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  • 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
  • 600+ Downloads
    Time Period of the Dataset [?]: January 01, 2017-December 31, 2017 ... 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 Tajikistan 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
  • 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
  • 10000+ Downloads
    Time Period of the Dataset [?]: January 01, 1990-August 15, 2021 ... More
    Modified [?]: 22 August 2021
    Dataset Added on HDX [?]: 15 April 2015
    This dataset updates: Never
    This no longer updated dataset contains Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
  • Time Period of the Dataset [?]: February 25, 2021-April 02, 2021 ... More
    Modified [?]: 30 June 2021
    Dataset Added on HDX [?]: 4 July 2021
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Post-Distribution Monitoring of Cash-Based Intervention
    THE CBI PDM Household Survey was conducted in Tajikistan between February, to April, 2021. Tajikistan hosts the largest number of refugees in Central Asia, predominantly from neighbouring Afghanistan. While some progress has been achieved in areas such as access to health and education for refugees, livelihoods and self-reliance, though, continue to pose a challenge. As the result of Covid-19, refugees faced a myriad of challenges, including the loss of daily incomes and livelihoods to cover basic needs such as rent, food and health care. For refugees in Tajikistan, who largely rely on daily work, the impact of Covid 19 has been devastating as it has led to widespread unemployment. As a response measure, UNHCR jointly with its NGO partner provided Covid-19 cash assistance to 414 refugee households over the course of six months (July-December 2020). The results from this survey suggest that cash assistance provided as an immediate measure to support vulnerable refugee households during the Covid-19 pandemic has had a positive impact on the lives of the respondents. Cash assistance predominantly has been spent to cover food, medicines and rent costs. UNHCR uses Post-Distribution Monitoring (PDM) as a mechanism to collect refugees' feedback on the quality, sufficiency, utilization and effectiveness of the assistance items they receive. The underlying principle behind the process is linked to accountability, as well as a commitment to improve the quality and relevance of support provided, and related services. UNHCR increasingly uses Cash-Based Interventions (CBIs) as a preferred modality for delivering assistance, offering greater dignity and choice to forcibly displaced and stateless persons in line with UNHCR's core protection mandate. In order to ensure that the cash assistance provided meets the intended programme objectives and that desired outcomes are achieved, UNHCR conducts regular post-distribution and outcome monitoring with a sample or all of refugee recipients.
  • 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.
  • 30+ 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
  • 30+ 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 [?]: 7 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 Tajikistan, with latitude and longitude. Unverified community data from http://ourairports.com/countries/TJ/
  • 100+ Downloads
    Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More
    Modified [?]: 1 November 2018
    Dataset Added on HDX [?]: 27 May 2019
    This dataset updates: Every year
    This dataset is part of the data series [?]: WorldPop - Age and sex structures
    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. A description of the modelling methods used for age and sex structures can be found in Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here. Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020. The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping. 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/WP00646
  • 60+ Downloads
    Time Period of the Dataset [?]: January 01, 1950-December 31, 2050 ... More
    Modified [?]: 28 September 2018
    Dataset Added on HDX [?]: 28 September 2018
    This dataset updates: Every year
    The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.
  • Time Period of the Dataset [?]: January 01, 2014-December 31, 2018 ... More
    Modified [?]: 5 May 2018
    Dataset Added on HDX [?]: 27 May 2019
    This dataset updates: Every year
    This dataset is part of the data series [?]: WorldPop - Pregnancies
    The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of pregnancies to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age, age-specific fertility rates, still births and abortions to map the estimated distributions of pregnancies for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al and James et al.. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Tajikistan 1km Pregnancies. Version 2.0 2015 estimates of numbers of pregnancies per grid square, with national totals adjusted to match national estimates on numbers of pregnancies made by the Guttmacher Institute (http://www.guttmacher.org) DOI: 10.5258/SOTON/WP00633
  • Time Period of the Dataset [?]: January 01, 2014-December 31, 2018 ... More
    Modified [?]: 5 May 2018
    Dataset Added on HDX [?]: 27 May 2019
    This dataset updates: Every year
    This dataset is part of the data series [?]: WorldPop - Births
    The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of live births to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age and age-specific fertility rates to map the estimated distributions of births for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al. and James et al.. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Tajikistan 1km Births. Version 2.0 2015 estimates of numbers of live births per grid square, with national totals adjusted to match UN national estimates on numbers of live births (http://esa.un.org/wpp/). DOI: 10.5258/SOTON/WP00582
  • COD 1200+ Downloads
    Time Period of the Dataset [?]: January 01, 2017-January 01, 2017 ... More
    Modified [?]: 18 May 2017
    Dataset Added on HDX [?]: 12 April 2017
    This dataset updates: As needed
    This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries
    An overview of the administrative divisions for Tajikistan, including their associated names and unique identifiers (according to the OKATO classification system). The overview includes administrative level 1 (Viloyat + independent city) and administrative level 2 (Nohiya + independent cities). Administrative level 3 (Jamoat) has not been included in this overview, as these have recently changed (geographical boundaries, names and OKATO codes) and it has not been possible to verify the most recent overview. OCHA's Regional Office for the Caucasus and Central Asia is maintaining a dataset with the geographical boundaries of administrative levels 1 and 2 for preparedness purposes, but is not allowed to make it public. In case of a major humanitarian emergency, this geographical dataset will be shared with humanitarian agencies.
  • 900+ Downloads
    Time Period of the Dataset [?]: May 13, 2015-May 13, 2015 ... More
    Modified [?]: 24 November 2015
    Dataset Added on HDX [?]: 15 April 2015
    This dataset updates: Every month
    The Food Consumption Score (FCS) dataset is based on the FCS indicator, which assigns a food security score based on food consumption and diets. This data is available sub-nationally for 38 countries, such as Nepal and Sierra Leone.