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  • 5700+ Downloads
    Time Period of the Dataset [?]: June 23, 1984-May 18, 2025 ... More
    Modified [?]: 12 May 2025
    Dataset Added on HDX [?]: 20 April 2023
    This dataset updates: Every week
    CSV containing subnational p-codes, their corresponding administrative names, parent p-codes, and reference dates for the world (where available). These are constructed using the COD gazetteers. English names are used where available, followed by names written in Latin alphabets. Note that Indonesia admin4 is not included for now, as that data is contained in a second, non-standard gazetteer.
  • 1200+ Downloads
    Time Period of the Dataset [?]: June 23, 2022-May 18, 2025 ... More
    Modified [?]: 5 May 2025
    Dataset Added on HDX [?]: 23 June 2022
    This dataset updates: Live
    This layer shows the different administrative boundaries (levels: 1) used in the UNHCR GIS system. It is mostly from governments and official sources but also other UN bodies or NGOs. The OCHA CODs and Pcodes are examined and considered. The boundaries and names do not imply official endorsement or acceptance by the United Nations.
  • 1200+ Downloads
    Time Period of the Dataset [?]: June 23, 2022-May 18, 2025 ... More
    Modified [?]: 5 May 2025
    Dataset Added on HDX [?]: 23 June 2022
    This dataset updates: Live
    This layer shows the different administrative boundaries (levels: 2) used in the UNHCR GIS system. It is mostly from governments and official sources but also other UN bodies or NGOs. The OCHA CODs and Pcodes are examined and considered. The boundaries and names do not imply official endorsement or acceptance by the United Nations.
  • 200+ Downloads
    Time Period of the Dataset [?]: June 07, 2021-May 18, 2025 ... More
    Modified [?]: 5 May 2025
    Dataset Added on HDX [?]: 22 June 2022
    This dataset updates: Live
    Point layer that represents populated places locations (e.g., capitals/ cities/ towns) and of administrative units (Level 1, 2 and 3 depending on availability).
  • 300+ Downloads
    Time Period of the Dataset [?]: February 11, 2025-February 11, 2025 ... More
    Modified [?]: 19 April 2025
    Dataset Added on HDX [?]: 28 January 2019
    This dataset updates: As needed
    MIMU Pcode is similar to a zip code or postal code, and is a part of a data management system providing unique reference codes to around 67,000 locations across Myanmar. The MIMU maintains the P-codes for Myanmar based on information collected from a variety of sources, including the Government gazette and humanitarian and development organizations. Without a system for organizing such data it is almost impossible for data from more than one source to be combined.
  • Time Period of the Dataset [?]: October 01, 2023-April 30, 2024 ... More
    Modified [?]: 2 April 2025
    Dataset Added on HDX [?]: 6 April 2025
    This dataset updates: Never
    This dataset presents findings from Protection Profiling and Monitoring conducted by UNHCR and partners between October 2023 and April 2024 across Belarus, Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Moldova, Poland, Romania, and Slovakia. The objective of this regional exercise is to strengthen evidence-based protection responses by regularly collecting and analyzing data on the demographics, protection risks, legal needs, displacement patterns, and basic needs of refugees from Ukraine. Data was gathered through household-level interviews conducted face-to-face at border crossing points, reception and transit centers, collective sites, and assistance locations in major cities. The structured questionnaire was administered by trained enumerators from UNHCR and partner organizations using digital data collection tools. Although respondents were selected to reduce bias, the sample follows a non-probability design and results should be interpreted as indicative rather than statistically representative of the refugee population.
  • Time Period of the Dataset [?]: July 01, 2024-October 31, 2024 ... More
    Modified [?]: 2 April 2025
    Dataset Added on HDX [?]: 6 April 2025
    This dataset updates: Never
    This dataset presents findings from Protection Profiling and Monitoring conducted by UNHCR and partners between July and October 2024 across Belarus, Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Moldova, Poland, Romania, and Slovakia. The objective of this regional exercise is to strengthen evidence-based protection responses by regularly collecting and analyzing data on the profiles, protection risks, legal needs, displacement patterns, and basic needs of refugees from Ukraine. Data was gathered through household-level interviews conducted face-to-face at border crossing points, reception and transit centers, collective sites, and assistance locations in major cities. The structured questionnaire was administered by trained enumerators from UNHCR and partner organizations using digital data collection tools. Although respondents were selected to reduce bias, the sample follows a non-probability design and results should be interpreted as indicative rather than statistically representative of the refugee population.
