Research Data Leeds Repository

Citation

Smith, Mark and Willis, Thomas and Alfieri, Lorenzo and James, William H. M. and Trigg, Mark and Yamazaki, Dai and Hardy, Andrew and Bisselink, Berny and De Roo, Ad and Macklin, Mark and Thomas, Christopher J. (2020) LIS-MAL estimates of hydro-climatic suitability for malaria transmission in Africa (1971-2100). University of Leeds. [Dataset] https://doi.org/10.5518/786

Dataset description

Estimates of climatic suitability for malaria transmission in Africa over the periods 1971-2005, 2011-2040, 2041-2070 and 2071-2100. Seven climate projections using the high concentration scenario (RCP 8.5) were produced with EC-EARTH3-HR v3.1 by the Swedish Meteorological and Hydrological Institute (described in the Excel workbook). These were used to run the Lisflood hydrological model at 0.5 degree resolution and estimate hydro-climatic suitability for malaria transmission based on the Mordecai temperature ranges and Lisflood-predicted surface water availability. For each time period and each of the seven GCMs (i.e. 28 rasters) a 0.5 degree raster layer of the ‘number of suitable months for malaria transmission’ over Africa is presented in the form of a Geotiff. An Excel spreadsheet summarises these files in terms of total area in each 1 month category for the Lisflood estimates and the estimated changes in suitability between time periods. The population estimated to live within areas hydro-climatically suitable for malaria transmission is also presented, incorporating both present day estimates and future predictions. These data are broken down by country and summarised in terms of ‘population months’ for each time period.

Divisions:	Faculty of Environment > School of Geography
Related resources:	Location Type https://doi.org/10.1038/s41467-020-18239-5 Publication https://eprints.whiterose.ac.uk/165068/ Publication https://github.com/ec-jrc/lisflood-code Software
License:	MIT License
Date deposited:	30 Jul 2020 11:35
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/715
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Smith, Mark https://orcid.org/0000-0003-4361-9527 University of Leeds https://ror.org/024mrxd33 ror Willis, Thomas https://orcid.org/0000-0003-0103-1805 University of Leeds https://ror.org/024mrxd33 ror Alfieri, Lorenzo https://orcid.org/0000-0002-3616-386X Joint Research Centre https://ror.org/02qezmz13 ror James, William H. M. https://orcid.org/0000-0002-3273-4688 University of Leeds https://ror.org/024mrxd33 ror Trigg, Mark https://orcid.org/0000-0002-8412-9332 University of Leeds https://ror.org/024mrxd33 ror Yamazaki, Dai https://orcid.org/0000-0002-6478-1841 University of Tokyo https://ror.org/057zh3y96 ror Hardy, Andrew https://orcid.org/0000-0002-7928-8873 Aberystwyth University https://ror.org/015m2p889 ror Bisselink, Berny https://orcid.org/0000-0001-5203-0410 Joint Research Centre https://ror.org/02qezmz13 ror De Roo, Ad https://orcid.org/0000-0001-9859-9127 Joint Research Centre https://ror.org/02qezmz13 ror Macklin, Mark https://orcid.org/0000-0003-4167-2033 University of Lincoln https://ror.org/03yeq9x20 ror Thomas, Christopher J. https://orcid.org/0000-0003-4939-9959 University of Lincoln https://ror.org/03yeq9x20 ror Type of data: Dataset Research funders: NERC, NERC Grant numbers: NE/H022740/1, NE/P013481/1 Publication date: 2020 Resource language: English Metadata language: English Research project title: HYDROMAL: Hydro-dynamic drivers of malaria transmission hazard in Africa., FLOODMAL. Publisher: University of Leeds Contact email: M.W.Smith@leeds.ac.uk Last Modified: 30 Oct 2024 15:44

Files

Documentation

Dataset Summary [294kB] Dataset Summary [294kB] Dataset Summary [294kB] Security: Anyone File name: dataset_summary.pdf Content type: Documentation Description: Dataset description Mime-Type: application/pdf License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 294kB

Q_seasonlength description [713B] Q_seasonlength description [713B] Q_seasonlength description [713B] Security: Anyone File name: Readme.txt Content type: Documentation Mime-Type: text/plain License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 713B

Data

Raw data [72kB] Raw data [72kB] Raw data [72kB] Security: Anyone File name: data.xlsx Content type: Data Description: Excel file with all quantitative data Mime-Type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 72kB

Q_seasonlength [273kB] Q_seasonlength [273kB] Q_seasonlength [273kB] Security: Anyone File name: LISMAL_Suitability.zip Content type: Data Description: TIF file for each forcing model and time period (in subfolders) Mime-Type: application/zip License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 273kB

Program

Python code [11kB] Python code [11kB] Python code [11kB] Security: Anyone File name: Code.zip Content type: Program Mime-Type: application/zip License: MIT License File size: 11kB

mit_license.txt [1kB] mit_license.txt [1kB] mit_license.txt [1kB] Security: Anyone File name: mit_license.txt Content type: Program Mime-Type: text/plain File size: 1kB