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  • 50+ Downloads
    Time Period of the Dataset [?]: July 10, 2023-November 01, 2023 ... More
    Modified [?]: 31 October 2023
    Dataset Added on HDX [?]: 30 June 2022
    This dataset updates: As needed
    This dataset is part of the data series [?]: Kontur - Population Density for 400m H3 Hexagons
    Uzbekistan 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.
  • 1700+ Downloads
    Time Period of the Dataset [?]: December 14, 2020-November 09, 2023 ... More
    Modified [?]: 29 October 2023
    Dataset Added on HDX [?]: 27 May 2020
    This dataset updates: Live
    Immunization campaigns impacted due to COVID-19
  • 100+ Downloads
    Time Period of the Dataset [?]: January 01, 2009-December 31, 2022 ... More
    Modified [?]: 20 September 2023
    Dataset Added on HDX [?]: 4 September 2017
    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 (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) 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.
  • 90+ Downloads
    Time Period of the Dataset [?]: May 19, 2020-May 19, 2020 ... More
    Modified [?]: 21 August 2023
    Dataset Added on HDX [?]: 27 May 2020
    This dataset updates: As needed
    Pool fund Extended allocation Details
  • 50+ Downloads
    Time Period of the Dataset [?]: April 07, 2022-April 07, 2022 ... More
    Modified [?]: 10 July 2023
    Dataset Added on HDX [?]: 16 April 2022
    This dataset updates: As needed
    This dataset is part of the data series [?]: Kontur - Administrative Division with Aggregated Population
    Uzbekistan 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
  • COD 1000+ Downloads
    Time Period of the Dataset [?]: January 01, 2018-December 31, 2018 ... More
    Modified [?]: 30 June 2023
    Dataset Added on HDX [?]: 12 July 2018
    This dataset updates: Every year
    This dataset is part of the data series [?]: COD - Subnational Population Statistics
    Uzbekistan administrative level 0 (country) and 1 (province / viloyat, autonomous republic / respublika, or independent city / shahar) population statistics and level 0,1, and 2 (district / tuman) gazetteer. REFERENCE YEAR: 2018 The administrative level 1 CSV table is suitable for database or GIS linkage to the administrative level 1 shapefile available on HDX here. REVISION HISTORY: 22 July 2019 2018 population statistics update 12 July 2018 Initial upload
  • 90+ Downloads
    Time Period of the Dataset [?]: May 19, 2017-March 28, 2024 ... More
    Modified [?]: 24 May 2023
    Dataset Added on HDX [?]: 13 September 2018
    This dataset updates: Never
    This dataset is part of the data series [?]: INFORM Models
    The sub national INFORM model for Caucasus and Central Asia was initiated by the Regional Inter-Agency Standing Committee (IASC) Task Force for Caucasus and Central Asia and is managed by OCHA. The INFORM model is being used to support coordinated preparedness actions. Partners hope to use the model to improve cooperation between humanitarian and development actors in managing risk and building resilience across the region.
  • 10+ Downloads
    Time Period of the Dataset [?]: January 01, 1997-December 31, 2010 ... More
    Modified [?]: 26 April 2023
    Dataset Added on HDX [?]: 13 March 2023
    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.
  • 21000+ Downloads
    Time Period of the Dataset [?]: April 01, 2021-March 28, 2024 ... More
    Modified [?]: 17 February 2023
    Dataset Added on HDX [?]: 8 April 2021
    This dataset updates: As needed
    The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. The data is provided for 93 low and middle-income countries at 2.4km resolution. 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/
  • 600+ Downloads
    Time Period of the Dataset [?]: January 01, 1970-December 31, 2019 ... More
    Modified [?]: 21 December 2022
    Dataset Added on HDX [?]: 22 September 2019
    This dataset updates: Every three months
    This dataset is part of the data series [?]: UNESCO - Education Indicators
    Education indicators for Uzbekistan. Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: SDG 4 Global and Thematic (made 2022 September), Other Policy Relevant Indicators (made 2022 September), Demographic and Socio-economic (made 2022 September)
  • 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
    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.
