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  • 40+ Downloads
    Updated 27 May 2021 | Dataset date: December 01, 2019-March 30, 2020
    This dataset updates: Never
    Multiple causes for displacement, all too often underpinned by violence and persecution, has led to over 800,000 Central Americans fleeing their homes, beginning in 2013. Year after year, there has been an increase in individuals fleeing. This was marked initially by especially large numbers of unaccompanied children, then joined in around 2018 with dramatic increases in families units fleeing Central America. Families are forced to flee together as violent threats and persecution by criminal groups in communities extend beyond individuals to entire family units. Given these shifting dynamics in human mobility in these countries, UNHCR and UNICEF, through the Interdisciplinary Development Consultants, CID Gallup, decided to undertake this study with the aim of understanding and giving visibility to the forced displacement of families that flee northern Central America. In addition, the study also seeks to shed light on the current trends, protection risks and factors associated to the forced displacement and migration of unaccompanied and separated children. For this purpose, Gallup conducted 3,104 surveys, complemented by focus group sessions segmented according to the geography of displacement in the region: country of origin, of transit and of asylum. Additionally, interviews were undertaken with families who were part of large mixed movement "caravans" that left Honduras at the beginning of 2020.
  • 8300+ Downloads
    Updated 6 May 2021 | Dataset date: April 01, 2021-December 06, 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. More details are available here: https://dataforgood.fb.com/tools/relative-wealth-index/ Research publication (preprint) for the Relative Wealth Index is available here: https://arxiv.org/abs/2104.07761 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/
  • 100+ Downloads
    Updated 4 May 2021 | Dataset date: January 01, 1990-December 31, 2030
    This dataset updates: Every year
    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'.
  • 100+ Downloads
    Updated 15 April 2021 | Dataset date: March 01, 2020-December 31, 2020
    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.
  • 100+ Downloads
    Updated Live | Dataset date: February 08, 2021-December 06, 2021
    This dataset updates: Live
    Number of children 6-59 months admitted for TREATMENT OF SEVERE ACUTE MALNUTRITION (SAM) by country
  • 500+ Downloads
    Updated 22 February 2021 | Dataset date: December 01, 2020-February 19, 2021
    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.
  • Updated 26 December 2020 | Dataset date: November 19, 2020-November 19, 2020
    This dataset updates: Never
    UNOSAT code: TC20201116HND This map illustrates satellite-detected surface waters in Atlantida and Yoro Departments of Honduras as observed from a Sentinel-1 image acquired on 18 November 2020 at 05:37 Local time. Within the analyzed area of about 3,000 km2, a total of about 40 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 1,200 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important Note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
  • Updated 26 December 2020 | Dataset date: November 19, 2020-November 19, 2020
    This dataset updates: Never
    UNOSAT code: TC20201116HND This map illustrates satellite-detected surface waters in Colon and Yoro Departments of Honduras as observed from a Sentinel-1 image acquired on 18 November 2020 at 05:37 Local time. Within the analyzed area of about 12,000 km2, a total of about 80 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 4,000 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important Note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
  • 10+ Downloads
    Updated 26 December 2020 | Dataset date: November 25, 2020-November 25, 2020
    This dataset updates: Never
    UNOSAT code: TC20201116HND This map illustrates satellite-detected surface waters in Cortes, Atlantida, and Yoro departments of Honduras as observed from a Sentinel-1 image acquired on 23 November 2020 at 05:45 Local time. Within the analyzed area of about 3,500 km2, a total of about 170 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 35,000 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important Note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
  • Updated 26 December 2020 | Dataset date: November 19, 2020-November 19, 2020
    This dataset updates: Never
    UNOSAT code: TC20201116HND This map illustrates satellite-detected surface waters in Olancho Department of Honduras as observed from a Sentinel-1 image acquired on 18 November 2020 at 05:37 Local time. Within the analyzed area of about 4,400 km2, a total of about 32 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 900 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important Note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
  • 10+ Downloads
    Updated 26 December 2020 | Dataset date: November 20, 2020-November 20, 2020
    This dataset updates: Never
    UNOSAT code: TC20201116HND This map illustrates satellite-detected surface waters in Colon and Yoro Departments of Honduras as observed from a Sentinel-1 image acquired on 18 November 2020 at 18:06 Local time. Within the analyzed area of about 5,200 km2, a total of about 220 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 82,000 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important Note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.
  • Updated 20 December 2020 | Dataset date: November 18, 2020-November 18, 2020
    This dataset updates: Never
    UNOSAT code: TC20201116HND This map illustrates satellite-detected surface waters (cumulative) aggregated using NOAA20-VIIRS in Honduras between 13 and 17 November 2020. Based on Worldpop spatial demographic data, about 140,000 people are exposed or living close to flooded areas. The potentially exposed population is mainly located in the department of Cortes with ~80,000 people, Choluteca with ~23,000 people, and Valle with ~14,000 people. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT
  • 200+ Downloads
    Updated 27 November 2020 | Dataset date: November 16, 2020-November 22, 2020
    This dataset updates: Every six months
    The dataset contains IDPs and it's needs.
