Romania - Humanitarian Data Exchange

Romania: NDVI at Subnational Level

100+ Downloads

Time Period of the Dataset [?]: July 01, 2002-November 20, 2024 ... More

This dataset updates: Every two weeks

This dataset is part of the data series [?]: WFP - NDVI at Subnational Level

This dataset contains dekadal NDVI indicators computed from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6.1 from the Aqua and Terra satellite aggregated by sub-national administrative units. Included indicators are (for each dekad): 10 day NDVI (vim) NDVI long term average (vim_lta) 10 day NDVI anomaly [%] (viq) The administrative units used for aggregation are based on WFP data and contain a Pcode reference attributed to each unit. The number of input pixels used to create the aggregates, is provided in the n_pixelscolumn.

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Attacks on Health Care Monthly News Brief Data

Insecurity Insight

2600+ Downloads

Time Period of the Dataset [?]: January 01, 2016-November 13, 2024 ... More

This dataset updates: As needed

This dataset contains agency- and open source events published in the Attacks on Health Care News Brief. Categorized by country. Please get in touch if you are interested in curated datasets: info@insecurityinsight.org See here for data supporting the Safeguarding Health in Conflict Coalition (SHCC).

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Romania: Road Surface Data

Heidelberg Institute for Geoinformation Technology

Time Period of the Dataset [?]: November 07, 2024-November 07, 2024 ... More

This dataset updates: Every six months

This dataset provides detailed information on road surfaces from OpenStreetMap (OSM) data, distinguishing between **paved** and **unpaved** surfaces across the region. This information is based on road surface prediction derived from hybrid deep learning approach. For more information on Methods, refer to the [paper](http://arxiv.org/abs/2410.19874) Roughly 0.4242 million km of roads are mapped in OSM in this region. Based on AI-mapped estimates the share of paved and unpaved roads is approximately 0.1112 and 0.1025 (in million kms), corressponding to 26.2097% and 24.1636% respectively of the total road length in the dataset region. 0.2105 million km or 49.6267% of road surface information is missing in OSM. In order to fill this gap, Mapillary derived road surface dataset provides an additional 0.0004 million km of information (corressponding to 0.1878% of total missing information on road surface) It is intended for use in transportation planning, infrastructure analysis, climate emissions and geographic information system (GIS) applications. This dataset provides comprehensive information on road and urban area features, including location, surface quality, and classification metadata. This dataset includes attributes from OpenStreetMap (OSM) data, AI predictions for road surface, and urban classifications. AI features: pred_class: Model-predicted class for the road surface, with values "paved" or "unpaved." pred_label: Binary label associated with pred_class (0 = paved, 1 = unpaved). osm_surface_class: Classification of the surface type from OSM, categorized as "paved" or "unpaved." combined_surface_osm_priority: Surface classification combining pred_label and surface(OSM) while prioritizing the OSM surface tag, classified as "paved" or "unpaved." combined_surface_DL_priority: Surface classification combining pred_label and surface(OSM) while prioritizing DL prediction pred_label, classified as "paved" or "unpaved." n_of_predictions_used: Number of predictions used for the feature length estimation. predicted_length: Predicted length based on the DL model’s estimations, in meters. DL_mean_timestamp: Mean timestamp of the predictions used, for comparison. OSM features may have these attributes(Learn what tags mean here): name: Name of the feature, if available in OSM. name:en: Name of the feature in English, if available in OSM. name:* (in local language): Name of the feature in the local official language, where available. highway: Road classification based on OSM tags (e.g., residential, motorway, footway). surface: Description of the surface material of the road (e.g., asphalt, gravel, dirt). smoothness: Assessment of surface smoothness (e.g., excellent, good, intermediate, bad). width: Width of the road, where available. lanes: Number of lanes on the road. oneway: Indicates if the road is one-way (yes or no). bridge: Specifies if the feature is a bridge (yes or no). layer: Indicates the layer of the feature in cases where multiple features are stacked (e.g., bridges, tunnels). source: Source of the data, indicating the origin or authority of specific attributes. Urban classification features may have these attributes: continent: The continent where the data point is located (e.g., Europe, Asia). country_iso_a2: The ISO Alpha-2 code representing the country (e.g., "US" for the United States). urban: Binary indicator for urban areas based on the GHSU Urban Layer 2019. (0 = rural, 1 = urban) urban_area: Name of the urban area or city where the data point is located. osm_id: Unique identifier assigned by OpenStreetMap (OSM) to each feature. osm_type: Type of OSM element (e.g., node, way, relation). The data originates from OpenStreetMap (OSM) and is augmented with model predictions using images downloaded from Mapillary in combination with the GHSU Global Human Settlement Urban Layer 2019 and AFRICAPOLIS2020 urban layer. This dataset is one of many HeiGIT exports on HDX. See the HeiGIT website for more information. We are looking forward to hearing about your use-case! Feel free to reach out to us and tell us about your research at communications@heigit.org – we would be happy to amplify your work.

