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PLoS One. 2017 May 11;12(5):e0177274. doi: 10.1371/journal.pone.0177274. eCollection 2017.

Modeling spatial variation in risk of presence and insecticide resistance for malaria vectors in Laos.

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UMR "Émergence des Pathologies Virales" (EPV: Aix-Marseille Univ-IRD 190 -Inserm 1207 -EHESP-IHU Méditerranée Infection), Marseille, France.
Asian Institute of Technology, Remote Sensing and GIS FoS, Klong Luang, Pathumthani, Thailand.
Institut Pasteur du Laos, Vientiane, Lao PDR.
Université de Toulouse-Le Mirail, Département de Géographie & Aménagement-UFR Sciences, Espaces, Sociétés Université, Toulouse, France.
UMR « Maladies Infectieuses et Vecteurs, Ecologie, Génétique, Evolution et Contrôle » (MIVEGEC, UM1-CNRS 5290-IRD 224), Montpellier, France.
Kasetsart University, Department of Entomology, Faculty of Agriculture, Bangkok, Thailand.
Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway.


Climatic, sociological and environmental conditions are known to affect the spatial distribution of malaria vectors and disease transmission. Intensive use of insecticides in the agricultural and public health sectors exerts a strong selective pressure on resistance genes in malaria vectors. Spatio-temporal models of favorable conditions for Anopheles species' presence were developed to estimate the probability of presence of malaria vectors and insecticide resistance in Lao PDR. These models were based on environmental and meteorological conditions, and demographic factors. GIS software was used to build and manage a spatial database with data collected from various geographic information providers. GIS was also used to build and run the models. Results showed that potential insecticide use and therefore the probability of resistance to insecticide is greater in the southwestern part of the country, specifically in Champasack province and where malaria incidence is already known to be high. These findings can help national authorities to implement targeted and effective vector control strategies for malaria prevention and elimination among populations most at risk. Results can also be used to focus the insecticide resistance surveillance in Anopheles mosquito populations in more restricted area, reducing the area of surveys, and making the implementation of surveillance system for Anopheles mosquito insecticide resistance possible.

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