• Time Period of the Dataset [?]: November 17, 2020-March 28, 2024 ... More
    Modified [?]: 21 March 2024
    Dataset Added on HDX [?]: 17 August 2017
    Nepal administrative level 0-3 boundaries and gazetteer LAYERS UPDATED MARCH 2024. Live services will be updated shortly to correspond Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID. These administrative level 0-2 layers are suitable for database or GIS linkage to the Nepal - Subnational Population Statistics tables using the ADM0, ADM1, and ADM2_PCODE fields. Official site for Nepali boundary information: Ministry of Land Management, Cooperatives and Poverty Alleviation, Survey Department [http://dos.gov.np/downloads/nepal-map] (Unsecure link.)
    COD+ 12000+ Downloads
    This dataset updates: Every year
    This dataset is part of the data series [?]: COD - Subnational Administrative Boundaries
  • Time Period of the Dataset [?]: April 01, 2023-August 31, 2023 ... More
    Modified [?]: 21 March 2024
    Dataset Added on HDX [?]: 21 March 2024
    Information of acute malnutrition by admin 2
    This dataset updates: Every year
  • Time Period of the Dataset [?]: March 02, 2020-March 16, 2024 ... More
    Modified [?]: 21 March 2024
    Dataset Added on HDX [?]: 2 January 2019
    The DTM Emergency Tracking activated on an ad hoc basis. Only Emergency situations which cause significant damage and require an immediate response or cause displacement taken into account.
    2200+ Downloads
    This dataset updates: Every month
    This dataset is part of the data series [?]: IOM - DTM Event and Flow Tracking
  • Time Period of the Dataset [?]: October 01, 2016-March 21, 2024 ... More
    Modified [?]: 21 March 2024
    Dataset Added on HDX [?]: 18 November 2022
    Impact of cyclones (people affected and injured by cyclones) in Mozambique from 2017 to 2024.
    100+ Downloads
    This dataset updates: As needed
  • Time Period of the Dataset [?]: January 20, 1993-September 30, 2024 ... More
    Modified [?]: 21 March 2024
    Dataset Added on HDX [?]: 13 March 2023
    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.
    50+ Downloads
    This dataset updates: Every week
    This dataset is part of the data series [?]: IFRC - Appeals
  • Time Period of the Dataset [?]: January 01, 2011-March 28, 2024 ... More
    Modified [?]: 21 March 2024
    Dataset Added on HDX [?]: 4 October 2022
    Uganda Current Situation FEWS NET Acute Food Insecurity Classifications data since 2011 to 2022.
    20+ Downloads
    This dataset updates: Every month
  • Time Period of the Dataset [?]: March 20, 2024-March 20, 2024 ... More
    Modified [?]: 20 March 2024
    Dataset Added on HDX [?]: 21 March 2024
    UNOSAT code: CE20231007PSE This map illustrates a satellite-imagery based comprehensive assessment of damage and destruction to structures within the area of interest in the Gaza Strip, Occupied Palestinian Territory, based on images collected on 29 February 2024 when compared to images collected on 1 May 2023, 10 May 2023, 18 September 2023, 15 October 2023, 7 November 2023, 26 November 2023, and 6-7 January 2024. According to satellite imagery analysis, UNOSAT identified 31,198 destroyed structures, 16,908 severely damaged structures and 40,762 moderately damaged structures, for a total of 88,868 structures. These correspond to around 35% of the total structures in the Gaza Strip and a total of 121,400 estimated damaged housing units. The governorates of Khan Yunis and Gaza have experienced the highest rise in damage, with 12,279 new structures damaged in Khan Yunis and 2,010 in Gaza. Khan Yunis City had the highest number of newly destroyed structures, with 6,663 in total. This is a preliminary analysis and has not yet been validated in the field.
    90+ Downloads
    This dataset updates: Never
  • Time Period of the Dataset [?]: January 01, 1988-December 31, 2015 ... More
    Modified [?]: 20 March 2024
    Dataset Added on HDX [?]: 29 January 2020
    Contains data from the DHS data portal. There is also a dataset containing Zimbabwe - National Demographic and Health Data on HDX. The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries.
