Data Grid Completeness
16/21 Core Data 17 Datasets 11 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
2 Datasets
Internally-Displaced Persons
Humanitarian Needs
Coordination & Context
4 Datasets
3w - Who is doing what where
International Aid Transparency Initiative
Affected Areas
Conflict Events
Humanitarian Access
Transportation Status
Food Security & Nutrition
3 Datasets
Food security
Integrated Food Security Phase Classification (IPC)
Food Prices
WFP - World Food Programme
Geography & Infrastructure
3 Datasets
Administrative Divisions
Populated Places
Roads
Airports
Health & Education
3 Datasets
Health Facilities
Global Healthsites Mapping Project
Education Facilities
Population & Socio-economy
2 Datasets
Poverty Rate
Oxford Poverty & Human Development Initiative
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  • Updated 26 May 2021 | Dataset date: July 15, 2020-September 29, 2021
    This dataset updates: Never
    Assessment of the impact of the COVID-19 pandemic on food security, livelihoods and local markets for refugees in urban areas.
  • 8000+ Downloads
    Updated 6 May 2021 | Dataset date: April 01, 2021-November 29, 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/
  • 200+ 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'.
  • 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.
  • Updated 11 April 2021 | Dataset date: January 01, 2018-December 31, 2018
    This dataset updates: Never
    The UNHCR Livelihoods Monitoring Framework takes a program-based approach to monitoring, with the aim of tracking both outputs and the impact of UNHCR dollars spent on programming (either via partners or through direct implementation). The process for developing the indicators began in 2015 with a review of existing tools and approaches. Consultations were held with governments, the private sector, field-based staff and civil society partners to devise a set of common, standardized measures rooted in global good practices. Since 2017, a data collection (survey) has been rolled out globally, and the participating operations conducted a household surveys to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline and endline data from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact. More info is available on the official website: https://lis.unhcr.org
  • Updated 11 April 2021 | Dataset date: January 01, 2019-December 31, 2019
    This dataset updates: Never
    The UNHCR Livelihoods Monitoring Framework takes a program-based approach to monitoring, with the aim of tracking both outputs and the impact of UNHCR dollars spent on programming (either via partners or through direct implementation). The process for developing the indicators began in 2015 with a review of existing tools and approaches. Consultations were held with governments, the private sector, field-based staff and civil society partners to devise a set of common, standardized measures rooted in global good practices. Since 2017, a data collection (survey) has been rolled out globally, and the participating operations conducted a household surveys to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline and endline data from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact. More info is available on the official website: https://lis.unhcr.org
  • 100+ Downloads
    Updated 6 March 2021 | Dataset date: January 01, 2020-December 31, 2020
    This dataset updates: Never
    UNICEF Eastern and Southern Africa Risks and Hazards- situation and response
  • 100+ Downloads
    Updated Live | Dataset date: February 08, 2021-November 29, 2021
    This dataset updates: Live
    Number of children 6-59 months admitted for TREATMENT OF SEVERE ACUTE MALNUTRITION (SAM) by country
  • 200+ 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.
  • 500+ Downloads
    Updated 22 February 2021 | Dataset date: December 01, 2020-February 19, 2021
    This dataset updates: As needed
    The dataset contains 93 harmonized indicators on 14 topics (demographic, food security, education, labor, health..) on households and individuals in 44 countries across all developing regions.
  • Updated 7 February 2021 | Dataset date: May 01, 2019-May 31, 2019
    This dataset updates: Never
    Tropical Cyclone Idai made a landfall on 14th March, 2019 which immensely affected Mozambique, Malawi and Zimbabwe. The Eastern Provinces of Zimbabwe which experienced torrential rainfall caused extensive destruction of properties and infrastructures as well as loss of lives. High winds combined with heavy rainfall affected about 90,000 people from districts of Chimanimani, Chipinge, Nyanga, Buhera, Mutare Rural, Masvingo, Makoni, Gutu and Bikita which caused riverine and flash flooding as well as landslides which caused significant loss of life, injury and displacement. Significant damages were recorded such as impassable roads, bridge, water network systems, houses, power and communication network among others causing displacement, lack of basic needs and loss of civil documentation. Many people were displaced and temporarily sheltered in schools, churches, hotels among others. According to the government reports at least 299 deaths and 186 injuries were recorded, and 329 people were missing as of 3 April. Women and children were among the vulnerable groups at risk that needed relief and recovery support. UNHCR joined the UN system response that activated its internal level 3 emergency so as to support the delivery of its commitments under the IASC Approach while leading the Protection Cluster.In Zimbabwe, the rapid inter-agency assessment was conducted in Chipinge and Chimanimani, the most affected districts of Manicaland province indicated that 270,000 people estimated were affected. Multiple assessments were conducted by humanitarian partners covering all the affected areas and identifying the needs. In Tongogara Refugee Camp about 1060 shelters and 618 latrines were partially or totally damaged affecting 5,300 refugees and asylum seekers. Thus the urgent need to respond to WASH, Public Health, Shelter, and Protection among other needs of the people affected by Cylone Idai in Zimbabwe.