  • COD 1100+ Downloads
    Time Period of the Dataset [?]: March 11, 2024-March 31, 2024 ... More
    Modified [?]: 28 March 2025
    Dataset Added on HDX [?]: 11 March 2024
    This dataset updates: As needed
    This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries
    Myanmar administrative level 0-5 boundaries (COD-AB) dataset. The date that these administrative boundaries were established is unknown. This COD-AB was most recently reviewed for accuracy and necessary changes in March 2024. The COD-AB requires improvements. Sourced from Myanmar Information Management Unit (MIMU) Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID. This COD-AB is suitable for database or GIS linkage to the Myanmar COD-PS. An edge-matched (COD-EM) version of this COD-AB is available on HDX here. Please see the COD Portal. Administrative level 1 contains 18 feature(s). The normal administrative level 1 feature type is ""State/Region"". Administrative level 2 contains 80 feature(s). The normal administrative level 2 feature type is ""District"". Administrative level 3 contains 330 feature(s). The normal administrative level 3 feature type is ""Township"". Administrative level 4 contains 14,174 feature(s). The normal administrative level 4 feature type is ""Town / Village tract"". Recommended cartographic projection: Asia South Albers Equal Area Conic This metadata was last updated on January 9, 2025.
  • 20+ Downloads
    Time Period of the Dataset [?]: January 22, 2025-January 22, 2025 ... More
    Modified [?]: 26 March 2025
    Dataset Added on HDX [?]: 26 March 2025
    This dataset updates: As needed
    This shapefile provides information about the extent and availability of aerial photograph coverage across Ethiopia. This dataset is valuable for professionals and researchers involved in cartography, land use planning, environmental monitoring, and infrastructure development, as it helps identify areas with existing aerial imagery and potential gaps where additional coverage may be needed.​ For more detailed information: Ethiopia Arial Photo Coverage
  • 200+ Downloads
    Time Period of the Dataset [?]: October 24, 2024-October 24, 2024 ... More
    Modified [?]: 26 March 2025
    Dataset Added on HDX [?]: 26 March 2025
    This dataset updates: As needed
    The dataset titled "Addis Ababa City Administration Woreda Boundary" provides detailed geographic information on the administrative divisions within Addis Ababa, Ethiopia. It includes shapefiles delineating the boundaries of both subcities and woredas (districts) within the city. Each feature in the dataset is attributed with identifiers and names corresponding to specific subcities and woredas, facilitating spatial analysis and mapping of Addis Ababa's administrative structure.​ This dataset is particularly useful for urban planning, resource allocation, and various analyses requiring precise administrative boundary data within Addis Ababa. Original source: Addis Ababa City Administration Woreda Boundary
  • COD+ 4100+ Downloads
    Time Period of the Dataset [?]: May 30, 2017-January 09, 2025 ... More
    Modified [?]: 21 March 2025
    Dataset Added on HDX [?]: 16 October 2015
    This dataset updates: Every year
    This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries
    Ecuador administrative level 0-3 boundaries (COD-AB) dataset. These administrative boundaries were established in: 2017 NOTE: ADM4 feature names are not yet availalble. (Currently ADM4_PCODE is copied into ADM4_ES as a proxy.) No lines layer is yet availalbe. The live geoservices do not reflect the new ADM4 level. This COD-AB was most recently reviewed for accuracy and necessary changes in December 2024. The COD-AB does not require any update. Sourced from INEC - Instituto Nacional de Estadística y Censos Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID. This COD-AB is suitable for database or GIS linkage to the Ecuador COD-PS. No edge-matched (COD-EM) version of this COD-AB has yet been prepared. Please see the COD Portal. Administrative level 1 contains 26 feature(s). The normal administrative level 1 feature type is ""currently not known"". Administrative level 2 contains 223 feature(s). The normal administrative level 2 feature type is ""currently not known"". Administrative level 3 contains 1,044 feature(s). The normal administrative level 3 feature type is ""currently not known"". Recommended cartographic projection: South America Albers Equal Area Conic This metadata was last updated on January 9, 2025.
