@article{fdi:010063977,
  title = {{M}apping urban and peri-urban breeding habitats of {A}edes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters},
  author = {{S}arfraz, {M}. {S}. and {T}ripathi, {N}. {K}. and {F}aruque, {F}. {S}. and {B}ajwa, {U}. {I}. and {K}itamoto, {A}. and {S}ouris, {M}arc},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he spread of dengue fever depends mainly on the availability of favourable breeding sites for its mosquito vectors around human dwellings. {T}o 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 {B}reteau index, were calculated from {M}inistry of {P}ublic health data collected three times annually in {P}hitsanulok, {T}hailand between 2009 and 2011. {T}he most influential factors were found to be temperature, humidity, rainfall, population density, elevation and land cover. {M}odels 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 {D}ecision {T}ree method. {T}he models developed were found to be sufficiently flexible to accommodate additional parameters and sampling data that might improve prediction of favourable breeding hotspots. {T}he 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. {T}he 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. {T}he proposed approach demonstrates the successful utilisation of remotely sensed images to map mosquito breeding habitats.},
  keywords = {dengue fever ; fuzzy analytic hierarchy process ; larval density ; data mining ; climatic factors ; health ; geographical information system ; {T}hailand ; {THAILANDE}},
  booktitle = {},
  journal = {{G}eospatial {H}ealth},
  volume = {8},
  numero = {3},
  pages = {{S}685--{S}697},
  ISSN = {1827-1987},
  year = {2014},
  URL = {https://www.documentation.ird.fr/hor/fdi:010063977},
}