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Spatial heterogeneity and temporal evolution of malaria transmission risk in Dakar, Senegal, according to remotely sensed environmental data.

Machault V, Vignolles C, Pagès F, Gadiaga L, Gaye A, Sokhna C, Trape JF, Lacaux JP, Rogier C - Malar. J. (2010)

Bottom Line: Linear regressions were fitted to identify the ecological factors associated with An. arabiensis aggressiveness measured in 1994-97 in the South and centre districts of Dakar.Risk maps for populated areas were computed and compared for 1996 and 2007 using the results of the statistical models.The evolution of the risk was quantified, and the results indicated there are benefits of urbanization in Dakar, since the proportion of the low risk population increased while urbanization progressed.

View Article: PubMed Central - HTML - PubMed

Affiliation: Unité de Recherche en Biologie et Epidémiologie Parasitaires, UMR6236, Institut de Recherche Biomédicale des Armées, Allée du Médecin colonel Jamot, Parc du Pharo, BP60109, 13262 Marseille cedex 07, France. vanessamachault@yahoo.com.br

ABSTRACT

Background: The United Nations forecasts that by 2050, more than 60% of the African population will live in cities. Thus, urban malaria is considered an important emerging health problem in that continent. Remote sensing (RS) and geographic information systems (GIS) are useful tools for addressing the challenge of assessing, understanding and spatially focusing malaria control activities. The objectives of the present study were to use high spatial resolution SPOT (Satellite Pour l'Observation de la Terre) satellite images to identify some urban environmental factors in Dakar associated with Anopheles arabiensis densities, to assess the persistence of these associations and to describe spatial changes in at-risk environments using a decadal time scale.

Methods: Two SPOT images from the 1996 and 2007 rainy seasons in Dakar were processed to extract environmental factors, using supervised classification of land use and land cover, and a calculation of NDVI (Normalized Difference Vegetation Index) and distance to vegetation. Linear regressions were fitted to identify the ecological factors associated with An. arabiensis aggressiveness measured in 1994-97 in the South and centre districts of Dakar. Risk maps for populated areas were computed and compared for 1996 and 2007 using the results of the statistical models.

Results: Almost 60% of the variability in anopheline aggressiveness measured in 1994-97 was explained with only one variable: the built-up area in a 300-m radius buffer around the catching points. This association remained stable between 1996 and 2007. Risk maps were drawn by inverting the statistical association. The total increase of the built-up areas in Dakar was about 30% between 1996 and 2007. In proportion to the total population of the city, the population at high risk for malaria fell from 32% to 20%, whereas the low-risk population rose from 29 to 41%.

Conclusions: Environmental data retrieved from high spatial resolution SPOT satellite images were associated with An. arabiensis densities in Dakar urban setting, which allowed to generate malaria transmission risk maps. The evolution of the risk was quantified, and the results indicated there are benefits of urbanization in Dakar, since the proportion of the low risk population increased while urbanization progressed.

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Measured anopheline aggressiveness overlaid on risk maps computed using the built-up surface in a 300-m radius buffer for every pixel of the populated areas. 1a. Anopheline data from 1994-97 and risk map computed with the 1996 SPOT satellite image. Refer to Table 1 for names of the study sites. 1b. Anopheline data from 2007 and risk map computed with the the 2007 SPOT satellite image. Refer to Table 2 for names of the study sites.
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Figure 1: Measured anopheline aggressiveness overlaid on risk maps computed using the built-up surface in a 300-m radius buffer for every pixel of the populated areas. 1a. Anopheline data from 1994-97 and risk map computed with the 1996 SPOT satellite image. Refer to Table 1 for names of the study sites. 1b. Anopheline data from 2007 and risk map computed with the the 2007 SPOT satellite image. Refer to Table 2 for names of the study sites.

Mentions: As the built-up area was found to be the factor most strongly associated with Anopheles density in the statistical analysis, risk maps were derived from the built-up area in a 300-m radius buffer for every pixel of the populated areas, using the results of the fitted regression model. Continuous values of the computed risk map were discretized to generate three classes, which were based on a calculation of the terciles of the built-up surface in the 300-m radius buffer, followed by a manual adjustment. Breaking values were chosen at 20 and 26 Ha around every pixel. Figures 1a and 1b show the 1996 and 2007 risk maps overlaid with the measured 1994-97 and 2007 An. arabiensis densities. A comparison of the maps indicated an increase in built-up surfaces in 11 years (about 1 300 ha), and also depicted the evolution of the areas of each risk class in Dakar and its suburb. Table 6 gives a summary of the information provided by the risk maps. The built-up area, the related anopheline aggressiveness predicted by inverting the best statistical association (R2 = 0.57), the total surface of the risk class and the proportional surface of the risk class with respect to the total built-up area is given for each class. Table 1 and Table 2 provide the risk class at each catching point for the 1994-97 and 2007 studies, respectively.


