Automated Author Profile

Hemingway, Janet

Current S-Index

12.2

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.9

Average Dataset Index per dataset

Total Datasets

14

Total datasets for this author

Average FAIR Score

77.6%

Average FAIR Score per dataset

Total Citations

11

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

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.

We provide spatial data files for:
1) district-level weighted means for pyrethroid resistance,
2) the maximum pyrethroid resistance value (minimum mortality value) predicted within each district,
3) the probability that pyrethroid resistance exceeds the World Health Organization (WHO) threshold for susceptibility,
4) the probability that pyrethroid resistance exceeds the World Health Organization (WHO) threshold for confirmed resistance, and
5) the probability that pyrethroid resistance falls within the World Health Organization (WHO) range for deployment of PBO-treated nets.
These data are all for deltametrin resistance in Anopheles gambiae s.l. in 2017. All of the above files are in shapefile format.

We also provide spatial data on the overlapping presence of Anopheles gambiae s.l. and the other dominant vector in this region, Anopheles funestus. These files are in GeoTIFF format.
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).

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].

Authors

  • Moyes, Catherine L. ;
  • Athinya, Duncan Kobia ;
  • Seethaler, Tara ;
  • Battle, Katherine E. ;
  • Sinka, Marianne ;
  • Hadi, Melinda P. ;
  • Hemingway, Janet ;
  • Coleman, Michael ;
  • Hancock, Penny
0 Citations0 Mentions85% FAIR0.3 Dataset Index
10.6084/m9.figshare.12435248.v12020

Mapping trends in insecticide resistance phenotypes in African malaria vectors

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 (http://cran.r-project.org/web/views/Spatial.html).

In addition, files containing the numerical values behind each figure in the linked article are provided in files S1 to S8.

Authors

  • Hancock, Penelope ;
  • Hendriks, Chantal ;
  • Julie-Anne Tangena ;
  • Gibson, Harry S. ;
  • Hemingway, Janet ;
  • Coleman, Michael ;
  • Gething, Peter ;
  • Bhatt, Samir ;
  • Moyes, Catherine L.
0 Citations0 Mentions56% FAIR1.4 Dataset Index
10.6084/m9.figshare.9912623.v12020

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.

We provide spatial data files for:
1) district-level weighted means for pyrethroid resistance,
2) the maximum pyrethroid resistance value (minimum mortality value) predicted within each district,
3) the probability that pyrethroid resistance exceeds the World Health Organization (WHO) threshold for susceptibility,
4) the probability that pyrethroid resistance exceeds the World Health Organization (WHO) threshold for confirmed resistance, and
5) the probability that pyrethroid resistance falls within the World Health Organization (WHO) range for deployment of PBO-treated nets.
These data are all for deltametrin resistance in Anopheles gambiae s.l. in 2017. All of the above files are in shapefile format.

We also provide spatial data on the overlapping presence of Anopheles gambiae s.l. and the other dominant vector in this region, Anopheles funestus. These files are in GeoTIFF format.
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).

Further information is given in the article that describes this work: Moyes, CL et al. (2020) Evaluating insecticide resistance across African districts to aid malaria control decisions. Proceedings of the National Academy of Science, 117, www.pnas.org/cgi/doi/10.1073/pnas.2006781117.

Authors

  • Moyes, Catherine L. ;
  • Athinya, Duncan Kobia ;
  • Seethaler, Tara ;
  • Battle, Katherine E. ;
  • Sinka, Marianne ;
  • Hadi, Melinda P. ;
  • Hemingway, Janet ;
  • Coleman, Michael ;
  • Hancock, Penny
2 Citations0 Mentions15% FAIR0.8 Dataset Index
10.6084/m9.figshare.124352482020

Mapping trends in insecticide resistance phenotypes in African malaria vectors

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 (http://cran.r-project.org/web/views/Spatial.html).

In addition, files containing the numerical values behind each figure in the linked article are provided in files S1 to S8.

Authors

  • Hancock, Penelope ;
  • Hendriks, Chantal ;
  • Julie-Anne Tangena ;
  • Gibson, Harry S. ;
  • Hemingway, Janet ;
  • Coleman, Michael ;
  • Gething, Peter ;
  • Bhatt, Samir ;
  • Moyes, Catherine L.
2 Citations0 Mentions85% FAIR0.8 Dataset Index
10.6084/m9.figshare.99126232020

MOESM2 of Developing global maps of insecticide resistance risk to improve vector control

Additional file 2. Pyrethroid resistance by subnational area for three time periods; the number of bioassay records for each first order administrative division is given for 1980â 1999, 2000â 2007, and 2008â 2015 together with the actual year range for which data are available in each instance, the number of mosquitoes assayed, and the average mortality as shown in Fig. 2.