    2100+ Downloads
    This dataset updates: Every year
    This dataset is part of the data series [?]: The DHS Program - Subnational Health and Demographic Data
  • Time Period of the Dataset [?]: October 21, 2023-March 20, 2024 ... More
    Modified [?]: 20 March 2024
    Dataset Added on HDX [?]: 23 November 2023
    The dataset provides an overview of the material entry process through Rafah and Kerem Shalom crossings. It gives insight into the progress of supplies and dispatched items as well as the vital manifest details associated with them.
    300+ Downloads
    This dataset updates: Every two weeks
  • Time Period of the Dataset [?]: September 30, 2020-December 31, 2023 ... More
    Modified [?]: 20 March 2024
    Dataset Added on HDX [?]: 29 June 2018
    Cash Based Programming in Somalia. Data are aggregated at admin level 2
    4200+ Downloads
    This dataset updates: Every three months
  • Time Period of the Dataset [?]: January 01, 1997-March 15, 2024 ... More
    Modified [?]: 20 March 2024
    Dataset Added on HDX [?]: 2 December 2021
    A weekly dataset providing the total number of reported civilian targeting events and fatalities broken down by country. Civilian targeting events include violence against civilians events and explosions/remote violence events in which civilians were directly targeted. Note: These are aggregated data files organized by country-year and country-month. To access full event data, please register to use the Data Export Tool and API on the ACLED website.
    700+ Downloads
    This dataset updates: Every week
  • Time Period of the Dataset [?]: January 01, 1997-March 15, 2024 ... More
    Modified [?]: 20 March 2024
    Dataset Added on HDX [?]: 2 December 2021
    A weekly dataset providing the total number of reported political violence events and fatalities broken down by country. Political violence events include ACLED’s battles, violence against civilians, and explosions/remote violence event types, as well as the mob violence sub-event type of the riots event type. Note: These are aggregated data files organized by country-year and country-month. To access full event data, please register to use the Data Export Tool and API on the ACLED website.
    900+ Downloads
    This dataset updates: Every week
  • Time Period of the Dataset [?]: January 01, 1997-March 15, 2024 ... More
    Modified [?]: 20 March 2024
    Dataset Added on HDX [?]: 2 December 2021
    A weekly dataset providing the total number of reported demonstration events broken down by country. Demonstration events include ACLED’s protests and riots event types, with the exception of the mob violence sub-event type of the riots event type. Note: These are aggregated data files organized by country-year and country-month. To access full event data, please register to use the Data Export Tool and API on the ACLED website.
    300+ Downloads
    This dataset updates: Every week
  • Time Period of the Dataset [?]: December 01, 2019-March 12, 2024 ... More
    Modified [?]: 20 March 2024
    Dataset Added on HDX [?]: 27 March 2020
    Data Overview This repository contains spatiotemporal data from many official sources for 2019-Novel Coronavirus beginning 2019 in Hubei, China ("nCoV_2019") You may not use this data for commercial purposes. If there is a need for commercial use of the data, please contact Concentric by Ginkgo, the biosecurity and public health unit of Ginkgo Bioworks ("Concentric”) at help-epi-modeling@ginkgobioworks.com to obtain a commercial use license. The incidence data are in a CSV file format. One row in an incidence file contains a piece of epidemiological data extracted from the specified source. The file contains data from multiple sources at multiple spatial resolutions in cumulative and non-cumulative formats by confirmation status. To select a single time series of case or death data, filter the incidence dataset by source, spatial resolution, location, confirmation status, and cumulative flag. Data are collected, structured, and validated by Concentric’s digital surveillance experts. The data structuring process is designed to produce the most reliable estimates of reported cases and deaths over space and time. The data are cleaned and provided in a uniform format such that information can be compared across multiple sources. Data are collected at the time of publication in the highest geographic and temporal resolutions available in the original report. This repository is intended to provide a single access point for data from a wide range of data sources. Data will be updated periodically with the latest epidemiological data. Concentric maintains a database of epidemiological information for over three thousand high-priority infectious disease events (please note: this database was previously maintained by Metabiota; the team responsible joined Concentric by Ginkgo in August 2022. When using the database, please cite Concentric and refer to this repository). Please contact us (help-epi-modeling@ginkgobioworks.com) if you are interested in licensing the complete dataset. Cumulative vs. Non-Cumulative Incidence Reporting sources provide either cumulative incidence, non-cumulative incidence, or both. If the source only provides a non-cumulative incidence value, the cumulative values are inferred using prior reports from the same source. Use the CUMULATIVE FLAG variable to subset the data to cumulative (TRUE) or non-cumulative (FALSE) values. Case Confirmation Status The incidence datasets include the confirmation status of cases and deaths