Democratic Republic of the Congo

Data Grid Completeness
73% 
14/19 Core Data 19 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
Affected People
4 Datasets
100% 
Internally-Displaced Persons
Democratic Republic of the Congo: Displacement - [Déplacé] - Site Assessment [OCHA]
OCHA Democratic Republic of the Congo (DRC)
Refugees & Persons of Concern
Democratic Republic of the Congo - Data on forcibly displaced populations and stateless persons
UNHCR - The UN Refugee Agency
Returnees
Democratic Republic of the Congo: Displacement - [returnees] - Site Assessment [OCHA]
OCHA Democratic Republic of the Congo (DRC)
Humanitarian Needs
Democratic Republic of the Congo: Humanitarian Needs Overview
OCHA Democratic Republic of the Congo (DRC)
Coordination & Context
4 Datasets
100% 
3w - Who is doing what where
République Démocratique du Congo : Présence Opérationnelle
OCHA Democratic Republic of the Congo (DRC)
Funding
Congo, The Democratic Republic of the - Requirements and Funding Data
OCHA Financial Tracking System (FTS)
Conflict Events
Democratic Republic of Congo - Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Humanitarian Access
Not available
Climate Impact
Democratic Republic of the Congo: Natural disaster Impact
OCHA Democratic Republic of the Congo (DRC)
Food Security & Nutrition
3 Datasets
66%  33% 
Food security
Democratic Republic of the Congo: Acute Food Insecurity Country Data
Integrated Food Security Phase Classification (IPC)
Acute Malnutrition
Démocratique République du Congo : Prévalence de la malnutrition
UNICEF Democratic Republic of Congo
Food Prices
Democratic Republic of the Congo - Food Prices
WFP - World Food Programme
Geography & Infrastructure
4 Datasets
50%  50% 
Administrative Divisions
Democratic Republic of the Congo - Subnational Administrative Boundaries
OCHA Democratic Republic of the Congo (DRC)
Populated Places
West and Central Africa - Administrative boundaries levels 0 - 2 and Settlements
OCHA West and Central Africa (ROWCA)
Roads
Democratic Republic of the Congo Roads (OpenStreetMap Export)
Humanitarian OpenStreetMap Team (HOT)
Airports
Democratic Republic of the Congo Airports (OpenStreetMap Export)
Humanitarian OpenStreetMap Team (HOT)
Health & Education
2 Datasets
100% 
Health Facilities
Health Facilities in Sub-Saharan Africa
HDX
Education Facilities
Democratic Republic of the Congo Education Facilities (OpenStreetMap Export)
Humanitarian OpenStreetMap Team (HOT)
Population & Socio-economy
2 Datasets
100% 
Baseline Population
Democratic Republic of the Congo - Subnational Population Statistics
OCHA Democratic Republic of the Congo (DRC)
Poverty Rate
Democratic Republic of the Congo: subnational poverty trends
Oxford Poverty & Human Development Initiative
Data Datasets [297] | Archived Datasets[87] [?]
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  • Democratic Republic of the Congo - Joint Assessment of Refugees from from...
    UNHCR - The UN Refugee Agency
    Time Period of the Dataset [?]: August 17, 2021-September 17, 2021 ... More
    Modified [?]: 22 August 2022
    Dataset Added on HDX [?]: 14 November 2022
    Less
    This dataset updates: Never
    Between August and September 2021, UNHCR and WFP undertook an assessment of refugees from the Central African Republic in North and South Ubangui provinces of the Democratic Republic of the Congo (DRC). The main objective of the of the assessment of needs and livelihoods is to understand the basic needs and vulnerabilities, particularly related to livelihoods, of refugees. The assessment was a joint effort between the UNHCR and WFP country offices and the UNHCR-WFP Joint Targetting Hub. Data collection took place from August 17 to September 17, 2021 in the four refugee camps of Bili and Inke (North Ubangi) and Boyabu and Mole (South Ubangi). 1,450 households were selected using stratified random sampling, with 1,328 were retained. See more details in the report. This dataset represents an anonymous version of the original dataset.
  • Democratic Republic of the Congo - Joint Assessment of Refugees from South...
