Data Grid Completeness defines
a set of core data that are essential for preparedness and emergency response.
For select countries, the HDX Team and trusted partners evaluate datasets available on HDX and add those meeting the definition of a core data category to the Data Grid Completeness board above. Please help us improve this feature by sending your feedback to
hdx@un.org.
Legend:
Presence, freshness, and quality of dataset
Dataset fully matches criteria and is up-to-date
Dataset partially matches criteria and/or is not up-to-date
Updated
January 29, 2016
| Dataset date: December 31, 2015-December 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.
Updated
November 24, 2015
| Dataset date: May 14, 2015-May 14, 2015
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.
Updated
November 24, 2015
| Dataset date: May 14, 2015-May 14, 2015
The Coping Strategy Index dataset measures the severity and frequency of the strategies that households use to cope with acute food insecurity. The strategies vary from borrowing food or money from neighbors to selling household assets. This data is available for 31 countries at a sub-national level.
Updated
November 24, 2015
| Dataset date: May 13, 2015-May 13, 2015
The Food Consumption Score (FCS) dataset is based on the FCS indicator, which assigns a food security score based on food consumption and diets. This data is available sub-nationally for 38 countries, such as Nepal and Sierra Leone.
Updated
October 14, 2015
| Dataset date: September 30, 2015-September 30, 2015
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)
Updated
October 14, 2015
| Dataset date: March 25, 2015-March 25, 2015
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)
Updated
October 14, 2015
| Dataset date: October 01, 2014-October 01, 2014
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)
Updated
October 14, 2015
| Dataset date: July 01, 2014-July 01, 2014
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)
Updated
October 14, 2015
| Dataset date: April 01, 2014-April 01, 2014
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
October 14, 2015
| Dataset date: January 01, 2014-January 01, 2014
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
October 14, 2015
| Dataset date: October 01, 2013-October 01, 2013
This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa.
It was last updated on November 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity.
The two shapefiles represent the two analytic periods:
xx201304_ML1 Most likely food security outcome for October-December 2013
xx201304_ML2 Most likely food security outcome for January-March 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
October 14, 2015
| Dataset date: July 01, 2013-July 01, 2013
This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa.
It was last updated on July 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity.
The two shapefiles represent the two analytic periods:
xx201304_ML1 Most likely food security outcome for July-September 2013
xx201304_ML2 Most likely food security outcome for October-December 2013
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
October 14, 2015
| Dataset date: April 01, 2013-April 01, 2013
This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa.
It was last updated on June 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity.
The two shapefiles represent the two analytic periods:
xx201304_ML1 Most likely food security outcome for April-June 2013
xx201304_ML2 Most likely food security outcome for July-September 2013
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
October 14, 2015
| Dataset date: January 01, 2013-January 01, 2013
This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa.
It was last updated on January 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity.
The two shapefiles represent the two analytic periods:
xx201304_ML1 Most likely food security outcome for January-March 2013
xx201304_ML2 Most likely food security outcome for April-June 2013
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
August 28, 2015
| Dataset date: January 01, 2013-April 01, 2014
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/
