Serbia - Humanitarian Data Exchange

Topline Indicators

World Bank Group

1000+ Downloads

Time Period of the Dataset [?]: January 01, 2011-December 31, 2023 ... More

This dataset updates: Every month

Data used to update country toplines in HDX. Contains data from World Bank's data portal.

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Serbia Healthsites

Global Healthsites Mapping Project

400+ Downloads

Time Period of the Dataset [?]: August 11, 2009-July 21, 2024 ... More

This dataset updates: Every three months

This dataset is part of the data series [?]: Global Healthsites Mapping Project - Healthsites

This dataset shows the list of operating health facilities. Attributes included: Name,Nature of Facility, Activities, Lat, Long

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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Serbia: 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 0.2264 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 0.0421 and 0.0367 (in million kms), corressponding to 18.5823% and 16.2183% respectively of the total road length in the dataset region. 0.1476 million km or 65.1994% of road surface information is missing in OSM. In order to fill this gap, Mapillary derived road surface dataset provides an additional 0.0005 million km of information (corressponding to 0.3424% 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.

Serbia - Health Indicators

World Health Organization

4400+ Downloads

Time Period of the Dataset [?]: January 01, 1974-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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Serbia - Internal Displacements Updates (IDU) (event data)

Internal Displacement Monitoring Centre (IDMC)

90+ Downloads

Time Period of the Dataset [?]: May 03, 2024-October 30, 2024 ... More

This dataset updates: Every day

This dataset is part of the data series [?]: IDMC - Internal Displacement Updates

Conflict and disaster population movement (flows) data for Serbia. The data is the most recent available and covers a 180 day time period. 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. The IDMC's Event data, sourced from the Internal Displacement Updates (IDU), offers initial assessments of internal displacements reported within the last 180 days. This dataset provides provisional information that is continually updated on a daily basis, reflecting the availability of data on new displacements arising from conflicts and disasters. The finalized, carefully curated, and validated estimates are then made accessible through the Global Internal Displacement Database (GIDD). The IDU dataset comprises preliminary estimates aggregated from various publishers or sources.

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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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Serbia - 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 Serbia. 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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Serbia - Human Development Indicators

UNDP Human Development Reports Office (HDRO)

100+ Downloads

Time Period of the Dataset [?]: January 01, 1995-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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Serbia - Internal Displacements (New Displacements) – IDPs

Internal Displacement Monitoring Centre (IDMC)

200+ Downloads

Time Period of the Dataset [?]: January 01, 2010-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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Serbia - Subnational Administrative Boundaries

geoBoundaries

900+ Downloads

Time Period of the Dataset [?]: January 01, 2017-December 31, 2017 ... 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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Serbia - IFRC Appeals

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

100+ Downloads

Time Period of the Dataset [?]: November 30, 2007-January 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.

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Serbia: WOF Administrative Subdivisions and Human Settlements

Who's On First

10+ Downloads

Time Period of the Dataset [?]: August 18, 2015-March 05, 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.

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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.

Serbia: Population Density for 400m H3 Hexagons

Kontur

70+ 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

Serbia 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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Serbia: 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

Serbia 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

Europe: Coronavirus (COVID-19) Subnational Cases

HDX

3000+ Downloads

Time Period of the Dataset [?]: August 02, 2021-December 08, 2024 ... More

This dataset updates: As needed

This dataset is part of the data series [?]: HDX - COVID-19 Subnational Cases

This dataset contains the number of confirmed cases, recoveries and deaths by country and subnational region due to the Coronavirus pandemic in Europe. Since the outbreak of the COVID-19 crisis, the Joint Research Centre (JRC) has been supporting the European Commission in multidisciplinary areas to understand the COVID-19 emergency, anticipate its impacts, and support contingency planning. This data provides an overview of the monitoring in the area of the 34 UCPM Participating States plus Switzerland related to sub-national data (admin level 1) on numbers of contagious and fatalities by COVID-19, collected directly from the National Authoritative sources (National monitoring websites, when available). The sub-national granularity of the data allows to have a fit-for-purpose model to early capture the local spread and response to the COVID-19 outbreak. The data is maintained on the JRC COVID-19 Github Repository

