Datasets from evaluating insecticide resistance across African districts to aid malaria control decisions

The data loaded here were generated by a published geostatistical ensemble model to bridge gaps in the available surveillance data and consider the likelihood that resistance exceeds recommended thresholds. <br><br>We provide spatial data files for: <br>1) district-level weighted means for pyrethroid resistance, <br>2) the maximum pyrethroid resistance value (minimum mortality value) predicted within each district, <br>3) the probability that pyrethroid resistance exceeds the World Health Organization (WHO) threshold for susceptibility, <br>4) the probability that pyrethroid resistance exceeds the World Health Organization (WHO) threshold for confirmed resistance, and <br>5) the probability that pyrethroid resistance falls within the World Health Organization (WHO) range for deployment of PBO-treated nets. <br>These data are all for deltametrin resistance in <i>Anopheles gambiae</i> s.l. in 2017. All of the above files are in shapefile format.<br><br>We also provide spatial data on the overlapping presence of <i>Anopheles gambiae</i> s.l. and the other dominant vector in this region, <i>Anopheles funestus. </i>These files are in GeoTIFF format.<br>All of the above data can be visualised, processed and analysed in a range of geographical information system packages (e.g. ArcGIS and QGIS) or spatial data packages in R (http://cran.r-project.org/web/views/Spatial.html). <br><br>Further information is given in the article describing this work: https://www.medrxiv.org/content/10.1101/2020.04.01.20049593v1 [to be replaced by the peer-reviewed article once published].<br>