when this information is provided by the reporting source. Subset the data by the CONFIRMATION_STATUS variable to either TOTAL, CONFIRMED, SUSPECTED, or PROBABLE to obtain the data of your choice. Total incidence values include confirmed, suspected, and probable incidence values. If a source only provides suspected, probable, or confirmed incidence, the total incidence is inferred to be the sum of the provided values. If the report does not specify confirmation status, the value is included in the "total" confirmation status value. The data provided under the "Multisource Fusion" often does not include suspected incidence due to inconsistencies in reporting cases and deaths with this confirmation status. Outcome - Cases vs. Deaths The incidence datasets include cases and deaths. Subset the data to either CASE or DEATH using the OUTCOME variable. It should be noted that deaths are included in case counts. Spatial Resolution Data are provided at multiple spatial resolutions. Data should be subset to a single spatial resolution of interest using the SPATIAL_RESOLUTION variable. Information is included at the finest spatial resolution provided to the original epidemic report. We also aggregate incidence to coarser geographic resolutions. For example, if a source only provides data at the province-level, then province-level data are included in the dataset as well as country-level totals. Users should avoid summing all cases or deaths in a given country for a given date without specifying the SPATIAL_RESOLUTION value. For example, subset the data to SPATIAL_RESOLUTION equal to "AL0” in order to view only the aggregated country level data. There are differences in administrative division naming practices by country. Administrative levels in this dataset are defined using the Google Geolocation API (https://developers.google.com/maps/documentation/geolocation/). For example, the data for the 2019-nCoV from one source provides information for the city of Beijing, which Google Geolocations indicates is a "locality.” Beijing is also the name of the municipality where the city Beijing is located. Thus, the 2019-nCoV dataset includes rows of data for both the city Beijing, as well as the municipality of the same name. If additional cities in the Beijing municipality reported data, those data would be aggregated with the city Beijing data to form the municipality Beijing data. Sources Data sources in this repository were selected to provide comprehensive spatiotemporal data for each outbreak. Data from a specific source can be selected using the SOURCE variable. In addition to the original reporting sources, Concentric compiles multiple sources to generate the most comprehensive view of an outbreak. This compilation is stored in the database under the source name "Multisource Fusion". The purpose of generating this new view of the outbreak is to provide the most accurate and precise spatiotemporal data for the outbreak. At this time, Concentric does not incorporate unofficial - including media - sources into the "Multisource Fusion" dataset. Quality Assurance Data are collected by a team of digital surveillance experts and undergo many quality assurance tests. After data are collected, they are independently verified by at least one additional analyst. The data also pass an automated validation program to ensure data consistency and integrity. NonCommercial Use License Creative Commons License Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0) This is a human-readable summary of the Legal Code. You are free: to Share — to copy, distribute and transmit the work to Remix — to adapt the work Under the following conditions: Attribution — You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). Noncommercial — You may not use this work for commercial purposes. Share Alike — If you alter, transform, or build upon this work, you may distribute the resulting work only under the same or similar license to this one. With the understanding that: Waiver — Any of the above conditions can be waived if you get permission from the copyright holder. Public Domain — Where the work or any of its elements is in the public domain under applicable law, that status is in no way affected by the license. Other Rights — In no way are any of the following rights affected by the license: Your fair dealing or fair use rights, or other applicable copyright exceptions and limitations; The author's moral rights; Rights other persons may have either in the work itself or in how the work is used, such as publicity or privacy rights. Notice — For any reuse or distribution, you must make clear to others the license terms of this work. The best way to do this is with a link to this web page. For details and the full license text, see http://creativecommons.org/licenses/by-nc-sa/3.0/ Liability The information is provided “AS IS” and Concentric makes no representations or warranties, express or implied, of any type whatsoever including, without limitation, title, noninfringement, accuracy, completeness, merchantability, or fitness for any particular purpose. Use of proprietary information shall be at the user’s own risk, and Concentric assumes no liability or obligation to the user as a result of use. Concentric shall in no event be liable for any decision taken by the user based on the data made available. Under no circumstances, shall Concentric be liable for any damages (whatsoever) arising out of the use or inability to use the database. The entire risk arising out of the use of the database remains with the user.