Romania - Health Indicators

World Health Organization

4200+ Downloads

Time Period of the Dataset [?]: January 01, 1955-December 31, 2030 ... More

This dataset updates: Every month

This dataset is part of the data series [?]: WHO - WHO Health Indicators

This dataset contains data from WHO's data portal covering the following categories: Air pollution, Assistive technology, Child mortality, Dementia diagnosis, treatment and care, Environment and health, Foodborne Diseases Estimates, Global Dementia Observatory (GDO), Global Health Estimates: Life expectancy and leading causes of death and disability, Global Information System on Alcohol and Health, Global Patient Safety Observatory, HIV, Health financing, Health systems, Health taxes, Hepatitis, Immunization coverage and vaccine-preventable diseases, Malaria, Maternal and reproductive health, Mental health, Neglected tropical diseases, Noncommunicable diseases, Nutrition, Oral Health, Priority health technologies, Resources for Substance Use Disorders, Road Safety, SDG Target 3.8 | Achieve universal health coverage (UHC), Sexually Transmitted Infections, Tobacco control, Tuberculosis, Vaccine-preventable communicable diseases, Violence prevention, Water, sanitation and hygiene (WASH), World Health Statistics. For links to individual indicator metadata, see resource descriptions.

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Facebook Business Activity Trends during Crisis

Data for Good at Meta

100+ Downloads

Time Period of the Dataset [?]: June 30, 2024-October 21, 2024 ... More

This dataset updates: As needed

Business Activity Trends during Crisis uses the rate that businesses post on Facebook compared to pre-crisis levels to measure how crisis events are affecting different economic sectors each day. Learn more details here: https://dataforgood.facebook.com/dfg/tools/business-activity-trends and https://dataforgood.facebook.com/dfg/resources/business-activity-trends-methodology-paper Here we are posting datasets from selected crisis events.

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Romania - IFRC Appeals

International Federation of Red Cross and Red Crescent Societies (IFRC)

100+ Downloads

Time Period of the Dataset [?]: January 01, 1997-December 31, 2024 ... More

This dataset updates: Every week

This dataset is part of the data series [?]: IFRC - Appeals

The International Federation of Red Cross and Red Crescent Societies (IFRC) is the world’s largest humanitarian network. Our secretariat supports local Red Cross and Red Crescent action in more than 192 countries, bringing together almost 15 million volunteers for the good of humanity. We launch Emergency Appeals for big and complex disasters affecting lots of people who will need long-term support to recover. We also support Red Cross and Red Crescent Societies to respond to lots of small and medium-sized disasters worldwide—through our Disaster Response Emergency Fund (DREF) and in other ways. There is also a global dataset.

CSV

Romania - Multi-Sector Needs Assessment (MSNA) - 2023

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: July 25, 2023-September 25, 2023 ... More

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Multi-Sector Needs Assessment

The 2023 Multi-Sector Needs Assessment (MSNA) in Romania surveyed 1,222 households representing 3,485 individuals to evaluate the needs of refugees in the country. Conducted from July to September 2023 by a regional interagency team, the assessment aimed to understand refugees’ access to basic services, identify service gaps, and determine refugees’ priorities for the coming year. The data will inform the 2024 Refugee Response Plan, guiding funding and planning requirements for the continued refugee response in Romania. Key focus areas included the in-country refugee population, current level of access to services and how needs are being met, and refugees’ self-reported priorities moving forward. The comprehensive interagency effort provides a critical information baseline to shape an effective, evidence-based humanitarian response.

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Coronavirus (COVID-19) Vaccinations

HDX

6000+ Downloads

Time Period of the Dataset [?]: December 17, 2020-January 11, 2024 ... More

This dataset updates: Live

The map and chart below show the number of COVID-19 vaccination doses administered per 100 people within a given population. Note that this does not measure the total number of people that have been vaccinated (which is usually two doses).