  • Time Period of the Dataset [?]: June 02, 2024-July 12, 2024 ... More
    Modified [?]: 18 March 2025
    Dataset Added on HDX [?]: 9 February 2025
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Multi-Sector Needs Assessment
    The 2024 Socio-Economic Insights Survey (SEIS) in Moldova, conducted by UNHCR in partnership with REACH, provides essential data on the needs of refugees and third-country nationals displaced from Ukraine. Building on the 2023 Multi-Sectoral Needs Assessment (MSNA), this household-level survey collected insights on protection, food security, education, livelihoods, health, and socio-economic inclusion to inform humanitarian planning and decision-making. A total of 622 in-person interviews were conducted across Moldova (excluding the Transnistrian region) between June 3 and July 12, 2024. The survey used purposive and respondent-assisted sampling to capture household and individual-level data on living conditions, access to services, and integration challenges. This anonymized dataset supports stakeholders in addressing the needs of displaced populations and promoting integration and access to essential services in Moldova.
  • Time Period of the Dataset [?]: May 20, 2024-July 27, 2024 ... More
    Modified [?]: 18 March 2025
    Dataset Added on HDX [?]: 12 January 2025
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Multi-Sector Needs Assessment
    The 2024 Socio-Economic Insights Survey (SEIS) in Romania is a comprehensive regional assessment conducted from May to July 2024, focusing on the needs of refugees in Romania, particularly those from Ukraine. This multi-sectoral survey aims to capture key data on refugees' socio-economic integration, access to national systems, and their priorities for the coming year, providing valuable insights to inform the 2025 Refugee Response Plan (RRP). The survey employs a stratified random sampling method and involves face-to-face and online interviews with refugees, covering topics such as health, education, protection, food security, and livelihoods. The collected data is anonymized and cleaned for use in policy planning and intervention development. The findings highlight gaps in services and provide crucial information on the changing trends in refugees’ needs, contributing to a more targeted and effective response to refugee challenges in Romania.
  • Time Period of the Dataset [?]: May 21, 2024-July 27, 2024 ... More
    Modified [?]: 18 March 2025
    Dataset Added on HDX [?]: 8 December 2024
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Multi-Sector Needs Assessment
    The 2024 Socio-Economic Insights Survey (SEIS) in Slovakia provides a comprehensive assessment of the needs and vulnerabilities of refugees from Ukraine. Conducted as part of an annual interagency regional process led by UNHCR, this assessment supports the Regional Refugee Response Plan (RRP) for the Ukraine Situation. Covering topics such as protection, health, education, shelter, livelihoods, and food security, the survey offers critical data to inform evidence-based planning and prioritization, ensuring the specific needs of different refugee groups are addressed. Data collection was conducted through face-to-face interviews from May to July 2024 with a probability-based random sample of refugee households, managed collaboratively by UNHCR and the International Organization for Migration. Findings will guide strategic interventions and resource allocation to enhance the welfare and resilience of the refugee population in Slovakia.
  • Time Period of the Dataset [?]: May 30, 2024-July 14, 2024 ... More
    Modified [?]: 18 March 2025
    Dataset Added on HDX [?]: 12 January 2025
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Multi-Sector Needs Assessment
    The 2024 SEIS in Czechia provides a comprehensive assessment of the needs and vulnerabilities of refugees from Ukraine. Conducted as part of the annual interagency regional process led by UNHCR, the survey supports the Regional Refugee Response Plan (RRP) for the Ukraine Situation. By addressing key areas such as protection, health, education, shelter, livelihoods, and food security, it delivers essential data to inform evidence-based planning and ensure the diverse needs of refugee groups are met. Data collection took place from May to July 2024 and followed a purposive sampling approach. While not random, the methodology was designed to reflect the geographical and gender distribution of the refugee population using Temporary Protection (TP) data from the Ministry of Interior. Enumerators worked within these parameters, using the snowball method to identify respondents who matched the criteria. The survey was a collaborative effort by UNHCR and the International Organization for Migration. Its findings will inform strategic planning and resource allocation to improve the welfare and resilience of refugees in Czechia.