    UNHCR - The UN Refugee Agency
    Time Period of the Dataset [?]: February 14, 2021-March 19, 2021 ... More
    Modified [?]: 22 August 2022
    Dataset Added on HDX [?]: 14 November 2022
    Less
    This dataset updates: Never
    Between February and March 2021, UNHCR and WFP undertook an assessment of refugees from South Sudan in the sites of Biringi (Ituri province), Bele and Meri (Haut Uélé province) in the Democratic Republic of the Congo (DRC). The objective of the assessment was to update the basic knowledge on the humanitarian needs of the whole South Sudanese refugee population in these sites to inform programmatic decisions and assess the relevance of a harmonized humanitarian targetting strategy based on level of vulnerability. The assessment was carried out jointly by UNHCR and WFP. All refugee households in all sites were interviewed, consisting of 8,630 households. This dataset represents an anonymous version of the original dataset. A 20% random sample of the original dataset was drawn as part of the anonymization. The sample was stratified by site (Mele, Beri and Biringi). The variable survey_weight provide the final weights.
  • Democratic Republic of the Congo - Joint Assessment of Refugees from Burundi...
    UNHCR - The UN Refugee Agency
    Time Period of the Dataset [?]: January 01, 2021-January 31, 2021 ... More
    Modified [?]: 22 August 2022
    Dataset Added on HDX [?]: 14 November 2022
    Less
    This dataset updates: Never
    In January 2021, the United Nations High Commissioner for Refugees (UNHCR) and the World Food Programme (WFP) undertook an assessment of refugees from Burundi in the Lusenda and Mulongwe refugee camps in South Kivu, Democratic Republic of the Congo (DRC). The objective of the assessment was to assess the relevance of UNHCR and WFP's targeting in the context of Burundian refugees and possibly develop a targeting strategy harmonized as much as possible with other refugee populations in DRC. A secondary objective was to introduce barcodes linked to unique identifiers used in registration. This vulnerability assessment was conducted through an exhaustive inventory of all refugee households living in the Lusenda and Mulongwe camps (South Kivu) as well as those living outside the camps and who went to the interview locations in the camps. The survey targeted Burundian refugee households assisted by WFP and UNHCR. The data collected during the survey are quantitative and were supplemented by qualitative data collected in February 2021 in the camps of Lusenda and Mulongwe through four focus group discussions per camp for a total of eight focus groups. All refugee households in Lusenda and Mulongwe camps as well as those living outside the camp, were interviewed with a core set of questions (see variable TypeEnquete, response Ciblage). In addition, 7% of households, randomly selected, participated in a more detailed interview (see variable TypeEnquete, response Exhaustive). A total of 7,873 households were selected. This dataset represents an anonymous version of the original dataset. A sample of the original dataset was drawn as part of the anonymization. The sample was stratified by camp (Lusenda or Muolongwe) and the type of survey (Ciblage or Exhaustive). All respondents that were part of the Exhaustive survey were preserved, while a random sample of the respondents that were part of the Ciblage survey was taken. The variable strata defines which records correspond with which group, and survey_weight provide the final weights.
  • Democratic Republic of the Congo Subnational Population and Housing Data...
    U.S. Census Bureau
    100+ Downloads
    Time Period of the Dataset [?]: November 16, 2021-April 18, 2024 ... More
    Modified [?]: 27 July 2022
    Dataset Added on HDX [?]: 27 July 2022
    Less
    This dataset updates: As needed
    This dataset is part of the data series [?]: US Census Bureau - Subnational Population and Housing Data Tables
    The geodatabase contains boundaries for the national and first- and second- order administrative divisions, aligned to the Large Scale International Boundaries dataset from the U.S. Department of State. The feature classes are suitable for linking to the attribute data provided. The tabular data contain total population for 2019 (population estimates), household characteristics, IDP movements, people in need, and tribe and religion.
  • Kinshasa Scholls in the CP3 health areas
    American Red Cross
    20+ Downloads
    Time Period of the Dataset [?]: July 24, 2022-April 18, 2024 ... More
    Modified [?]: 25 July 2022
    Dataset Added on HDX [?]: 25 July 2022
    Less
    This dataset updates: Every six months
    This dataset shows the schools facilities in the target CP3 program health areas of the DRC Red Cross. CP3 program is deployed in 4 health zones find in 2 provinces, Kinshasa and Kongo Central province.