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Total COVID-19 Tests Performed by Country

HDX

22000+ Downloads

Time Period of the Dataset [?]: January 18, 2020-January 11, 2024 ... More

This dataset updates: Every week

'Our World in Data' is compiling COVID-19 testing data over time for many countries around the world. They are adding further data in the coming days as more details become available for other countries. In some cases figures refer to the number of tests, in other cases to the number of individuals who have been tested. Refer to documentation provided here.

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Romania - Education Indicators

UNESCO

500+ Downloads

Time Period of the Dataset [?]: January 01, 1970-December 31, 2023 ... More

This dataset updates: Every three months

This dataset is part of the data series [?]: UNESCO - Education Indicators

Education indicators for Romania. Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: SDG 4 Global and Thematic (made 2024 February), Other Policy Relevant Indicators (made 2024 February), Demographic and Socio-economic (made 2024 February)

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Romania - Human Development Indicators

UNDP Human Development Reports Office (HDRO)

100+ Downloads

Time Period of the Dataset [?]: January 01, 1990-December 31, 2022 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: UNDP Human Development Reports Office - Human Development Indicators

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'.

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Romania - Internal Displacements (New Displacements) – IDPs

Internal Displacement Monitoring Centre (IDMC)

100+ Downloads

Time Period of the Dataset [?]: January 01, 2008-December 31, 2023 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: IDMC - Internally displaced persons

Internally displaced persons are defined according to the 1998 Guiding Principles as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. "Internally displaced persons - IDPs" refers to the number of people living in displacement as of the end of each year. "Internal displacements (New Displacements)" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once. Contains data from IDMC's Global Internal Displacement Database.

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Ukraine: Border Crossings

OCHA Ukraine

3200+ Downloads

Time Period of the Dataset [?]: June 06, 2024-June 06, 2024 ... More

This dataset updates: Every year

This dataset includes the names, types, statuses, and coordinates of international border crossings of Ukraine with Belarus, Hungary, Moldova, Poland, Romania, Russian Federation and Slovakia. The names of the border crossings are in English and Ukrainian.

Romania - Subnational Administrative Boundaries

geoBoundaries

1100+ Downloads

Time Period of the Dataset [?]: January 01, 2016-December 31, 2018 ... More

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.

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Romania: WOF Administrative Subdivisions and Human Settlements

Who's On First

Time Period of the Dataset [?]: August 18, 2015-March 08, 2024 ... More

This dataset updates: Every year

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes: - macroregion (admin-1 including region) - region (admin-2 including state, province, department, governorate) - macrocounty (admin-3 including arrondissement) - county (admin-4 including prefecture, sub-prefecture, regency, canton, commune) - localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb) The dataset also contains human settlement points and polygons for: - localities (city, town, and village) - neighbourhoods (borough, macrohood, neighbourhood, microhood) The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names. Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

SHP

Multi-Sector Needs Assessment (MSNA) - 2023

UNHCR - The UN Refugee Agency

20+ Downloads

Time Period of the Dataset [?]: June 18, 2023-September 24, 2023 ... More

This dataset updates: Never

With the goal of supporting the Inter-Agency Regional Response Plan (RRP) and to enable planning among key humanitarian actors through the provision of updated information on multi-sectoral needs and priorities of refugees from Ukraine, the Regional Refugee Coordination Forum (RCF) agreed on a regional approach to the implementation of inter-agency multi-sectoral needs assessments (MSNA) in 2023. The assessments were conducted around summer of 2023, using a similar methodological approach and a harmonized questionnaire aiming at having comparable results to better inform and prioritize the humanitarian response. This comprehensive regional dataset was compiled by consolidating MSNA datasets from seven countries: Poland, Slovakia, Hungary, Czechia, Moldova, Romania, and Bulgaria.

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Facebook Social Connectedness Index

Data for Good at Meta

29000+ Downloads

Time Period of the Dataset [?]: October 13, 2021-March 15, 2024 ... More

This dataset updates: As needed

We use an anonymized snapshot of all active Facebook users and their friendship networks to measure the intensity of connectedness between locations. The Social Connectedness Index (SCI) is a measure of the social connectedness between different geographies. Specifically, it measures the relative probability that two individuals across two locations are friends with each other on Facebook. Details on the underlying data and the construction of the index are provided in the “Facebook Social Connectedness Index - Data Notes.pdf” file. Please also see https://dataforgood.facebook.com/ as well as the associated research paper “Social Connectedness: Measurement, Determinants and Effects,” published in the Journal of Economic Perspectives (https://www.aeaweb.org/articles?id=10.1257/jep.32.3.259). Region identifiers are taken from GADM v2.8 https://gadm.org/download_country_v2.html. Future versions will update IDs to be compatible with the newest GADM version.

