications des scientifiques de l'IRD

Sarfraz M. S., Tripathi N. K., Faruque F. S., Bajwa U. I., Kitamoto A., Souris Marc. (2014). Mapping urban and peri-urban breeding habitats of Aedes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters. Geospatial Health, 8 (3), p. S685-S697. ISSN 1827-1987.

Titre du document
Mapping urban and peri-urban breeding habitats of Aedes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters
Année de publication
2014
Type de document
Article référencé dans le Web of Science WOS:000350407800008
Auteurs
Sarfraz M. S., Tripathi N. K., Faruque F. S., Bajwa U. I., Kitamoto A., Souris Marc
Source
Geospatial Health, 2014, 8 (3), p. S685-S697 ISSN 1827-1987
The spread of dengue fever depends mainly on the availability of favourable breeding sites for its mosquito vectors around human dwellings. To investigate if the various factors influencing breeding habitats can be mapped from space, dengue indices, such as the container index, the house index and the Breteau index, were calculated from Ministry of Public health data collected three times annually in Phitsanulok, Thailand between 2009 and 2011. The most influential factors were found to be temperature, humidity, rainfall, population density, elevation and land cover. Models were worked out using parameters mostly derived from freely available satellite images and fuzzy logic software with parameter synchronisation and a predication algorithm based on data mining and the Decision Tree method. The models developed were found to be sufficiently flexible to accommodate additional parameters and sampling data that might improve prediction of favourable breeding hotspots. The algorithm applied can not only be used for the prediction of near real-time scenarios with respect to dengue, but can also be applied for monitoring other diseases influenced by environmental and climatic factors. The multi-criteria model presented is a cost-effective way of identifying outbreak hotspots and early warning systems lend themselves for development based on this strategy. The proposed approach demonstrates the successful utilisation of remotely sensed images to map mosquito breeding habitats.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Sciences du milieu [021] ; Entomologie médicale / Parasitologie / Virologie [052] ; Télédétection [126]
Description Géographique
THAILANDE
Localisation
Fonds IRD [F B010063977]
Identifiant IRD
fdi:010063977
Contact