Data Grid Completeness
12/27 Core Data 27 Datasets 15 Organisations Show legend
What is Data Grid Completeness?
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.
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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
  • No dataset found matching the criteria
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Affected People
3 Datasets
Internally-Displaced Persons
International Organization for Migration
Refugees & Persons of Concern
Returnees
Humanitarian Profile Locations
Humanitarian Needs
Casualties
Coordination & Context
6 Datasets
3w - Who is doing what where
International Aid Transparency Initiative
Affected Areas
Conflict Events
Humanitarian Access
Transportation Status
Damaged & Destroyed Buildings
Food Security & Nutrition
2 Datasets
Food security
Integrated Food Security Phase Classification (IPC)
Global Acute Malnutrition Rate
Severe Acute Malnutrition Rate
Food Prices
WFP - World Food Programme
Geography & Infrastructure
9 Datasets
Administrative Divisions
Roads
Humanitarian OpenStreetMap Team (HOT)
Airports
WFP - World Food Programme
Humanitarian OpenStreetMap Team (HOT)
Health & Education
5 Datasets
Health Facilities
Global Healthsites Mapping Project
Humanitarian OpenStreetMap Team (HOT)
Education Facilities
Affected Schools
Population & Socio-economy
2 Datasets
Baseline Population
Baseline Population by Age & Sex
Poverty Rate
Oxford Poverty & Human Development Initiative
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  • 400+ Downloads
    Updated 18 July 2021 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    Food Security Indicators for Haiti. Contains data from the FAOSTAT bulk data service.
  • 500+ Downloads
    Updated 22 June 2021 | Dataset date: January 01, 2011-December 31, 2020
    This dataset updates: Every six months
    Data collated by UNHCR, containing information about forcibly displaced populations and stateless persons, spanning across 70 years of statistical activities. The data includes the countries / territories of asylum and origin. Specific resources are available for end-year population totals, demographics, asylum applications, decisions, and solutions availed by refugees and IDPs (resettlement, naturalisation or returns).
  • 400+ Downloads
    Updated 30 May 2021 | Dataset date: January 01, 2008-December 31, 2020
    This dataset updates: Every year
    Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. "People Displaced" refers to the number of people living in displacement as of the end of each year. "New Displacement" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once. Contains data from IDMC's Global Internal Displacement Database.
  • 50+ Downloads
    Updated 8 May 2021 | Dataset date: May 19, 2020-May 19, 2020
    This dataset updates: As needed
    Pool fund Extended allocation Details
  • 5700+ Downloads
    Updated 6 May 2021 | Dataset date: April 01, 2021-September 18, 2021
    This dataset updates: As needed
    The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. The data is provided for 93 low and middle-income countries at 2.4km resolution. More details are available here: https://dataforgood.fb.com/tools/relative-wealth-index/ Research publication (preprint) for the Relative Wealth Index is available here: https://arxiv.org/abs/2104.07761 Press coverage of the release of the Relative Wealth Index here: https://www.fastcompany.com/90625436/these-new-poverty-maps-could-reshape-how-we-deliver-humanitarian-aid An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/
  • 100+ Downloads
    Updated 4 May 2021 | Dataset date: January 01, 1990-December 31, 2030
    This dataset updates: Every year
    The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities. The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions. The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.
  • 20+ Downloads
    Updated 4 May 2021 | Dataset date: November 02, 2012-November 02, 2012
    This dataset updates: Never
    This is "Flood vectors - TerraSAR-X (02 November 2012)" of the Tropical Cyclone analysis for Haiti which began on 30 October 2012. It includes 2,628 satellite detected water bodies with a spatial extent of 4.35 square kilometers derived from the TerraSAR-...
  • Updated 4 May 2021 | Dataset date: November 02, 2012-November 02, 2012
    This dataset updates: Never
    This is "Flood vectors - Radarsat-2 (02 November 2012)" of the Tropical Cyclone analysis for Haiti which began on 30 October 2012. It includes 5,842 satellite detected water bodies with a spatial extent of 319.98 square kilometers derived from the Radarsa...