Authors

  • Coleman, Michael ;
  • Hemingway, Janet ;
  • Gleave, Katherine ;
  • Wiebe, Antoinette ;
  • Gething, Peter ;
  • Moyes, Catherine
1 Citation0 Mentions85% FAIR0.7 Dataset Index
10.6084/m9.figshare.c.3699982_d1.v12017

MOESM15 of Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance

Additional file 15. Tables of summary insecticide resistance data. A separate worksheet is provided for each insecticide class for each of the Gambiae complex and the Funestus group.

Authors

  • Wiebe, Antoinette ;
  • Longbottom, Joshua ;
  • Gleave, Katherine ;
  • Shearer, Freya ;
  • Sinka, Marianne ;
  • N. Massey ;
  • Cameron, Ewan ;
  • Bhatt, Samir ;
  • Gething, Peter ;
  • Hemingway, Janet ;
  • Smith, David ;
  • Coleman, Michael ;
  • Moyes, Catherine
1 Citation0 Mentions85% FAIR0.7 Dataset Index
10.6084/m9.figshare.c.3696217_d8.v12017

MOESM2 of Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance

Additional file 2. Presence and background datasets for each species. Each dataset is provided in a separate worksheet within the workbook.

Authors

  • Wiebe, Antoinette ;
  • Longbottom, Joshua ;
  • Gleave, Katherine ;
  • Shearer, Freya ;
  • Sinka, Marianne ;
  • N. Massey ;
  • Cameron, Ewan ;
  • Bhatt, Samir ;
  • Gething, Peter ;
  • Hemingway, Janet ;
  • Smith, David ;
  • Coleman, Michael ;
  • Moyes, Catherine
1 Citation0 Mentions85% FAIR0.7 Dataset Index
10.6084/m9.figshare.c.3696217_d3.v12017

MOESM2 of Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance

Additional file 2. Presence and background datasets for each species. Each dataset is provided in a separate worksheet within the workbook.

Authors

  • Wiebe, Antoinette ;
  • Longbottom, Joshua ;
  • Gleave, Katherine ;
  • Shearer, Freya ;
  • Sinka, Marianne ;
  • N. Massey ;
  • Cameron, Ewan ;
  • Bhatt, Samir ;
  • Gething, Peter ;
  • Hemingway, Janet ;
  • Smith, David ;
  • Coleman, Michael ;
  • Moyes, Catherine
0 Citations0 Mentions85% FAIR0.3 Dataset Index
10.6084/m9.figshare.c.3696217_d32017

MOESM15 of Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance

Additional file 15. Tables of summary insecticide resistance data. A separate worksheet is provided for each insecticide class for each of the Gambiae complex and the Funestus group.

Authors

  • Wiebe, Antoinette ;
  • Longbottom, Joshua ;
  • Gleave, Katherine ;
  • Shearer, Freya ;
  • Sinka, Marianne ;
  • N. Massey ;
  • Cameron, Ewan ;
  • Bhatt, Samir ;
  • Gething, Peter ;
  • Hemingway, Janet ;
  • Smith, David ;
  • Coleman, Michael ;
  • Moyes, Catherine
0 Citations0 Mentions85% FAIR0.3 Dataset Index
10.6084/m9.figshare.c.3696217_d82017

MOESM2 of Developing global maps of insecticide resistance risk to improve vector control

Additional file 2. Pyrethroid resistance by subnational area for three time periods; the number of bioassay records for each first order administrative division is given for 1980â 1999, 2000â 2007, and 2008â 2015 together with the actual year range for which data are available in each instance, the number of mosquitoes assayed, and the average mortality as shown in Fig. 2.

Authors

  • Coleman, Michael ;
  • Hemingway, Janet ;
  • Gleave, Katherine ;
  • Wiebe, Antoinette ;
  • Gething, Peter ;
  • Moyes, Catherine
0 Citations0 Mentions85% FAIR0.9 Dataset Index
10.6084/m9.figshare.c.3699982_d12017