  • 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
    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/
  • 100+ Downloads
    Time Period of the Dataset [?]: December 31, 2021-December 31, 2021 ... More
    Modified [?]: 10 March 2022
    Dataset Added on HDX [?]: 10 March 2022
    This dataset updates: Every year
    The INFORM subnational model for Caucasus and Central Asia was updated by CESDRR in collaboration with UNDRR and with financial support from USAID BHA in September 2021. The model developed by OCHA and EC’s Joint Research Center for the Regional Inter-Agency Standing Committee (RIASC) Task Force for Caucasus and Central Asia in April 2017. The INFORM model is being used to support coordinated preparedness actions. Partners hope to use the model to improve cooperation between humanitarian and development actors in managing risk and building resilience across the region. INFORM identifies areas at a high risk of humanitarian crisis that are more likely to require international assistance. The INFORM model is based on risk concepts published in scientific literature and envisages three dimensions of risk: Hazards & Exposure, Vulnerability and Lack of Coping Capacity. The INFORM model is split into different levels to provide a quick overview of the underlying factors leading to humanitarian risk. The INFORM subnational model for Caucasus and Central Asia is developed at the first administrative level (corresponding to the provinces/oblasts/regions and few independent cities) of the eight countries in South Caucasus and Central Asia. The INFORM index supports a proactive crisis management framework. It will be helpful for an objective allocation of resources for disaster management as well as for coordinated actions focused on anticipating, mitigating, and preparing for humanitarian emergencies.
  • 4000+ Downloads
    Time Period of the Dataset [?]: September 21, 2020-September 21, 2020 ... More
    Modified [?]: 14 January 2022
    Dataset Added on HDX [?]: 22 September 2020
    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
  • 200+ Downloads
    Time Period of the Dataset [?]: January 01, 2017-December 31, 2020 ... More
    Modified [?]: 6 January 2022
    Dataset Added on HDX [?]: 6 January 2022
    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.
  • Time Period of the Dataset [?]: January 01, 2019-March 28, 2024 ... More
    Modified [?]: 10 November 2021
    Dataset Added on HDX [?]: 14 February 2019
    This dataset updates: Live
    This dataset is part of the data series [?]: IATI - Current IATI aid activities
    Live list of active aid activities for Uzbekistan 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
  • COD 5100+ Downloads
    Time Period of the Dataset [?]: July 12, 2018-March 28, 2024 ... More
    Modified [?]: 29 September 2021
    Dataset Added on HDX [?]: 12 July 2018
    This dataset updates: Every year
    This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries
    Uzbekistan administrative level 0 (country), 1 (province / viloyat, autonomous republic / respublika, or independent city / shahar), and 2 (district / tuman) boundary polygon and line shapefiles, and gazetteer. 27 May 2020 update: A topology error affecting all levels was corrected in the shapefiles only. The administrative level 1 shapefile is suitable for database or GIS linkage to the administrative level 1 population statistics table available on HDX here.
  • 600+ Downloads
    Time Period of the Dataset [?]: November 14, 2020-May 17, 2021 ... More
    Modified [?]: 15 September 2021
    Dataset Added on HDX [?]: 15 June 2021
    This dataset updates: Every month
    Overview The dataset contains harmonized indicators created from high-frequency phone surveys collected by the World Bank and partners. The surveys capture the socioeconomic impacts of the COVID-19 pandemic on households and individuals from all developing regions. Data are available for over 90 indicators in 14 topic areas, including education, food security, income, safety nets, and others. For more information, please refer to our Technical Note and Data Dictionary. Unit of Measure Percentages. Aggregation Method: The data is aggregated by Urban/Rural/National and Industry Sector Disclaimer: This harmonized dataset is an ongoing collation and harmonization of COVID-19 high-frequency phone survey (HFPS) data. Harmonization involves redefining indicators and categories so that they are comparable across countries. As a result, even if the names and definitions of indicators appear similar, numbers in this global database might differ slightly from those of each country's publications or dashboard. If you see large discrepancies or other issues, please reach out. Version Notes: COVID-19 Harmonized Household Data Feb 18 • Temporarily suppressed select income, labor, and government assistance indicators collected after wave 2 surveys for harmonization review • Added need for, and access to medical care in multiple countries • Temporarily suppressed select income, labor and government assistance indicators collected after wave 2 surveys for harmonization review Funding Name, Abbreviation, Role: The project received support from the Trust Fund for Statistical Capacity Building III (TFSCB-III). TFSCB-III is funded by the United Kingdom’s Foreign, Commonwealth & Development Office, the Department of Foreign Affairs and Trade of Ireland, and the Governments of Canada and Korea. Other Acknowledgments: This dashboard was created by the Data for Goals (D4G) team and the Regional High-Frequency Phone Survey (HFPS) Focal Points in the EFI Poverty and Equity Global Practice (POV GP), under the guidance of POV GP management, using data collected under the World Bank-wide COVID-19 HFPS initiative. Time Periods: March, 2021
  • 300+ Downloads
    Time Period of the Dataset [?]: March 01, 2020-December 31, 2020 ... More
    Modified [?]: 15 April 2021
    Dataset Added on HDX [?]: 15 April 2021
    This dataset updates: Every three months
    Under the leadership of UNDP and DCO, an inter-agency task team developed the UN framework for the immediate socio-economic response to COVID-19 (adopted in April 2020) to govern its response over 12 to 18 months. To measure the UN’s support to the socio-economic response and recovery, UN entities developed a simple monitoring framework with 18 programmatic indicators (endorsed by the UNSDG in July 2020). Lead entities – based on their mandate and comparative advantage – were nominated to lead the development of methodological notes for each indicator and lead the collection of data at the country level. These lead entities reported through the Office of the Resident Coordinators the collective UN results on a quarterly basis through UN Info. All 2020 data was reported by March 2021. This is the UN development system’s first comprehensive attempt at measuring its collective programming contribution and results. These programmatic indicators enabled the UN system to monitor the progress and achievements of UNCT’s collective actions in socio-economic response. In support of the Secretary-General’s call for a "… single, consolidated dashboard to provide up-to-date visibility on [COVID-19] activities and progress across all pillars” all data was published in real time on the COVID-19 data portal, hosted by DCO. The data is disaggregated by geography (rural/urban), sex, age group and at-risk populations -- to measure system-wide results on the socio-economic response to the pandemic, in order to ensure UNDS accountability and transparency for results.