Spatial heterogeneity and temporal evolution of malaria transmission risk in Dakar, Senegal, according to remotely sensed environmental data.

Machault V, Vignolles C, Pagès F, Gadiaga L, Gaye A, Sokhna C, Trape JF, Lacaux JP, Rogier C - Malar. J. (2010)

Measured anopheline aggressiveness overlaid on risk maps computed using the built-up surface in a 300-m radius buffer for every pixel of the populated areas. 1a. Anopheline data from 1994-97 and risk map computed with the 1996 SPOT satellite image. Refer to Table 1 for names of the study sites. 1b. Anopheline data from 2007 and risk map computed with the the 2007 SPOT satellite image. Refer to Table 2 for names of the study sites.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2944340&req=5

Figure 1: Measured anopheline aggressiveness overlaid on risk maps computed using the built-up surface in a 300-m radius buffer for every pixel of the populated areas. 1a. Anopheline data from 1994-97 and risk map computed with the 1996 SPOT satellite image. Refer to Table 1 for names of the study sites. 1b. Anopheline data from 2007 and risk map computed with the the 2007 SPOT satellite image. Refer to Table 2 for names of the study sites.
Mentions: As the built-up area was found to be the factor most strongly associated with Anopheles density in the statistical analysis, risk maps were derived from the built-up area in a 300-m radius buffer for every pixel of the populated areas, using the results of the fitted regression model. Continuous values of the computed risk map were discretized to generate three classes, which were based on a calculation of the terciles of the built-up surface in the 300-m radius buffer, followed by a manual adjustment. Breaking values were chosen at 20 and 26 Ha around every pixel. Figures 1a and 1b show the 1996 and 2007 risk maps overlaid with the measured 1994-97 and 2007 An. arabiensis densities. A comparison of the maps indicated an increase in built-up surfaces in 11 years (about 1 300 ha), and also depicted the evolution of the areas of each risk class in Dakar and its suburb. Table 6 gives a summary of the information provided by the risk maps. The built-up area, the related anopheline aggressiveness predicted by inverting the best statistical association (R2 = 0.57), the total surface of the risk class and the proportional surface of the risk class with respect to the total built-up area is given for each class. Table 1 and Table 2 provide the risk class at each catching point for the 1994-97 and 2007 studies, respectively.

Bottom Line: Linear regressions were fitted to identify the ecological factors associated with An. arabiensis aggressiveness measured in 1994-97 in the South and centre districts of Dakar.Risk maps for populated areas were computed and compared for 1996 and 2007 using the results of the statistical models.The evolution of the risk was quantified, and the results indicated there are benefits of urbanization in Dakar, since the proportion of the low risk population increased while urbanization progressed.

View Article: PubMed Central - HTML - PubMed

Affiliation: Unité de Recherche en Biologie et Epidémiologie Parasitaires, UMR6236, Institut de Recherche Biomédicale des Armées, Allée du Médecin colonel Jamot, Parc du Pharo, BP60109, 13262 Marseille cedex 07, France. vanessamachault@yahoo.com.br

ABSTRACT

Background: The United Nations forecasts that by 2050, more than 60% of the African population will live in cities. Thus, urban malaria is considered an important emerging health problem in that continent. Remote sensing (RS) and geographic information systems (GIS) are useful tools for addressing the challenge of assessing, understanding and spatially focusing malaria control activities. The objectives of the present study were to use high spatial resolution SPOT (Satellite Pour l'Observation de la Terre) satellite images to identify some urban environmental factors in Dakar associated with Anopheles arabiensis densities, to assess the persistence of these associations and to describe spatial changes in at-risk environments using a decadal time scale.

Methods: Two SPOT images from the 1996 and 2007 rainy seasons in Dakar were processed to extract environmental factors, using supervised classification of land use and land cover, and a calculation of NDVI (Normalized Difference Vegetation Index) and distance to vegetation. Linear regressions were fitted to identify the ecological factors associated with An. arabiensis aggressiveness measured in 1994-97 in the South and centre districts of Dakar. Risk maps for populated areas were computed and compared for 1996 and 2007 using the results of the statistical models.

Results: Almost 60% of the variability in anopheline aggressiveness measured in 1994-97 was explained with only one variable: the built-up area in a 300-m radius buffer around the catching points. This association remained stable between 1996 and 2007. Risk maps were drawn by inverting the statistical association. The total increase of the built-up areas in Dakar was about 30% between 1996 and 2007. In proportion to the total population of the city, the population at high risk for malaria fell from 32% to 20%, whereas the low-risk population rose from 29 to 41%.

Conclusions: Environmental data retrieved from high spatial resolution SPOT satellite images were associated with An. arabiensis densities in Dakar urban setting, which allowed to generate malaria transmission risk maps. The evolution of the risk was quantified, and the results indicated there are benefits of urbanization in Dakar, since the proportion of the low risk population increased while urbanization progressed.

Show MeSH
Related in: MedlinePlus