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Risk Mapping of Anopheles gambiae s.l. Densities Using Remotely-Sensed Environmental and Meteorological Data in an Urban Area: Dakar, Senegal

Vanessa Machault; Cécile Vignolles; Frédéric Pagès; Libasse Gadiaga; Yves M. Tourre; Abdoulaye Gaye; Cheikh Sokhna; Jean-François Trape; Jean-Pierre Lacaux; Christophe Rogier

Title:
Risk Mapping of Anopheles gambiae s.l. Densities Using Remotely-Sensed Environmental and Meteorological Data in an Urban Area: Dakar, Senegal
Author(s):
Machault, Vanessa
Vignolles, Cécile
Pagès, Frédéric
Gadiaga, Libasse
Tourre, Yves M.
Gaye, Abdoulaye
Sokhna, Cheikh
Trape, Jean-François
Lacaux, Jean-Pierre
Rogier, Christophe
Date:
Type:
Articles
Department(s):
Lamont-Doherty Earth Observatory
Volume:
7
Persistent URL:
Book/Journal Title:
PLOS ONE
Geographic Area:
Senegal--Dakar
Abstract:
Introduction High malaria transmission heterogeneity in an urban environment is basically due to the complex distribution of Anopheles larval habitats, sources of vectors. Understanding 1) the meteorological and ecological factors associated with differential larvae spatio-temporal distribution and 2) the vectors dynamic, both may lead to improving malaria control measures with remote sensing and high resolution data as key components. In this study a robust operational methodology for entomological malaria predictive risk maps in urban settings is developed. Methods The Tele-epidemiology approach, i.e., 1) intensive ground measurements (Anopheles larval habitats and Human Biting Rate, or HBR), 2) selection of the most appropriate satellite data (for mapping and extracting environmental and meteorological information), and 3) use of statistical models taking into account the spatio-temporal data variability has been applied in Dakar, Senegal. Results First step was to detect all water bodies in Dakar. Secondly, environmental and meteorological conditions in the vicinity of water bodies favoring the presence of Anopheles gambiae s.l. larvae were added. Then relationship between the predicted larval production and the field measured HBR was identified, in order to generate An. gambiae s.l. HBR high resolution maps (daily, 10-m pixel in space). Discussion and Conclusion A robust operational methodology for dynamic entomological malaria predictive risk maps in an urban setting includes spatio-temporal variability of An. gambiae s.l. larval habitats and An. gambiae s.l. HBR. The resulting risk maps are first examples of high resolution products which can be included in an operational warning and targeting system for the implementation of vector control measures.
Subject(s):
Malaria
Larvae
Epidemiology
Rain and rainfall
Publisher DOI:
https://doi.org/10.1371/journal.pone.0050674
Item views
15
Metadata:
text | xml
Suggested Citation:
Vanessa Machault, Cécile Vignolles, Frédéric Pagès, Libasse Gadiaga, Yves M. Tourre, Abdoulaye Gaye, Cheikh Sokhna, Jean-François Trape, Jean-Pierre Lacaux, Christophe Rogier, , Risk Mapping of Anopheles gambiae s.l. Densities Using Remotely-Sensed Environmental and Meteorological Data in an Urban Area: Dakar, Senegal, Columbia University Academic Commons, .

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