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Small Business Surveys - Aggregated Data

Data for Good at Meta

16000+ Downloads

Time Period of the Dataset [?]: September 01, 2016-March 24, 2023 ... More

This dataset updates: Every three months

More than 200 million businesses use Facebook globally. The goal of Meta’s quarterly Small Business Surveys is to learn about the unique perspectives, challenges and opportunities of small and medium-sized businesses (SMBs). The Future of Business (FoB) Survey is conducted biannually in partnership with the World Bank and the Organisation for Economic Cooperation and Development (OECD) across nearly 100 countries. The target population consists of SMEs that have an active Facebook Business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. Meta also conducts the Global State of Small Business (GSoSB) Survey bi-annually in partnership with various academic partners across approximately 30 countries. Similarly to the FoB Survey, the target population is active Facebook Page Administrators, but also includes the general population of Facebook users. Survey questions for all surveys cover a range of topics depending on the survey wave such as business characteristics, challenges, financials and strategy in addition to custom modules related to regulation, gender inequity, access to finance, digital technologies, reduction in revenues, business closures, international trade, inflation, reduction of employees and challenges/needs of the business. Aggregated country level data for each survey wave is available to the public on HDX and controlled access microdata is available to Data for Good at Meta partners. Please visit https://dataforgood.facebook.com/dfg/tools/future-of-business-survey to apply for access to microdata or contact dataforgood@fb.com for any questions.

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Relative Wealth Index

Data for Good at Meta

27000+ Downloads

Time Period of the Dataset [?]: April 01, 2021-February 17, 2023 ... More

This dataset updates: As needed

The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. The data is provided for 93 low and middle-income countries at 2.4km resolution. Please cite / attribute any use of this dataset using the following: Microestimates of wealth for all low- and middle-income countries Guanghua Chi, Han Fang, Sourav Chatterjee, Joshua E. Blumenstock Proceedings of the National Academy of Sciences Jan 2022, 119 (3) e2113658119; DOI: 10.1073/pnas.2113658119 More details are available here: https://dataforgood.fb.com/tools/relative-wealth-index/ Research publication for the Relative Wealth Index is available here: https://www.pnas.org/content/119/3/e2113658119 Press coverage of the release of the Relative Wealth Index here: https://www.fastcompany.com/90625436/these-new-poverty-maps-could-reshape-how-we-deliver-humanitarian-aid An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/

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Admissions for Treatment of Severe Acute Malnutrition (SAM)

UNICEF Data and Analytics (HQ)

400+ Downloads

Time Period of the Dataset [?]: February 08, 2021-December 08, 2024 ... More

This dataset updates: Live

Number of children 6-59 months admitted for TREATMENT OF SEVERE ACUTE MALNUTRITION (SAM) by country

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Climate Change Opinion Survey

Data for Good at Meta

4800+ Downloads

Time Period of the Dataset [?]: February 17, 2021-June 28, 2022 ... More

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.

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Movement Range Maps

Data for Good at Meta

55000+ Downloads

Time Period of the Dataset [?]: March 01, 2020-May 24, 2022 ... More

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/

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Survey on Gender Equality At Home

Data for Good at Meta

4600+ Downloads

Time Period of the Dataset [?]: September 21, 2020-January 14, 2022 ... More

This dataset updates: As needed

This data contains aggregated weighted statistics at the regional level by gender for the 2020 Survey on Gender Equality At Home as well as the country and regional level for the 2021 wave. The Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. Researchers and nonprofits interested in access to survey microdata can apply at: https://dataforgood.facebook.com/dfg/tools/survey-on-gender-equality-at-home

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Current IATI aid activities in Serbia

International Aid Transparency Initiative

Time Period of the Dataset [?]: January 01, 2019-December 08, 2024 ... More

This dataset updates: Live

This dataset is part of the data series [?]: IATI - Current IATI aid activities

Live list of active aid activities for Serbia shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from http://www.d-portal.org Definitions for the geographical-precision codes are available at https://iatistandard.org/en/iati-standard/203/codelists/geographicalprecision/ Definitions for the geographical-precision codes are available at https://iatistandard.org/en/iati-standard/203/codelists/geographicalprecision/

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