  • 1900+ Downloads
    Updated 24 November 2020 | Dataset date: June 12, 2020-December 06, 2021
    This dataset updates: Every year
    Proyecciones de Población del Instituto Nacional de Estadística - INE - por edad y sexo según Departamento y Municipio 2020 REFERENCE YEAR: 2020 These tables are suitable for database or GIS linkage to the Honduras - Subnational Administrative Boundaries. 20 NOVEMBER UPDATE: The gazetteer has been updated to include only administrative level 0-2 to conform to the COD-AB.
  • 3800+ Downloads
    Updated 24 November 2020 | Dataset date: July 01, 2010-July 01, 2010
    This dataset updates: Every year
    Honduras administrative level 0-2 boundaries PLEASE REFER TO THE CAVEATS ABOUT THE ADMINISTRATIVE LEVEL 3 DATA. 24 NOVEMBER UPDATES: Due to the structural inconsistency of the best available administrative level 3 boundary information it has been removed from the standard gazetteer, shapefile, geodatabase, web service, and EMF resources and P-coding of populated places resource. HOWEVER a shapefile and EMF file of the original administrative level 3 boundaries is still included in this dataset. Please see the caveats below for specific information. Note that a [Honduras Open Street Map populated places dataset is available here](https://data.humdata.org/dataset/honduras-open-street-map-populated-places). Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID. These boundaries are suitable for database or GIS linkage to the Honduras - Subnational Population Statistics tables.
  • 20+ Downloads
    Updated 24 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    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
  • 70+ Downloads
    Updated 24 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    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
  • 50+ Downloads
    Updated 13 November 2020 | Dataset date: November 13, 2020-November 13, 2020
    This dataset updates: As needed
    Honduras Open Street Map populated places P-coded to COD-AB SEE CAVEATS Populated Places extracted from Open Street Map (OSM) by MapAction P-coded from the Honduras - Subnational Administrative Boundaries Common Operational Dataset. SEE CAVEATS
  • 80+ Downloads
    Updated Live | Dataset date: November 10, 2020-November 10, 2020
    This dataset updates: Live
    This dataset provides the Web Map Service (WMS) layers described below and a tutorial document for consuming the WMS layers in ArcGIS. Link to overall Geoportal website. Links to specific layers on the Geoportal are embedded below. Albergues (Shelters): Albergues registrados por el Centro de Operaciones de Emergencia Nacional (COEN) de COPECO (Shelters registered by the National Emergency Operations Center (COEN) of COPECO) Datos COVID19 por Departamento (COVID19 Data by Department): Número de casos totales, muertos y recuperados, por Departamento (Number of total cases, dead and recovered, by Department) Eventos_ETA (ETA events): Mapeo de incidentes durante la tormenta ETA (Incident mapping during the ETA storm) Fallas Geologicas Centroamerica (Central America Geological Faults) Incidencias ETA por Municipio (ETA incidents by Municipality): Reporte de las incidencias registradas por el Centro de Operaciones de Emergencia Nacional (COEN) de COPECO, a nivel municipal (Report of incidents registered by the COPECO National Emergency Operations Center (COEN), at the municipal level) Limite Aldeas de Honduras (Honduras village limits) Limite Departamental de Honduras (Departmental Limit of Honduras = Administrative level 2) Limite Municipal de Honduras (Municipal Limit of Honduras = Administrative level 1) Limite Nacional de Honduras (National Boundary of Honduras = Administrative level 0) NOTES ON CODS: The P-coded Common Operational Dataset boundaries for administrative levels 0, 1, and 2 are available at Honduras - Subnational Administrative Boundaries. The accompanying Common Operational Dataset 2020 projected sex and age disaggregated population statistics for administrative level 0, 1, and 2 are available at Honduras - Subnational Population Statistics.
  • 60+ Downloads
    Updated 10 September 2020 | Dataset date: July 08, 2020-July 10, 2021
    This dataset updates: Every year
    This table contains subnational multidimensional poverty data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI 2020 methodology is detailed in Alkire, Kanagaratnam & Suppa (2020).
  • 500+ Downloads
    Updated 9 September 2020 | Dataset date: January 01, 2018-December 31, 2018
    This dataset updates: As needed
    This dataset is compiled from two categories of sources: (a) verified security events submitted to Insecurity Insight by 30 Aid in Danger partner agencies; and (b) publicly reported events identified by Insecurity Insight and published in the Aid in Danger Monthly News Brief. Events are categorised by date, country, type of organisation affected and event category, based on standard definitions.
  • 800+ Downloads
    Updated 9 September 2020 | Dataset date: January 01, 2018-December 31, 2018
    This dataset updates: As needed
    This dataset contains events in which an aid worker was involved in a road safety accident (RSA). Categorized by country.
  • 2800+ Downloads
    Updated 9 August 2020 | Dataset date: March 23, 2020-March 23, 2020
    This dataset updates: Every year
    Listado de centros educativos de Honduras, desagregado por municipios y haciendo diferenciación entre centros educativos rurales y urbanos.
  • 385000+ Downloads
    Updated Live | Dataset date: January 22, 2020-December 05, 2021
    This dataset updates: Live
    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
  • 90+ Downloads
    Updated 12 July 2020 | Dataset date: September 02, 2021-September 02, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: building IS NOT NULL Features may have these attributes: source addr:street building:materials addr:housenumber building office building:levels addr:full name addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.