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
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
14 December 2021
| Dataset date: October 07, 2021-October 15, 2022
This table contains subnational multidimensional poverty data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI 2021 methodology is detailed in Alkire, Kanagaratnam & Suppa (2021).
| Dataset date: January 01, 2019-August 12, 2022
Live list of active aid activities for Haiti shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from http://www.d-portal.org
19 November 2021
| Dataset date: July 30, 2021-July 30, 2021
Data showing the mapping of humanitarian and development actors with a physical presence in Haiti. It shows the location of their offices in the different communes. The information was collected by OCHA Haiti via an online survey.
22 September 2021
| Dataset date: September 22, 2021-August 12, 2022
Prepared by MapAction from OpenStreetMap, September 2021.
Contains 4880 points P-coded as ADM4.
Compatible administrative level 0-3 polygon boundaries are available at Haiti - Subnational Administrative Boundaries.
22 August 2021
| Dataset date: January 01, 1990-August 15, 2021
This no longer updated dataset contains Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
18 August 2021
| Dataset date: December 05, 2018-August 12, 2022
Administrative boundary, administrative level 0 (national), level 1 (department), level 2 (commune), and level 3 (section communale).
Notice! The boundaries and names shown and the designations used on these shapefiles do not imply official endorsement or acceptance by the United Nations.
Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
The 'AdminLevel' field categorizes the lines AdminLevel 0: coastlines AdminLevel 1: lines between administrative level 1 polygons AdminLevel 2: lines between administrative level 2 polygons within the same administrative level 1 polygon AdminLevel 3: lines between administrative level 3 polygons within the same administrative level 2 polygon AdminLevel 99: international borders
These layers are suitable for database or GIS linkage to the Haiti - Subnational Population Statistics tables.
18 August 2021
| Dataset date: August 17, 2021-August 12, 2022
Haiti administrative level 3 sex and age disaggregated projected population statistics. See caveats.
Reference year 2020.
These tables are suitable for database or GIS linkage to the Haiti - Subnational Administrative Boundaries layers.
4 August 2021
| Dataset date: January 01, 1970-December 31, 2019
Education indicators for Haiti.
Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: National Monitoring (made 2021 March), SDG 4 Global and Thematic (made 2021 March), Demographic and Socio-economic (made 2021 March)
26 July 2021
| Dataset date: March 01, 2021-August 12, 2022
This dataset is produced by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners in Haiti. It contains the estimation of people aggregated per geographic locations, sex and age who have been targeted for urgent humanitarian response in Haiti
4 May 2021
| Dataset date: January 01, 1990-December 31, 2030
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'.
4 May 2021
| Dataset date: November 02, 2012-November 02, 2012
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-...
15 April 2021
| Dataset date: March 01, 2020-December 31, 2020
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.
6 April 2021
| Dataset date: April 01, 2020-December 12, 2020
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.
2 April 2021
| Dataset date: May 05, 2020-May 05, 2020
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,
If you find this data useful please provide feedback via our questionnaire; it should take only a few minutes:
Please see the METEOR project page for information about the METEOR Project:
Please see the METEOR map portal for interactive maps:
For more information about the Open Exposure Data (OED) standard, please see
24 November 2020
| Dataset date: January 01, 2000-December 31, 2020
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.
Data for earlier dates is available directly from WorldPop.
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