  • Time Period of the Dataset [?]: May 10, 2024-October 29, 2024 ... More
    Modified [?]: 18 March 2025
    Dataset Added on HDX [?]: 6 April 2025
    This dataset updates: Never
    The 2024 Regional Socio-Economic Insights Survey (SEIS) provides critical data to inform the 2025 Regional Refugee Response Plan (RRP), supporting strategic planning and funding allocation to address regional needs. This consolidated dataset includes comprehensive information from Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Moldova, Poland, Romania, and Slovakia, covering essential topics such as demographics, protection, education, socio-economic inclusion and livelihoods, health, and accommodation. By synthesizing data from these ten countries, the SEIS offers a detailed view of key areas impacting refugee and host communities, supporting evidence-based decisions for targeted interventions and resource mobilization across the region.
  • Time Period of the Dataset [?]: January 17, 2023-February 09, 2023 ... More
    Modified [?]: 18 March 2025
    Dataset Added on HDX [?]: 28 July 2024
    This dataset updates: Never
    The 2023 Results Monitoring Survey (RMS) in the Republic of Congo aimed to monitor key impact and outcome indicators related to education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation for refugees and asylum seekers. The survey was conducted between January 17 and February 9, 2023, targeting 1,900 households across Brazzaville, Pointe-Noire, Likouala, and Cuvette. The survey achieved interviews with 1,473 households (77.53% coverage), with data collected through Computer-Assisted Personal Interviews (CAPI). The results contribute to an evidence base for UNHCR’s multi-year strategies in the country.
  • Time Period of the Dataset [?]: December 01, 2022-January 23, 2023 ... More
    Modified [?]: 18 March 2025
    Dataset Added on HDX [?]: 28 July 2024
    This dataset updates: Never
    The Results-Monitoring Survey (RMS) was conducted by UNHCR South Sudan in the last quarter of 2022 to serve as a pilot tool for measuring country operations' results regarding internally displaced persons (IDPs). Using computer-assisted personal interviews, around 4,634 questionnaires were carried out proportionally across eight states. The target was IDPs in camps and non-camp settings, including hard-to-reach areas. A simple random sampling method was used to allow generalizability and minimize bias. The questionnaire was tailored to the local context while drawing from the standard RMS instrument. Sample sizes were calculated for states and counties based on displacement figures and partner presence. A 95% confidence level and 5% margin of error determined the state samples. The county samples used 90% confidence and 5% margins given the need for greater precision at lower administrative levels. Total target was 5,309 households, allocated proportionally. High response rate (97%) exceeded targets in some counties. The pilot provides baseline data on results indicators to track over time. Key aspects were representative sampling, localized questionnaire, sufficient sample size, and community access enabling quality data for ongoing monitoring.
  • Time Period of the Dataset [?]: February 27, 2023-April 07, 2024 ... More
    Modified [?]: 18 March 2025
    Dataset Added on HDX [?]: 28 July 2024
    This dataset updates: Never
    The UNHCR Results Monitoring Survey (RMS) in Mozambique, conducted from February 27, 2023, to April 7, 2024, by CS Research and the United Nations High Commissioner for Refugees, assessed the impact in areas such as Health and Nutrition, Water Sanitation Hygiene, Protection, and Education among refugees, asylum-seekers, and IDPs. Covering regions like Cabo Delgado and Nampula, the survey employed mixed sampling methods, including phone surveys (CATI) for widespread geographical coverage, excluding Nampula City and Maratane Camp, and face-to-face interviews (CAPI) in specified areas. This approach, integrating non-probabilistic and probabilistic techniques, and stratified by gender, provided comprehensive data, crucial for UNHCR’s strategic planning and reporting in Mozambique.
