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  • Updated March 21, 2016 | Dataset date: Jan 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on January 19, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: xx201401_ML1 Most likely food security outcome for January-March 2014 xx201401_ML2 Most likely food security outcome for April-June 2014 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)
  • Updated March 21, 2016 | Dataset date: Apr 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on July 17, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: WA201304_ML1 Most likely food security outcome for April-June 2014 WA201304_ML2 Most likely food security outcome for July-September 2014 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)
  • Updated March 21, 2016 | Dataset date: Jul 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa. It was last updated on September 29, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: WA201304_ML1 Most likely food security outcome for July-September 2014 WA201304_ML2 Most likely food security outcome for October-December 2014 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 March 21, 2016 | Dataset date: Oct 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa. It was last updated on November 13, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: WA201304_ML1 Most likely food security outcome for October-December 2014 WA201304_ML2 Most likely food security outcome for January-March 2015 Where xx is one of the region codes listed above. 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 March 8, 2016 | Dataset date: Feb 25, 2016
    This dataset updates: Never
    This map illustrates satellite-detected shelters and other buildings at the Minawao refugee settlement, Mayo-Tsanaga District, Far North Province in Cameroon as seen by the WorldView-2 satellite on 19 November 2015. UNOSAT analysed a total of 11,777 structures (9,390 tent shelters, 551 administrative buildings, 634 improvised shelters, and 1,202 semi-permanent shelters) within 502 hectares of the settlement area. Previous analysis from 10 March 2015 indicated 5, 220 shelters over 261 hectares and thus the updated analysis indicates an increase of approximately 126% on shelters and 93% in land occupied. Note that apparently adjoining, contiguous shelters were counted as a single shelter which may thus underestimate total number of shelters. This is a preliminary analysis & has not yet been validated in the field. Please send ground feedback to UNITAR/UNOSAT.
  • 60+ Downloads
    Updated February 1, 2016 | Dataset date: Dec 31, 2015
    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 29, 2015 | Dataset date: Oct 1, 2015
    Nigeria Admin Level 2 boundaries created by the Bill & Melinda Gates foundation. The boundaries were made by mapping all settlements, and then using the Ward Level 2 admin attributes and the ESRI Thiessen polygons tool to create boundaries at each admin level.
  • 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)
  • This map illustrates satellite-detected shelters and other buildings at the Minawao refugee settlement, Mayo-Tsanaga District, Far North Province, in Cameroon as seen by the WorldView-2 satellite on 10 March 2015. UNOSAT analyzed a total of 5,220 structures (4,027 tent shelters, 903 improvised shelters and 290 administrative buildings) within the 261 hectares of the settlement area. Note that apparently adjoining, contiguous shelters were counted as a single shelter which may thus underestimate total number of shelters. This is a preliminary analysis & has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT
  • 300+ Downloads
    Updated November 24, 2015 | Dataset date: Feb 2, 2012
    This dataset updates: Every year
    The geodata represents the digital elevation model of Nigeria. Spatial resolution: 90 meters.
  • 300+ Downloads
    Updated November 24, 2015 | Dataset date: Feb 2, 2012
    This dataset updates: Every year
    The geodata represents the hydrography network of Nigeria. Scale: 1:1,000,000
  • 100+ Downloads
    Updated November 24, 2015 | Dataset date: Nov 1, 2012
    This dataset updates: Never
    The dataset represents the extent of floods in Nigeria from July to November 2012.
  • 800+ Downloads
    Updated November 24, 2015 | Dataset date: Oct 21, 2014
    This dataset updates: Every year
    The dataset represents all settlements of Nigeria with codification of capitals.
  • 500+ Downloads
    Updated November 24, 2015 | Dataset date: Sep 7, 2014-Nov 4, 2015
    This dataset updates: Never
    Cumulative number of health-care workers that died from Ebola infection. Extracted from WHO: Ebola Response Roadmap Situation Reports, the latest of which was on 4 November 2015.
  • 400+ Downloads
    Updated November 24, 2015 | Dataset date: Dec 31, 2014
    This dataset updates: Every six months
    Total number of existing beds in EVD treatment units. Extracted from WHO: Ebola Response Roadmap Situation Reports, the latest of which was on 31 December 2014.
  • 700+ Downloads
    Updated November 24, 2015 | Dataset date: Sep 7, 2014-Nov 4, 2015
    This dataset updates: Never
    Cumulative number of health-care workers infected with Ebola. Extracted from WHO: Ebola Response Roadmap Situation Reports, the last of which was on 4 November 2015.
  • 100+ Downloads
    Updated November 24, 2015 | Dataset date: Jan 1, 2013-Apr 1, 2014
    This dataset updates: Never
    Here we provide version 1 Flowminder (www.flowminder.org) human mobility models for West Africa, together with WorldPop population density data for the region, to support ongoing efforts to control the ebola outbreak. Before downloading any data, please read the documention carefully as it provides details on the datasets and models provided through the links below. The mobility data refer to estimated patterns before the Ebola outbreak and should be interpreted with caution for Ebola affected countries as mobility patters are known to have changed. Additional discussion by the authors around the use of mobile operator data for epidemilogical research see: http://currents.plos.org/outbreaks/article/containing-the-ebola-outbreak-the-potential-and-challenge-of-mobile-network-data/
  • 300+ Downloads
    Updated November 24, 2015 | Dataset date: Dec 5, 2014
    This dataset updates: Every three months
    Who, What, Where (3W) dataset on the Ebola response effort. Some entries have a maximum level of desegregation up to administrative level 3. The dataset contains data from Guinea, Liberia, Sierra Leone, and Nigeria. This dataset is updated weekly. Last Update 17 Nov. 2014 Note: If your humanitarian organization would like to make a correction or update the dataset, please contact the OCHA focal point for the respective country. Contacts can be found at https://wca.humanitarianresponse.info/fr/emergencies/virus-ebola
  • 600+ Downloads
    Updated November 24, 2015 | Dataset date: Apr 2, 2015
    This dataset updates: Every six months
    Ebola outbreak time series data at national and sub national levels since March 2014. Data compiled manually from a number of published reports. Updated by OCHA ROWCA every working day.
  • 60+ Downloads
    Updated November 24, 2015
    This dataset updates: Never
    The Open Humanitarian Data Repository contains a comprehensive repository of openly available GIS baseline data for the Ebola Outbreak in West-Africa.