Mapping trends in insecticide resistance phenotypes in African malaria vectors
Domaine:
healthcaregeospatialType de record:
dataset
Créateur:
HanHenJulGib
Éditeur:
fig
Hôte:
The mean predictions for the prevalence of resistance (susceptibility test mortality) were produced by a model that used susceptibility test data from field populations and a large number of potential explanatory variables. Full details are given in the linked PLoS Biology article.
A zip folder is provided for each year from 2005 to 2017. Each zip folder contains a raster comprising of a GRD and GRI file. Each raster has five bands:
- band 1 is mortality after alpha-cypermethrin exposure;- band 2 is mortality after DDT exposure;- band 3 is mortality after deltametrin exposure;- band 4 is mortality after lambda-cyhalothrin exposure;- band 5 is mortality after permethrin exposure.
The rasters are at a 2.5 arcminute (approx. 5 km) resolution. Each grid cell has a value for the predicted mean prevalence of resistance (susceptibility test mortality) on a scale 0.0 to 1.0.
The above data can be visualised and processed in a range of geographical information system packages (e.g. ArcGIS and QGIS) or spatial data packages in R (cran.r-project.org).
In addition, files containing the numerical values behind each figure in the linked article are provided in files S1 to S8.
A zip folder is provided for each year from 2005 to 2017. Each zip folder contains a raster comprising of a GRD and GRI file. Each raster has five bands:
- band 1 is mortality after alpha-cypermethrin exposure;- band 2 is mortality after DDT exposure;- band 3 is mortality after deltametrin exposure;- band 4 is mortality after lambda-cyhalothrin exposure;- band 5 is mortality after permethrin exposure.
The rasters are at a 2.5 arcminute (approx. 5 km) resolution. Each grid cell has a value for the predicted mean prevalence of resistance (susceptibility test mortality) on a scale 0.0 to 1.0.
The above data can be visualised and processed in a range of geographical information system packages (e.g. ArcGIS and QGIS) or spatial data packages in R (cran.r-project.org).
In addition, files containing the numerical values behind each figure in the linked article are provided in files S1 to S8.
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