  • 600+ Downloads
    Time Period of the Dataset [?]: December 01, 2020-February 19, 2021 ... More
    Modified [?]: 22 February 2021
    Dataset Added on HDX [?]: 7 December 2020
    This dataset updates: As needed
    The dataset contains 93 harmonized indicators on 14 topics (demographic, food security, education, labor, health..) on households and individuals in 44 countries across all developing regions.
  • 60+ Downloads
    Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More
    Modified [?]: 16 September 2020
    Dataset Added on HDX [?]: 20 July 2017
    This dataset updates: Every year
    This dataset is part of the data series [?]: World Pop - Population Counts
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App. The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively): - Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019) -Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019). -Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets. -Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020. -Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019). Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645
  • 433000+ Downloads
    Time Period of the Dataset [?]: January 22, 2020-March 09, 2023 ... More
    Modified [?]: 28 July 2020
    Dataset Added on HDX [?]: 7 February 2020
    This dataset updates: As needed
    JHU Has Stopped Collecting Data As Of 03/10/2023 After three years of around-the-clock tracking of COVID-19 data from around the world, Johns Hopkins has discontinued the Coronavirus Resource Center’s operations. The site’s two raw data repositories will remain accessible for information collected from 1/22/20 to 3/10/23 on cases, deaths, vaccines, testing and demographics. Novel Corona Virus (COVID-19) epidemiological data since 22 January 2020. The data is compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) from various sources including the World Health Organization (WHO), DXY.cn, BNO News, National Health Commission of the People’s Republic of China (NHC), China CDC (CCDC), Hong Kong Department of Health, Macau Government, Taiwan CDC, US CDC, Government of Canada, Australia Government Department of Health, European Centre for Disease Prevention and Control (ECDC), Ministry of Health Singapore (MOH), and others. JHU CCSE maintains the data on the 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository on Github. Fields available in the data include Province/State, Country/Region, Last Update, Confirmed, Suspected, Recovered, Deaths. On 23/03/2020, a new data structure was released. The current resources for the latest time series data are: time_series_covid19_confirmed_global.csv time_series_covid19_deaths_global.csv time_series_covid19_recovered_global.csv ---DEPRECATION WARNING--- The resources below ceased being updated on 22/03/2020 and were removed on 26/03/2020: time_series_19-covid-Confirmed.csv time_series_19-covid-Deaths.csv time_series_19-covid-Recovered.csv
  • 40+ Downloads
    Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More
    Modified [?]: 22 June 2020
    Dataset Added on HDX [?]: 24 November 2020
    This dataset updates: Every year
    This dataset is part of the data series [?]: WorldPop - Population Density
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674
  • Time Period of the Dataset [?]: January 01, 2008-March 28, 2024 ... More
    Modified [?]: 3 November 2019
    Dataset Added on HDX [?]: 28 April 2014
    This dataset updates: Live
    This dataset is part of the data series [?]: Our Airports - Airports
    List of airports in Uzbekistan, with latitude and longitude. Unverified community data from http://ourairports.com/countries/UZ/
  • 1000+ Downloads
    Time Period of the Dataset [?]: June 19, 2019-June 19, 2019 ... More
    Modified [?]: 21 June 2019
    Dataset Added on HDX [?]: 20 June 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Uzbekistan: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).