  • 200+ Downloads
    Updated 23 April 2021 | Dataset date: October 05, 2016-October 05, 2016
    This dataset updates: Every day
    Includes Assessment, two shapefiles: basemaps
  • 700+ Downloads
    Updated 23 April 2021 | Dataset date: October 06, 2016-October 06, 2016
    This dataset updates: Every day
    Partial Assessment and 3W matrix ,Hurricane Matthew. as of 06.10.2016
  • 100+ Downloads
    Updated 15 April 2021 | Dataset date: March 01, 2020-December 31, 2020
    This dataset updates: Every three months
    Under the leadership of UNDP and DCO, an inter-agency task team developed the UN framework for the immediate socio-economic response to COVID-19 (adopted in April 2020) to govern its response over 12 to 18 months. To measure the UN’s support to the socio-economic response and recovery, UN entities developed a simple monitoring framework with 18 programmatic indicators (endorsed by the UNSDG in July 2020). Lead entities – based on their mandate and comparative advantage – were nominated to lead the development of methodological notes for each indicator and lead the collection of data at the country level. These lead entities reported through the Office of the Resident Coordinators the collective UN results on a quarterly basis through UN Info. All 2020 data was reported by March 2021. This is the UN development system’s first comprehensive attempt at measuring its collective programming contribution and results. These programmatic indicators enabled the UN system to monitor the progress and achievements of UNCT’s collective actions in socio-economic response. In support of the Secretary-General’s call for a "… single, consolidated dashboard to provide up-to-date visibility on [COVID-19] activities and progress across all pillars” all data was published in real time on the COVID-19 data portal, hosted by DCO. The data is disaggregated by geography (rural/urban), sex, age group and at-risk populations -- to measure system-wide results on the socio-economic response to the pandemic, in order to ensure UNDS accountability and transparency for results.
  • 30+ Downloads
    Updated 6 April 2021 | Dataset date: April 01, 2020-December 12, 2020
    This dataset updates: Never
    Catholic Medical Mission Board (CMMB) working across the five countries of Haiti, Kenya, Peru, South Sudan, and Zambia, surveyed the 253 health facilities we partner with to determine their preparedness to prevent and respond to the COVID-19 pandemic in April of 2020. The assessment was considered a "baseline" with follow up data collected for 242 health facilities in November of 2021. Altogether there were 213 health facilities assessed twice. the core areas of focus were: medical equipment and supplies, training, waste disposal, IPC practices, triage and isolation, water and sanitation, and operations and accessibility.
  • 20+ Downloads
    Updated 2 April 2021 | Dataset date: May 05, 2020-May 05, 2020
    This dataset updates: Never
    This data was developed as part of the Modelling Exposure Through Earth Observation Routines (METEOR) project and is a Level 1, or a global-quality exposure data set. Minimal country-specific data was collected. The data is intended for CAT modeling and loss estimation. Repurposing this data for any reason other than assessing risk is not recommended. The data presents the estimated number of buildings, building area, and rebuilding value at a 15-arcsecond grid resolution (approximately 500 meters at the equator). This data set is in point shapefile format where the points represent the centroids of the 15-arcsecond grid. The results were created through a process of spreading the number of buildings to the 15-arcsecond level by a statistical assessment of moderate resolution EO data, which is described in more detail in the dasymetric mapping lineage processing step. The estimated building count at any given area is a result of statistical processes and should not be mistaken as a building count. The structural classes of buildings used for risk assessment are estimated given the building wall, floor, and roof material classes surveyed through 2002 Population and Housing Census - Volume 1. Analytical report. Additionally, the data is provided in Open Exposure Data (OED) import format, as a pair of CSV files. One CSV file contains the location details, and the other is an "account" file that is filled with default information to satisfy OED format requirements. The OED input files are set to use "All perils" (i.e. "AA1"). All required OED account-related fields are populated with "1" by default (such as PortNumber, AccNumber, PolNumber). If you find this data useful please provide feedback via our questionnaire; it should take only a few minutes: https://forms.gle/DQjhE89CRegNKB3X8 Please see the METEOR project page for information about the METEOR Project: http://meteor-project.org/ Please see the METEOR map portal for interactive maps: https://maps.meteor-project.org/ For more information about the Open Exposure Data (OED) standard, please see https://github.com/OasisLMF/OpenDataStandards
  • 700+ Downloads
    Updated 2 April 2021 | Dataset date: March 03, 2021-March 03, 2021
    This dataset updates: Every year
    This dataset contains the people in need by department, commune and sector. The dataset is produced by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners.