  • Priorisation Juin 2022- Novembre 2022
    UNICEF Democratic Republic of Congo
    300+ Downloads
    Time Period of the Dataset [?]: June 21, 2022-November 21, 2022 ... More
    Modified [?]: 20 July 2022
    Dataset Added on HDX [?]: 14 April 2021
    Less
    This dataset updates: Every six months
    Priorisation du cluster nutrition qui se base sur plusieurs facteurs aggravants pour permettre de mettre en avant les zones de santé les plus sensibles à la malnutrition alors que les données provenant des enquêtes nutritionnelles sont vieillissantes pour certaine Zone de santé.
  • GRID3 DRC Settlements - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and...
    GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development)
    70+ Downloads
    Time Period of the Dataset [?]: June 29, 2022-April 18, 2024 ... More
    Modified [?]: 29 June 2022
    Dataset Added on HDX [?]: 29 June 2022
    Less
    This dataset updates: As needed
    The "GRID3 DRC Settlements - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of settlement points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: settlement point data and a table with the field descriptions for the layer. The data are available for download in Esri file geodatabase format packaged in zip files. File name: GRID3_DRC_settlements_names_V01.gdb The following layers are included in the gdb: codebook__settlements_names GRID3_DRC_settlements_names_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Settlements - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/pvdz-4x94. Accessed DAY MONTH YEAR.
  • GRID3 DRC Schools - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and...
    GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development)
    60+ Downloads
    Time Period of the Dataset [?]: June 29, 2022-April 18, 2024 ... More
    Modified [?]: 29 June 2022
    Dataset Added on HDX [?]: 29 June 2022
    Less
    This dataset updates: As needed
    The "GRID3 DRC Schools - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01" dataset consists of school points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work. the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support of data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS and Novel-T. GRID3 Mapping for Health in DRC is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: schools point data and a table with the field descriptions for the layer. File name: GRID3_DRC_schools_V01.gdb The following layers are included in the gdb: codebook_schools GRID3_DRC_schools_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Schools - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces- Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/a3d6-m921. Accessed DAY MONTH YEAR
  • GRID3 DRC Religious Centres - Haut-Katanga, Kasaï, Kasaï-Oriental,...
    GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development)
    30+ Downloads
    Time Period of the Dataset [?]: June 29, 2022-April 18, 2024 ... More
    Modified [?]: 29 June 2022
    Dataset Added on HDX [?]: 29 June 2022
    Less
    This dataset updates: As needed
    The "GRID3 DRC Religious Centres - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01" dataset consists of religious centre points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). This dataset is one of five (5) datasets (along with the Settlements, Health Facilities, Health Catchment Area Boundaries, and Schools datasets)included in this Version 01 release. To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support of data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one geospatial layer: religious centre point data and a table with the field descriptions for the layer. File name: GRID3_DRC_religious_centers_V01.gdb The following layers are included in the gdb: codebook__religious_centers GRID3_DRC_religious_center_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Religious Centres - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces - Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/z4vq-h095. Accessed DAY MONTH YEAR
  • GRID3 DRC Health Facilities - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa,...
    GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development)
    70+ Downloads
    Time Period of the Dataset [?]: June 29, 2022-April 18, 2024 ... More
    Modified [?]: 29 June 2022
    Dataset Added on HDX [?]: 29 June 2022
    Less
    This dataset updates: As needed
    The "GRID3 DRC Health Facilities - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of health facility points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of four layers: health facility point data and a table with the field descriptions for the layer. The data are available for download in Esri file geodatabase format packaged in zip files. File name: GRID3_DRC_health_facilities_V01.gdb The following layers are included in the gdb: codebook_health_facilities GRID3_DRC_bcz_5_prov_V01 (The “BCZ” refers to the Bureau central de la Zone de Santé (Central Office of the Health Zone), which constitutes the framework structure for the organization and operation of the health zone. It is located either within the Hôpital Général de Référence (General Reference Hospital), or outside it but inside the health zone. The BCZ is the operational level of the DRC Health System and level of implementation of strategies from the Ministry of Health.) GRID3_DRC_health_facilities_5_prov_V01 (Government, NGO, or private health facilities that offer vaccination or public health services.) GRID3_DRC_KN_secondary_health_facilities_1_prov_V01 (The main goal of data collection conducted for the EPI was to identify health facilities (public and private) that provided services for public health and routine immunisations. However, at the demand of the DSNIS, all the facilities, public or private, were also geo-referenced. The healthcare services density is such in Kinshasa (with various facilities for private services, specialists, and faith healers opening and closing quite frequently) that GRID3 created a secondary health facilities layer to be able to differentiate the main public structures from others.) Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Health Facilities - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/0bvp-kp75. Accessed DAY MONTH YEAR.
