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  • The GAR15 global exposure database is based on a top-down approach where statistical information including socio-economic, building type, and capital stock at a national level are transposed onto the grids of 5x5 or 1x1 using geographic distribution of population data and gross domestic product (GDP) as proxies.
  • 100+ Downloads
    Updated December 2, 2015 | Dataset date: Sep 14, 2015
    This dataset updates: Never
    The dataset represents the compilation of Global and Severe Acute Malnutrition in Mauritania between 2006 and 2015. The dataset has been collected mosty twice a year (post harvest and lean season).
  • 200+ Downloads
    Updated November 25, 2015 | Dataset date: Sep 14, 2015
    This dataset updates: Every three months
    The dataset represents the latest Severe Acute Malnutrition Prevalence available for the Sahel nine countries (Burkina Faso, Cameroon, Chad, the Gambia, Mali, Mauritania, Niger, Nigeria, Senegal).
  • 100+ Downloads
    Updated November 25, 2015 | Dataset date: Nov 6, 2015
    This dataset updates: Every year
    This dataset is a summary of the latest prevalences of the Global Acute Malnutrition of Sahel by Admin1.
  • 10+ Downloads
    Updated November 25, 2015 | Dataset date: Sep 30, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on September 30, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: westafrica201304_ML1 Most likely food security outcome for July-September 2015 westafrica201304_ML2 Most likely food security outcome for October-December 2015 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated November 25, 2015 | Dataset date: Jun 30, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on June 30, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: westafrica201304_ML1 Most likely food security outcome for April-June 2015 westafrica201304_ML2 Most likely food security outcome for July-September 2015 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated November 25, 2015 | Dataset date: Mar 25, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa. It was last updated on March 25, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: westafrica201304_ML1 Most likely food security outcome for January-March 2015 westafrica201304_ML2 Most likely food security outcome for April-June 2015 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 60+ Downloads
    Updated November 25, 2015 | Dataset date: Jan 25, 2012
    This dataset updates: Every year
    The present geodata represents the railway network.
  • 60+ Downloads
    Updated November 25, 2015 | Dataset date: Jan 25, 2012
    This dataset updates: Every year
    The present geodata represents the roads network of Mauritania.
  • 400+ Downloads
    Updated November 24, 2015 | Dataset date: May 14, 2015
    This dataset updates: Every month
    The Income Activities dataset includes data on income generation at the household level. Sources of income listed include labor, agriculture, asset sales, and remittances, among others. It is available for 32 countries.