  • 100+ Downloads
    Updated 29 March 2021 | Dataset date: May 06, 2020-May 23, 2021
    This dataset updates: Every day
    This dataset contains the number of suspected cases, confirmed cases, and deaths by Département due to the Coronavirus pandemic in Haiti. Released by the Ministry of Public Health and Population of Haiti.
  • 12000+ Downloads
    Updated 25 March 2021 | Dataset date: August 27, 2020-August 27, 2020
    This dataset updates: As needed
    We use an anonymized snapshot of all active Facebook users and their friendship networks to measure the intensity of connectedness between locations. The Social Connectedness Index (SCI) is a measure of the social connectedness between different geographies. Specifically, it measures the relative probability that two individuals across two locations are friends with each other on Facebook. Details on the underlying data and the construction of the index are provided in the “Facebook Social Connectedness Index - Data Notes.pdf” file. Please also see https://dataforgood.fb.com/ as well as the associated research paper “Social Connectedness: Measurement, Determinants and Effects,” published in the Journal of Economic Perspectives (https://www.aeaweb.org/articles?id=10.1257/jep.32.3.259).
  • 400+ Downloads
    Updated 18 March 2021 | Dataset date: January 30, 2019-January 30, 2019
    This dataset updates: Every year
    Haiti humanitarian needs overview (HNO) numbers , Jan-Dec 2018. The HNO figures are compiled by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners.
  • 100+ Downloads
    Updated Live | Dataset date: February 08, 2021-September 18, 2021
    This dataset updates: Live
    Number of children 6-59 months admitted for TREATMENT OF SEVERE ACUTE MALNUTRITION (SAM) by country
  • 100+ Downloads
    Updated 4 March 2021 | Dataset date: November 20, 2020-November 20, 2020
    This dataset updates: As needed
    Data on access constraints, aid workers security, % of affected CERF and CBPF projects combined with the status of Polio vaccination in the HRP countries.
  • 1900+ Downloads
    Updated 26 February 2021 | Dataset date: September 21, 2020-September 21, 2020
    This dataset updates: Every year
    This data contains aggregated weighted statistics at the regional level by gender for the Survey on Gender Equality At Home fielded in July 2020. Facebook’s Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. If you're interested in becoming a Survey on Gender Equality research partner, please email gendersurvey@fb.com.
  • 400+ Downloads
    Updated 22 January 2021 | Dataset date: July 31, 2021-July 31, 2021
    This dataset updates: Every year
    This dataset shows the number of people in need(PiN), funds required and funds received by country and over the years, from 2010 to 2021.
  • 50+ Downloads
    Updated 24 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674
  • 100+ Downloads
    Updated 24 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App. The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively): - Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019) -Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019). -Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets. -Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020. -Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019). Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645
  • 100+ Downloads
    Updated 5 November 2020 | Dataset date: October 27, 2016-October 27, 2016
    This dataset updates: As needed
    This is an extraction of the WFP global obstacles dataset (https://data.humdata.org/dataset/global-obstacles) for Haiti showing obstacles after Hurricane Matthew. The dataset will refresh by itself as data is edited on our side, so it means it will always contain the most up-to-date data we have on the Logistics Cluster/WFP side, even though the date on hdx is showing an earlier date. Sources of information come mainly from Social Media compiled by local Haitian Bloggers: https://umap.openstreetmap.fr/fr/map/cyclone-matthew-haiti_105242#9/18.8166/-72.5290 The dataset is the one used to produce the Logistics Cluster Access Constraints map: http://www.logcluster.org/sector/hurrimat16
  • 40+ Downloads
    Updated Live | Dataset date: September 30, 2020-September 30, 2020
    This dataset updates: Live
    None