  • GRID3 DRC Health Zone and Health Area Boundaries - Haut-Katanga, Kasaï,...
    GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development)
    70+ Downloads
    Time Period of the Dataset [?]: June 29, 2022-April 18, 2024 ... More
    Modified [?]: 29 June 2022
    Dataset Added on HDX [?]: 29 June 2022
    Less
    This dataset updates: As needed
    The "GRID3 DRC Health Zone and Health Area Boundaries - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of health area boundary polygons with names and attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative delivered in partnership with Flowminder and CIESIN (Columbia University), in collaboration with WorldPop at the University of Southampton, the Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: health catchment area polygon data and a table with the field descriptions for the layers. Filename: GRID3_DRC_health_catchment_area_boundaries_V01.gdb The following layers are included in the gdb: GRID3_DRC_health_catchment_zone_boundaries_5_prov_V01 GRID3_DRC_health_catchment_area_boundaries_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Health Zone and Health Area Boundaries - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/hzrd-yq54. Accessed DAY MONTH YEAR.
  • Climate Change Opinion Survey
    Data for Good at Meta
    2600+ Downloads
    Time Period of the Dataset [?]: February 17, 2021-March 03, 2021 ... More
    Modified [?]: 28 June 2022
    Dataset Added on HDX [?]: 24 June 2021
    Less
    This dataset updates: Every year
    In partnership with Yale, Meta launched a climate change opinion survey that explores public climate change knowledge, attitudes, policy preferences, and behaviors. The 2022 survey includes respondents from nearly 200 countries and territories. We are sharing country level data from this survey, providing policymakers, research institutions, and nonprofits with an international view of public climate change opinion. For more information please see https://dataforgood.facebook.com/dfg/tools/climate-change-opinion-survey If you're interested in becoming a research partner and accessing record level data, please email dataforgood@fb.com.
  • Movement Range Maps
    Data for Good at Meta
    54000+ Downloads
    Time Period of the Dataset [?]: March 01, 2020-May 22, 2022 ... More
    Modified [?]: 24 May 2022
    Confirmed [?]: 31 May 2022
    Dataset Added on HDX [?]: 26 May 2020
    Less
    This dataset updates: As needed
    NOTE: We plan to no longer update this dataset after May 22 2022. These data sets are intended to inform researchers and public health experts about how populations are responding to physical distancing measures. In particular, there are two metrics, Change in Movement and Stay Put, that provide a slightly different perspective on movement trends. Change in Movement looks at how much people are moving around and compares it with a baseline period that predates most social distancing measures, while Stay Put looks at the fraction of the population that appear to stay within a small area during an entire day. Full details, including the privacy protections in this data, are available here: https://research.fb.com/blog/2020/06/protecting-privacy-in-facebook-mobility-data-during-the-covid-19-response/
  • DRC Health Zone and Health Area boundaries
    American Red Cross
    2600+ Downloads
    Time Period of the Dataset [?]: July 11, 2020-July 11, 2020 ... More
    Modified [?]: 20 May 2022
    Dataset Added on HDX [?]: 24 January 2019
    Less
    This dataset updates: As needed
    This dataset is showing the health boundaries data of the Democratic Republic of Congo.
  • DRC: Ports and Airports of Kinshasa
    American Red Cross
    40+ Downloads
    Time Period of the Dataset [?]: May 09, 2022-April 18, 2024 ... More
    Modified [?]: 9 May 2022
    Dataset Added on HDX [?]: 9 May 2022
    Less
    This dataset updates: Every six months
    This database shows sea and air entry points of Kinshasa city. This data was updated by Maluku commune Red Cross volunteers during the training on the usage of OSMTracker, an opensource mobile phone GPS application for the CP3/IFRC program.