Ukraine Situation Protection Profiling and Monitoring - Oct 2022 - Feb 2023

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: October 01, 2022-February 15, 2023 ... More

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Protection Monitoring

This comprehensive dataset provides invaluable insights into the evolving protection needs and integration challenges facing Ukrainian refugees several months into displacement in major host countries. It contains the results of 17,708 household interviews conducted by UNHCR and partners between October 2022 and February 15, 2023 across 5 key reception countries: Hungary, Republic of Moldova, Poland, Romania, and Slovakia. The interviews were carried out through rigorous random sampling at strategically selected locations including border crossings, reception and transit centers, collective sites, and assistance points in major cities. The questionnaire was redesigned for this second round to focus on pressing longer-term issues like healthcare, education, employment, housing, and local integration. While the sampling provides indicative findings only due to the non-probability approach, the dataset offers a rich evidence base to inform policy and programming. By comparing results over time with the first round (May-November 2022), researchers can analyze trends in refugees' situations, vulnerabilities, coping mechanisms, and unmet needs several months into displacement. The data collection was part of UNHCR's comprehensive protection profiling and monitoring exercise implemented since May 2022 to regularly gather insights into Ukrainian refugees' evolving profiles, risks, and needs. Detailed methodology documentation is provided to support proper interpretation and ethical utilization of the data.

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Romania: Population Density for 400m H3 Hexagons

Kontur

30+ Downloads

Time Period of the Dataset [?]: July 10, 2023-November 01, 2023 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: Kontur - Population Density for 400m H3 Hexagons

Romania population density for 400m H3 hexagons. Built from Kontur Population: Global Population Density for 400m H3 Hexagons Vector H3 hexagons with population counts at 400m resolution. Fixed up fusion of GHSL, Facebook, Microsoft Buildings, Copernicus Global Land Service Land Cover, Land Information New Zealand, and OpenStreetMap data.

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Europe: Ukraine Situation Protection Profiling and Monitoring - Feb-Jun 2023

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: February 16, 2023-June 30, 2023 ... More

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Protection Monitoring

To strengthen and promote an evidence-based protection response, UNHCR and its partners implemented a protection profiling and monitoring exercise in Europe starting in May 2022 to regularly collect and analyze data about the profiles, protection risks, and needs of refugees from Ukraine and monitor changes over time. The exercise covered the following countries that received refugees from Ukraine: Belarus, Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Republic of Moldova, Poland, Romania and Slovakia. The protection profiling and monitoring involved household-level interviews conducted at border crossing points, reception and transit centres, collective sites, and assistance points in major cities using a structured questionnaire. Trained enumerators from UNHCR and partners collected data digitally using the Kobo Toolbox. While respondents were randomly selected to reduce bias, the sample is considered a non-probability sample and results should be considered indicative, meaning they cannot be extrapolated to the population of refugees from Ukraine. The result reflects the refugees' situation at the time of data collection. The first round of data collection took place between May and Nov 2022. The focus of the first round was general profiling of Ukraine refugees and their needs, as well as key issues during the intial phase of the crisis such as family separation, etc. In October 2022, a new questionnaire was rolled out, shifting towards exploring longer-term issues in host countries such as access to health care, education, etc. The second round took place between Oct 2022 and 15 Feb 2023. overlapping slightly with the first round, however the datasets are not comparable due to the change in the questionnaire. The third round employed the same questionnaire as the second, and took place between 16 Feb and 30 Jun 2023. This dataset is the anonymous version of the data that was collected during the third round. It includes 21,340 household interviews. Data from the following countries are new to this round: Czechia, Estonia, Latvia, and Lithuania. The data from the first round is also available on the Microdata Library as a separate dataset for each country where the exercise took place.