  • 10+ Downloads
    Time Period of the Dataset [?]: July 13, 2023-August 21, 2023 ... More
    Modified [?]: 18 March 2025
    Dataset Added on HDX [?]: 7 January 2024
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Multi-Sector Needs Assessment
    A multi-sectoral needs assessment was conducted in Poland between July 13, 2023 and August 25, 2023, surveying 5,645 households comprising 13,421 individuals. The assessment aimed to capture the needs of refugees in Poland, understand their level of access to basic services, how their needs are currently being met, gaps in services, and priorities for the refugee response in the coming year. Key findings will inform the 2024 Regional Refugee Response Plan for Poland, providing critical data on priorities and funding requirements to support refugees. With 5,645 households surveyed across multiple sectors, the assessment provides a robust evidence base to shape a more effective, responsive refugee program in Poland.
  • COD+ 5600+ Downloads
    Time Period of the Dataset [?]: August 30, 2018-March 06, 2025 ... More
    Modified [?]: 6 March 2025
    Dataset Added on HDX [?]: 30 August 2018
    This dataset updates: Every year
    This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries
    Angola administrative level 0-3 boundaries (COD-AB) dataset. The date that these administrative boundaries were established is unknown. NOTE: See COD-PS caveats about two special ADM2 records. The shapefile zipfile in the HDX dataset was corrected in March 2025. It previously excluded the ADM1 layer. This COD-AB was most recently reviewed for accuracy and necessary changes in January 2025. The COD-AB requires improvements. Sourced from OCHA Regional Office for Southern and Eastern Africa (ROSEA) Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. USERS SHOULD BE AWARE that changes to COD-AB datasets on HDX since February 2025 will NOT be reflected in the live geoservices. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID. This COD-AB is suitable for database or GIS linkage to the Angola COD-PS. No edge-matched (COD-EM) version of this COD-AB has yet been prepared. Please see the COD Portal. Administrative level 1 contains 18 feature(s). The normal administrative level 1 feature type is 'Province'. Administrative level 2 contains 161 feature(s). The normal administrative level 2 feature type is 'Municipality'. Administrative level 3 contains 539 feature(s). The normal administrative level 3 feature type is 'currently not known'. Recommended cartographic projection: Africa Albers Equal Area Conic This metadata was last updated on March 06, 2025.
  • COD+ 3100+ Downloads
    Time Period of the Dataset [?]: September 06, 2017-February 28, 2025 ... More
    Modified [?]: 4 March 2025
    Dataset Added on HDX [?]: 6 September 2017
    This dataset updates: As needed
    This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries
    Dominican Republic administrative level 0-4 boundaries (COD-AB) dataset. The date that these administrative boundaries were established is unknown. NOTE: This COD-AB was updated by OCHA FIS in March 2025 without the most complete quality control processes. The live geoservices have not been similarly updated. The accompanying COD-EM has not been similarly updated. The COD-PS extends only to ADM2 This COD-AB was most recently reviewed for accuracy and necessary changes in February 2025. The COD-AB does not require any update. Sourced from OCHA Field Information Services Section (FISS) Live geoservices (provided by Information Technology Outreach Services (ITOS) with funding from USAID) are available for this COD-AB. USERS SHOULD BE AWARE that changes to COD-AB datasets on HDX since February 2025 will NOT be reflected in the live geoservices. Please see COD_External. (For any earlier versions please see here, here, and here.) Vetting, configuration, and geoservices provision by Information Technology Outreach Services (ITOS) with funding from USAID. This COD-AB is suitable for database or GIS linkage to the Dominican Republic COD-PS. An edge-matched (COD-EM) version of this COD-AB is available on HDX here. Please see the COD Portal. Administrative level 1 contains 10 feature(s). The normal administrative level 1 feature type is 'region'. Administrative level 2 contains 32 feature(s). The normal administrative level 2 feature type is 'province or national district (distrito nacional)'. Administrative level 3 contains 158 feature(s). The normal administrative level 3 feature type is 'municipio'. Administrative level 4 contains 383 feature(s). The normal administrative level 4 feature type is 'dm(?)'. Recommended cartographic projection: North America Albers Equal Area Conic This metadata was last updated on March 04, 2025.