    7300+ Downloads
    This dataset updates: Live
  • Time Period of the Dataset [?]: December 01, 2022-March 28, 2024 ... More
    Modified [?]: 19 March 2024
    Dataset Added on HDX [?]: 11 January 2024
    The Movement Distribution dataset shows the range of movement of people away from the area where they live on a daily basis. These maps are useful for projects focused on transportation, tourism, displacement, and other areas. More info available here: https://dataforgood.facebook.com/dfg/tools/movement-distribution-maps
    400+ Downloads
    This dataset updates: Every month
  • Time Period of the Dataset [?]: February 24, 2022-February 29, 2024 ... More
    Modified [?]: 19 March 2024
    Dataset Added on HDX [?]: 22 April 2022
    The Registered IDP Area Baseline Assessment provides granular data on the number and geographic location of officially registered internally displaced people (IDPs). The data collected for the Area Baseline Assessment Round 33 reflects the up-to-date local administrative register of the IDP population as of 29 February 2024, equivalent to a total of 3,413,472 registered IDPs. Registered IDP figures were collected for 1,098 hromadas (83% of all hromadas covered in Ukrainian government-controlled areas), across 108 raions and 23 oblasts. Data disaggregated by age, sex and disability status were provided for around 83 per cent of the administrative units covered.
    20+ Downloads
    This data is by request only
    This dataset is part of the data series [?]: IOM - DTM Baseline Assessment
  • Time Period of the Dataset [?]: February 24, 2022-February 29, 2024 ... More
    Modified [?]: 19 March 2024
    Dataset Added on HDX [?]: 23 June 2022
    A baseline assessment is a sub-component of mobility tracking. It aims to collect data on IDP, migrant or returnee population presence in a defined administrative area of the country.
    1600+ Downloads
    This dataset updates: Every month
    This dataset is part of the data series [?]: IOM - DTM Baseline Assessment
  • Time Period of the Dataset [?]: January 01, 2024-March 31, 2024 ... More
    Modified [?]: 19 March 2024
    Dataset Added on HDX [?]: 18 March 2024
    Monthly DEEP extracts related to the Sudan Situational Analyses conducted by DFS and iMMAP Inc. They are provided by sector and operational environment themes. DOCX files contain the screenshot of the visuals used as DEEP entries. XLSX files contain links to the screenshots stored in the DEEP platform.