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Romania: Administrative Division with Aggregated Population

Kontur

30+ Downloads

Time Period of the Dataset [?]: April 07, 2022-April 07, 2022 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: Kontur - Administrative Division with Aggregated Population

Romania administrative division with aggregated population. Built from Kontur Population: Global Population Density for 400m H3 Hexagons on top of OpenStreetMap administrative boundaries data. Enriched with HASC codes for regions taken from Wikidata. Global version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population

Geopackage

Survey of intentions and perspectives of refugees from Ukraine #3 - Feb 2023

UNHCR - The UN Refugee Agency

10+ Downloads

Time Period of the Dataset [?]: December 21, 2022-January 14, 2023 ... More

This dataset updates: Never

To ensure the centrality of refugees’ voices in discussions about their future, as well as to inform evidence-based inter-agency responses in support of host Governments, UNHCR is leading the regular implementation of intentions surveys with refugees from Ukraine, collecting primary data on their profiles, their current situation and intentions, and the factors influencing their decision-making. The first and second regional intentions surveys were completed and the report published in July 2022 (https://data.unhcr.org/en/documents/details/94176) and September 2022 (https://data.unhcr.org/en/documents/details/95767). This data was collected during the third round, conducted between December 2022 and January 2023. The survey covered refugees hosted in countries in Europe. In addition, the third round included a longitudinal sample of refugees surveyed in both the second and third rounds. The report was published in Februrary 2023 (https://data.unhcr.org/en/documents/details/99072). A mixed methodological approach was used, combining two data collection modes. Around 3,900 refugee households (2,100 from countries neighboring Ukraine and 1,800 from other host countries) were interviewed either through a phone-based survey, web-based survey or face-to-face interview. A total of 887 households participated in both the second and third round (longitudinal sample). All surveys used a harmonized questionnaire. This data is an anonymous version of the original data collected and used for the primary analysis.

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Survey of intentions and perspectives of refugees from Ukraine #2 - Sept 2022

UNHCR - The UN Refugee Agency

20+ Downloads

Time Period of the Dataset [?]: August 01, 2022-September 30, 2022 ... More

This dataset updates: Never

This dataset is part of the data series [?]: UNHCR - Intention to return survey

To ensure the centrality of refugees’ voices in discussions about their future, as well as to inform evidence-based inter-agency responses in support of host Governments, UNHCR is leading the regular implementation of intentions surveys with refugees from Ukraine, collecting primary data on their profiles, their current situation and intentions, and the factors influencing their decision-making. The first regional intentions survey was completed and the report published in July 2022 (https://data.unhcr.org/en/documents/details/94176). This data was collected during the second round, conducted between August and September 2022. The scope was expanded to include not only countries neighbouring Ukraine but other host countries in Europe and beyond. In addition, the second round also includes a deeper analysis of the factors influencing refugees’ decisions, as well as key insights into their current socio-economic situation. The report was published in September 2022 (https://data.unhcr.org/en/documents/details/95767). A mixed methodological approach was used, combining different sampling approaches and data collection modes. Over 4,800 refugee households (2,000 from countries neighboring Ukraine and 2,800 from other host countries) were interviewed either through a phone-based survey, web-based survey or face-to-face interview. All surveys used a harmonized questionnaire. This data is an anonymous version of the original data collected and used for the primary analysis.

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Survey of intentions and perspectives of refugees from Ukraine #4 - June 2023

UNHCR - The UN Refugee Agency

20+ Downloads

Time Period of the Dataset [?]: April 24, 2023-May 19, 2023 ... More

This dataset updates: Never

To ensure the centrality of refugees’ voices in discussions about their future, as well as to inform evidence-based inter-agency responses in support of host Governments, UNHCR is leading the regular implementation of intentions surveys with refugees from Ukraine, collecting primary data on their profiles, their current situation and intentions, and the factors influencing their decision-making. The first, second and third regional intentions surveys were completed and the reports published in July 2022 (https://data.unhcr.org/en/documents/details/94176), September 2022 (https://data.unhcr.org/en/documents/details/95767) and February 2023 (https://data.unhcr.org/en/documents/details/99072). This data was collected during the fourth round, conducted between April and May 2023. The survey covered refugees hosted in countries in Europe. A mixed methodological approach was used, combining two data collection modes. Around 3,850 refugee households were interviewed either through a phone-based survey, web-based survey or face-to-face interview. The data include a mix of Fresh refugee households (i.e. not included in previous rounds) and Panel households (i.e. those included in at least one of the previous rounds). All surveys used a harmonized questionnaire. This data is an anonymous version of the original data collected and used for the primary analysis.

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Romania - Subnational Population Statistics

UNFPA

COD+ 1100+ Downloads

Time Period of the Dataset [?]: January 01, 2022-December 31, 2022 ... More

This dataset updates: Every year

This dataset is part of the data series [?]: COD - Subnational Population Statistics

Romania administrative level 0-2 sex and age disaggregated 2022 population statistics REFERENCE YEAR 2022 These tables are suitable for database or GIS linkage to the Romania - Subnational Administrative Boundaries layers.