  • GRID3 Democratic Republic of the Congo Settlement Extents, Version 01.02
    GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development)
    COD 100+ Downloads
    Time Period of the Dataset [?]: April 04, 2022-April 18, 2024 ... More
    Modified [?]: 4 April 2022
    Dataset Added on HDX [?]: 4 April 2022
    Less
    This dataset updates: As needed
    This dataset is part of the data series [?]: GRID3 - Settlement Extents
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This data product contains all information contained in the previous “GRID3 Democratic Republic of the Congo Settlement Extents, Version 01.01” product, with updates. Updates in this version include: The addition of the WorldPop GRID3 Gridded Population Estimates for Age and Sex in Kinshasa, Kongo-Central, Kwango, Kwilu, and Mai-Ndombe provinces . This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2022. GRID3 Democratic Republic of the Congo Settlement Extents, Version 01.02. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/hbr4-ve53 . Accessed DAY MONTH YEAR
  • RDC - Statistiques des Populations par Zones de Santé
    OCHA Democratic Republic of the Congo (DRC)
    COD 7100+ Downloads
    Time Period of the Dataset [?]: September 10, 2019-April 18, 2024 ... More
    Modified [?]: 21 February 2022
    Dataset Added on HDX [?]: 13 April 2017
    Less
    This dataset updates: As needed
    Statistiques des populations : population désagrégée par âge et sexe pour toutes les zones de santé du pays.
  • Modelled gridded population estimates for the Haut-Katanga, Haut-Lomami,...
    GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development)
    100+ Downloads
    Time Period of the Dataset [?]: July 21, 2021-April 18, 2024 ... More
    Modified [?]: 17 February 2022
    Dataset Added on HDX [?]: 13 January 2022
    Less
    This dataset updates: As needed
    This dataset is part of the data series [?]: GRID3 - Gridded Population Estimated
    These data consist of modelled gridded population estimates produced at a spatial resolution of approximately 100m across the Haut-Katanga, Haut-Lomami, Ituri, Kasaï, Kasaï-Oriental, Lomami and Sud-Kivu provinces in the Democratic Republic of the Congo (DRC). The estimates comprise total population counts created using a Bayesian statistical model and post-hoc breakdowns in 40 age and sex groups. The main input data were derived from a dedicated microcensus survey carried out in the targeted provinces throughout March and April 2021. The microcensus was led by the Flowminder Foundation, the École de Santé Publique de Kinshasa, the WorldPop Research Group at the University of Southampton and the Bureau Central du Recensement, which is part of the Institut National de la Statistique of the DRC. Other essential input data include metrics derived from building footprints, which were automatically delineated by Ecopia.AI in 2021 using satellite imagery collected by Maxar Technologies between 2010 and 2021. The modelled population estimates represent the period of the microcensus but their consistency may be impacted by the accuracy of the building footprints, particularly in the areas where the satellite imagery used for automatic delineation was outdated. These data were produced by the WorldPop Research Group at the University of Southampton as part of the GRID3 Mapping for Health Project. This project was delivered under the leadership of the Ministry of Public Health, Hygiene and Prevention of the DRC and funded by Gavi, the Vaccine Alliance (RM 867204 20A2). The project was led by the Flowminder Foundation and the Center for International Earth Science Information Network (CIESIN) at Columbia University, in collaboration with the WorldPop Research Group at the University of Southampton and national partners including, but not limited to, the École de Santé Publique de Kinshasa and both the Bureau Central du Recensement and the Institut National de la Statistique. This work was a continuation of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) programme funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom’s Foreign, Commonwealth & Development Office (INV 009579, formerly OPP 1182425). The study was approved by the Faculty Ethics Committee of the University of Southampton (ERGO II 62716). The production of these data was led by Gianluca Boo (WorldPop](https://www.worldpop.org/) ) with support from Roland Hosner (Flowminder Foundation), Pierre Z Akilimali (École de Santé Publique de Kinshasa), Edith Darin (WorldPop), Heather R Chamberlain (WorldPop), Warren C Jochem (WorldPop), Patricia Jones (WorldPop), Roger Shulungu Runika (Institut National de la Statistique), Henri Marie Kazadi Mutombo (Bureau Central du Recensement), Attila N Lazar (WorldPop) and Andrew J Tatem (WorldPop). The authors acknowledge the support of their respective institutions in the completion of this work. Recommended citation: G Boo, R Hosner, PZ Akilimali, E Darin, HR Chamberlain, WC Jochem, P Jones, R Shulungu Runika, HM Kazadi Mutombo, AN Lazar and AJ Tatem. 2021. Modelled gridded population estimates for the HautKatanga, Haut-Lomami, Ituri, Kasaï, Kasaï-Oriental, Lomami and Sud-Kivu provinces in the Democratic Republic of the Congo (2021), version 3.0. WorldPop, University of Southampton, Flowminder Foundation, École de Santé Publique de Kinshasa, Bureau Central du Recensement and Institut National de la Statistique. doi:10.5258/SOTON/WP00720
  • DPS Nord-Kivu (RDC)
    OpenStreetMap RDC
    1100+ Downloads
    Time Period of the Dataset [?]: October 18, 2021-December 05, 2021 ... More
    Modified [?]: 7 January 2022
    Dataset Added on HDX [?]: 19 October 2021
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    This dataset updates: Every three months
    This dataset is part of the data series [?]: OSM - DRC Health Zones
    Données de base ou d'intérêt pour le secteur de la santé, extraites de la base de données OpenStreetMap, pour la province du Nord-Kivu. Ce dossier reprend actuellement des données publiées dans un contexte de formation et révision.