  • Updated 7 February 2021 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Never
    Since 2014, UNHCR has undertaken a comprehensive revision of the framework for monitoring UNHCR Livelihoods and Economic Inclusion programs. Since 2017, mobile data collection (survey) tools have been rolled out globally, including in Zimbabwe. The participating operations conducted a household survey to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline (103 observations) and endline data (89 observations) from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact.
  • Updated 7 February 2021 | Dataset date: October 23, 2017-October 27, 2017
    This dataset updates: Never
    This assessment was carried out in Zimbabwe's Tongogara Refugee Camp. Its aim was to help UNHCR better understand refugees' and asylum seekers' living conditions and needs, which in turn will inform priority setting, programming and advocacy. The assessment was underpinned by the objectives of the "Graduation Approach" which targets support to the ultra-poor amongst the refugee population. A quantitative survey was conducted among 386 households during October 2017.
  • 30+ Downloads
    Updated Live | Dataset date: November 16, 2015-November 29, 2021
    This dataset updates: Live
    List of aid activities by InterAction members in Zimbabwe. Source: http://ngoaidmap.org/location/gn_878675
  • 9800+ Downloads
    Updated 26 November 2020 | Dataset date: August 31, 2018-November 29, 2021
    This dataset updates: Every year
    Zimbabwe administrative level 0 (country), 1 (province), 2 (district) and 3 (ward) boundary polygon, line, and point shapefiles, geodatabase, and live services, and gazetteer. Please note that administrative level 3 (ward) features are identified numerically. Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID. These shapefiles are suitable for linkage by P-code to the Zimbabwe - Subnational Population Statistics CSV population statistics tables.
  • 40+ 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. 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
  • 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. 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/WP00645
  • 100+ Downloads
    Updated 30 October 2020 | Dataset date: December 31, 2019-December 31, 2019
    This dataset updates: As needed
    UNICEF Eastern and Southern Africa Risks and Hazards- situation
  • 200+ Downloads
    Updated 30 October 2020 | Dataset date: October 31, 2020-October 31, 2020
    This dataset updates: Every six months
    Eastern and Southern Africa Risk Analysis based on Inform, FEWSNET, OCHA, UNICEF and others
  • 90+ Downloads
    Updated 30 October 2020 | Dataset date: October 01, 2019-October 01, 2019
    This dataset updates: As needed
    Post cyclone, drought, disease outbreak for Idai countries- Mozambique, Zimbabwe, Malawi
  • 100+ Downloads
    Updated 30 October 2020 | Dataset date: December 31, 2019-December 31, 2019
    This dataset updates: As needed
    The Database and dashboard covers the regional humanitarian situation including targets, results and funding all as of December 2019 for entire Eastern and Southern Africa. Annual 2019 Database.
  • 100+ Downloads
    Updated 14 September 2020 | Dataset date: July 08, 2020-July 10, 2021
    This dataset updates: Every year
    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 2020 methodology is detailed in Alkire, Kanagaratnam & Suppa (2020).
  • 1500+ Downloads
    Updated 9 September 2020 | Dataset date: January 01, 2015-December 31, 2017
    This dataset updates: As needed
    This dataset contains agency- and publicly-reported data on sexual violence and abuse against aid workers between January 2015 and December 2017.
  • 500+ Downloads
    Updated 9 September 2020 | Dataset date: January 01, 2018-December 31, 2018
    This dataset updates: As needed
    This dataset is compiled from two categories of sources: (a) verified security events submitted to Insecurity Insight by 30 Aid in Danger partner agencies; and (b) publicly reported events identified by Insecurity Insight and published in the Aid in Danger Monthly News Brief. Events are categorised by date, country, type of organisation affected and event category, based on standard definitions.
  • 800+ Downloads
    Updated 9 September 2020 | Dataset date: January 01, 2018-December 31, 2018
    This dataset updates: As needed
    This dataset contains events in which an aid worker was involved in a road safety accident (RSA). Categorized by country.