  • Time Period of the Dataset [?]: May 13, 2024-September 26, 2024 ... More
    Modified [?]: 28 February 2025
    Dataset Added on HDX [?]: 2 March 2025
    This dataset updates: Never
    The Community-Based Assessment (CBA) in South Sudan, 2024 evaluates the capacity of high-return locations in South Sudan to absorb additional populations. This assessment employed a mixed-methods approach, including quantitative household surveys, qualitative assessments, and infrastructure evaluations. Data collection was conducted between May and September 2024 through face-to-face interviews in selected payams across Northern Bahr el Ghazal, Eastern Equatoria, Central Equatoria, and Western Bahr el Ghazal. The dataset comprises anonymized household and infrastructure survey data, with stratified random sampling used to ensure representation across returnees, host communities, internally displaced persons (IDPs), and refugees. The study explores key humanitarian themes, including health, water sanitation and hygiene (WASH), education, and housing, land, and property (HLP). The collected data aims to inform operational planning, self-reliance programs, and service provision strategies for displaced and returning populations. The dataset provides valuable insights to support evidence-based decision-making and improve response strategies for communities affected by displacement in South Sudan.
  • 60+ Downloads
    Time Period of the Dataset [?]: January 01, 2004-May 18, 2025 ... More
    Modified [?]: 27 February 2025
    Dataset Added on HDX [?]: 27 February 2024
    This dataset updates: Every year
    The Global Violent Deaths (GVD) database integrates indicators on the major causes of lethal interpersonal and communal violence—intentional and unintentional homicides, killings in legal interventions, and direct conflict deaths—and combines them in a single violent deaths indicator. These indicators are also reported in a disaggregated format by the sex of the victim and perpetration mechanism, namely firearm killings. The GVD database tracks this information across 222 countries and territories worldwide yearly from 2004 and reports both crude counts and rates per 100,000 population. The input data is retrieved from reliable sources, such as governments, national and international organizations, trusted non-governmental organizations, and verified media outlets. Missing data points are estimated using the methods described in this document. The GVD database is updated annually by the Small Arms Survey, an associated programme of the Geneva Graduate Institute, which strengthens the capacity of governments and practitioners to reduce illicit arms flows and armed violence. This is done through three mutually reinforcing activities: the generation of policy-relevant knowledge, the development of authoritative resources and tools, and the provision of training and other services. The GVD database benefits from financial support from governments and organizations, and notably its core donors, who are publicly disclosed online. The Small Arms Survey follows rigorous procedures to ensure that the input data, the applied methods, and the results are of reasonable quality. If the user encounters apparent errors, they should contact us via email at media@smallarmssurvey.org. Regions, sub-regions, countries, and territories are defined based on the classification system used by the UN Statistical Division (2013 revision), except for Kosovo, England and Wales, Northern Ireland, and Scotland. The names and designations reported in the database do not imply any sort of endorsement by the Small Arms Survey.
  • 40+ Downloads
    Time Period of the Dataset [?]: May 01, 2024-May 01, 2024 ... More
    Modified [?]: 20 February 2025
    Dataset Added on HDX [?]: 8 January 2025
    This dataset updates: As needed
    SIRA Dataset for disability and older age - Cabo Delgado, Mozambique Background The Survey for Inclusive Rapid Assessment (SIRA) Dataset for disability and older age was collected in May 2024 in Pemba (urban) and Metuge (rural) localities of Cabo Delgado, Mozambique, as part of the Data that Matters project funded by Elrha. Stratified clustered random sampling was used in this survey, the aim of which is to assess the barriers and enablers people face in accessing humanitarian assistance, in particular persons with disabilities and older persons. The Data The dataset consists of: * SIRA Dataset #1. Household-level data: locality, household size, displacement status, registration * SIRA Dataset #2. Individual-level data: sex, age, education, health, employment * SIRA Dataset #3. Individual-level data: Washington Group (WG) questions taken from short (WG_SS), extended (WG-ES) of questions and child functioning modules (0-4 and 5-17 years). Questions include functioning domains associated with mental health. * SIRA Dataset #4. Individual-level data: barriers in accessing humanitarian assistance for i) distributions, ii) services, iii) livelihood opportunities, iv) sexual, maternal and reproductive health, v) safety and security. The datasets can be merged via the respondent identifier "indID", with "hhID" allowing to group individuals linked to a common household.