  • Democratic Republic of the Congo - Subnational Administrative Boundaries
    geoBoundaries
    300+ Downloads
    Time Period of the Dataset [?]: January 01, 2017-December 31, 2019 ... More
    Modified [?]: 6 January 2022
    Dataset Added on HDX [?]: 6 January 2022
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    This dataset updates: Live
    This dataset is part of the data series [?]: geoBoundaries - Subnational Administrative Boundaries
    This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2. Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database www.geoboundaries.org is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.
  • West and Central Africa - Administrative boundaries levels 0 - 2 and Settlements
    OCHA West and Central Africa (ROWCA)
    9700+ Downloads
    Time Period of the Dataset [?]: July 01, 2021-July 01, 2021 ... More
    Modified [?]: 31 December 2021
    Confirmed [?]: 5 January 2024
    Dataset Added on HDX [?]: 26 September 2017
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    This dataset updates: Every year
    West and Central Africa Administrative boundaries, administrative level 0 to 2. Notice: The boundaries and names shown and the designations used on these shapefiles do not imply official endorsement or acceptance by the United Nations. West and Central Africa settlements with administrative capitals
  • Zones de santé (RDC) / Health zones (DRC)
    OpenStreetMap RDC
    COD 3000+ Downloads
    Time Period of the Dataset [?]: July 09, 2020-December 12, 2021 ... More
    Modified [?]: 12 December 2021
    Dataset Added on HDX [?]: 30 June 2020
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    This dataset updates: Every six months
    Les 519 zones de santé (ZS) de la République démocratique du Congo, extraites de la base de données OpenStreetMap. The 519 health zones of the Democratic Republic of the Congo, extracted from the OpenStreetMap database.
  • "Territoires sanitaires" (RDC) / "Territory Health" Divisions (DRC)
    OpenStreetMap RDC
    400+ Downloads
    Time Period of the Dataset [?]: November 09, 2021-December 12, 2021 ... More
    Modified [?]: 12 December 2021
    Dataset Added on HDX [?]: 30 June 2020
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    This dataset updates: As needed
    This dataset is part of the data series [?]: OSM - DRC Health Zones
    Les limites "sanitaires" des 145 territoires et 19 villes de la République démocratique du Congo, extraites de la base de données OpenStreetMap. The "health" limits of the 145 territories and 19 cities of the Democratic Republic of the Congo, extracted from the OpenStreetMap database.
  • Divisions provinciales de la santé (RDC) / Provincial Health Divisions (DRC)
    OpenStreetMap RDC
    600+ Downloads
    Time Period of the Dataset [?]: November 09, 2021-December 12, 2021 ... More
    Modified [?]: 12 December 2021
    Dataset Added on HDX [?]: 30 June 2020
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    This dataset updates: As needed
    This dataset is part of the data series [?]: OSM - DRC Health Zones
    Les 26 divisions provinciales de la santé (DPS) de la République démocratique du Congo, extraites de la base de données OpenStreetMap. The 26 provincial health divisions of the Democratic Republic of the Congo, extracted from the OpenStreetMap database.
  • DPS Ituri (RDC)
    OpenStreetMap RDC
    400+ Downloads
    Time Period of the Dataset [?]: December 01, 2021-December 08, 2021 ... More
    Modified [?]: 9 December 2021
    Dataset Added on HDX [?]: 8 December 2021
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    This dataset updates: As needed
    This dataset is part of the data series [?]: OSM - DRC Health Zones
    Données de base ou d'intérêt pour le secteur de la santé, extraites de la base de données OpenStreetMap, pour la province de l'Ituri. Ce dossier reprend actuellement des données publiées dans un contexte de formation et révision.