    60+ Downloads
    This dataset updates: Every month
  • Time Period of the Dataset [?]: November 01, 2022-March 13, 2024 ... More
    Modified [?]: 19 March 2024
    Confirmed [?]: 19 March 2024
    Dataset Added on HDX [?]: 16 October 2023
    The dataset contains numbers of internally displaced individuals and returnees at admin 2 level (Territories) in North Kivu province. Since November 2021, attacks by the former rebel group M 23 have resumed and increased against the congolese armed forces (FARDC) in the east of the DRC. These clashes have further intensified since March 2022, due to which the M23 seized in June 2022 the town of Bunagana located on the border with Uganda, as well as other neighboring localities in the regions of Jomba, Bweza, Kisigari and Busanza in Rutshuru territory. At the end of October 2022, the M23 extended their hold after several offensives, expanding their control over the entire Bwisha chiefdom including the territorial capital and the town of Kiwanja, with alleged plans to extend over the entire territory
    300+ Downloads
    This dataset updates: Every three months
  • Time Period of the Dataset [?]: November 01, 2019-December 31, 2023 ... More
    Modified [?]: 19 March 2024
    Dataset Added on HDX [?]: 1 October 2019
    La Présence Opérationnelle (3W) est un ensemble de données pour la coordination humanitaire. Il est essentiel de savoir où les organisations humanitaires travaillent, ce qu'elles font et leurs capacités afin d'identifier les lacunes, d'éviter la duplication des efforts et de planifier une future réponse humanitaire. Cet ensemble de données comprend une liste des organisations humanitaires opérant au Burkina Faso au niveau Admin 3.
    2000+ Downloads
    This dataset updates: Every six months
  • Time Period of the Dataset [?]: October 01, 2023-December 31, 2023 ... More
    Modified [?]: 19 March 2024
    Dataset Added on HDX [?]: 19 March 2024
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
    This dataset updates: Never
  • Time Period of the Dataset [?]: January 01, 1997-March 31, 2029 ... More
    Modified [?]: 19 March 2024
    Dataset Added on HDX [?]: 17 October 2023
    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.
    10+ Downloads
    This dataset updates: Every week
    This dataset is part of the data series [?]: IFRC - Appeals
  • Time Period of the Dataset [?]: March 19, 2024-March 19, 2024 ... More
    Modified [?]: 19 March 2024
    Dataset Added on HDX [?]: 22 September 2017
    OpenStreetMap contains roughly 7.9 million buildings in this region. Based on AI-mapped estimates, this is approximately 88% of the total buildings.The average age of data for this region is 2 years ( Last edited 5 days ago ) and 2% buildings were added or updated in the last 6 months. Read about what this summary means : indicators , metrics OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['building'] IS NOT NULL Features may have these attributes: name name:en building building:levels building:materials addr:full addr:housenumber addr:street addr:city office source name:ne This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
    300+ Downloads
    This dataset updates: Every day
    This dataset is part of the data series [?]: HOTOSM - Buildings
  • Time Period of the Dataset [?]: March 19, 2024-March 19, 2024 ... More
    Modified [?]: 19 March 2024
    Dataset Added on HDX [?]: 21 July 2017
    FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's Financial Tracking Service, is encoded as utf-8 and the second row of the CSV contains HXL tags.
    900+ Downloads
    This dataset updates: Every day
    This dataset is part of the data series [?]: OCHA FTS - Requirements and Funding Data
  • Time Period of the Dataset [?]: October 01, 2022-March 28, 2024 ... More
    Modified [?]: 19 March 2024
    Dataset Added on HDX [?]: 24 May 2023
    ACAPS Information Landscape Dataset is a repository of data on the information landscape (or ‘information ecosystem’) in humanitarian settings, tracking the events and trends that affect the way information is handled, circulated and received by people affected in crisis settings. It aims to inform the users about: information disorders (disinformation, misinformation, malinformation) vulnerability of specific groups within the context / safety and dignity of people accessing information (stigma trends, hate-speech) access to information (telecommunication infrastructures damage or limitation, accurate information access, information trust and literacy, digital literacy) information freedom and security (journalist safety, censorship, digital security, communication shutdown and restrinctions) The dataset aims to inform humanitarian actors and analyst, on how to handle information and how to approach the information coming from specific context, to provide some useful insights on how to communicate in specific context, both publicly and with population affected, and how the population receives information. The framework was develop by a partnership between ACAPS and Internews.
    60+ Downloads
    This dataset updates: Every month