• Updated 1 October 2022 | Dataset date: May 31, 2020-May 31, 2020
    Aggregated figures for Natural Disasters in EM-DAT More on the EM-DAT database : ( website / data portal ). Each line corresponds to a given combination of year, country, disaster subtype and reports figures for : number of disasters total number of people affected total number of deaths economic losses (original value and adjusted)
    5800+ Downloads
    This dataset updates: Every day
  • Updated 1 October 2022 | Dataset date: October 01, 2022-October 01, 2022
    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.
    11000+ Downloads
    This dataset updates: Every day
  • Updated 1 October 2022 | Dataset date: March 09, 2022-August 23, 2022
    IOM conducted rapid representative surveys of the general population in Ukraine to gather initial insights into internal displacement and mobility flows, and to assess local needs. While Displacement Tracking Matrix tools are being established, this general population survey will serve as a preliminary source to identify areas with high humanitarian needs and to inform the targeting of response aiming to assist the conflict-affected population. The geographical scope of the survey covers all five macro-regions (West, East, North, Center, South, and the city of Kyiv). The probabilistic sample, representative at macro-region level, was constructed through a random‐digit‐dial (RDD) approach, and 2,000 respondents aged 18 and over were interviewed using the computer assisted telephone interviewing (CATI) method. Those currently outside Ukraine were not interviewed. Population estimates assume that children travel together with their adult guardians. The estimates rely on the UNFPA population data for Ukraine, agreed upon as the common population baseline by the humanitarian community.
    1700+ Downloads
    This dataset updates: Every month
  • Updated 1 October 2022 | Dataset date: January 01, 2017-March 31, 2023
    The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.
    700+ Downloads
    This dataset updates: As needed
  • Updated 1 October 2022 | Dataset date: January 01, 2022-October 01, 2022
    This dataset contains the change in the cost of a food basket in relation to a previous period (Periods of 3 months). The change of the cost of basic food basket is calculated by comparing the seasonally adjusted cost of the food basket with the cost in the reference period (previous quarter or baseline), as percentage change. The change is considered normal when the percentage change is between 0 and 3%, moderate when it is between 3 and 10%, high when it is between 10 and 25%, and severe above 25%. Note that the countries included here only include those monitored by WFP.
    100+ Downloads
    This dataset updates: Every month
  • Updated 1 October 2022 | Dataset date: August 03, 2022-September 30, 2022
    This dataset contains the list of voyages completed under the Black Sea Grain Initiative since 3 August 2022.
    30+ Downloads
    This dataset updates: Every day
  • Updated 1 October 2022 | Dataset date: January 01, 2018-January 01, 2019
    This dataset contains shapefiles for Guinea, Liberia, and Sierra Leone from the OpenStreetMap (OSM) project. Each country has its individual file. The dataset counts with contributions of hundreds of users. This dataset is updated daily. The original dataset can be downloaded from the OSM West Africa Ebola response wiki.
    2000+ Downloads
    This dataset updates: Never
  • Updated Live | Dataset date: December 01, 2019-September 30, 2022
    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 Metabiota at info@metabiota.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 Metabiota’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. Metabiota maintains a database of epidemiological information for over two thousand high-priority infectious disease events. Please contact us (info@metabiota.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 "Metabiota Composite Source" 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, Metabiota compiles multiple sources to generate the most comprehensive view of an outbreak. This compilation is stored in the database under the source name “Metabiota Composite Source.” 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, Metabiota does not incorporate unofficial - including media - sources into the “Metabiota Composite Source” 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 Metabiota shall in no event be liable for any decision taken by the user based on the data made available. Under no circumstances, shall Metabiota 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.
    9000+ Downloads
    This dataset updates: Live
  • Updated 30 September 2022 | Dataset date: January 31, 2016-July 24, 2022
    The dataset contains IDPs individual and households at admin2 level. IOM has been developing a Displacement Tracking Matrix (DTM) since May 2015 aimed at effectively monitoring and evaluating the flows of Burundian IDPs and providing accurate information on the current IDP situation. The DTM in Burundi has been successfully used in 2014, upon the request of the humanitarian community and the GoB when some areas of Bujumbura were flooded, which caused displacement. This tool allowed registering IDPs in four IDP sites and in host families in four locations and identifying their humanitarian needs.
    11000+ Downloads
    This dataset updates: Every three months
  • Updated 30 September 2022 | Dataset date: January 01, 2022-September 29, 2022
    Number of Refugees returning to Afghanistan for the period of 01 January 2022 to 29 September 2022 by district of destination and origin.
    800+ Downloads
    This dataset updates: Every week
  • Between 5 September and 18 September the International Organization for Migration (IOM) conducted an Area Baseline assessment of 994 hromadas* hosting IDPs in 21 oblasts and Kyiv City in order to gather initial trends on the number and precise geographic location of officially recorded internally displaced persons. This routine assessment supports the targeting and provision of humanitarian assistance to the affected population and serves as a key source to identifying oblasts and hromadas hosting high numbers of IDPs. IOM compiled information on more than 3,176,000 in the 21 oblasts (in addition to Kyiv City) covered by Round 12 of DTM Area Baseline.
    100+ Downloads
    This data is by request only
  • 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.
    1000+ Downloads
    This dataset updates: Every month
  • Updated 30 September 2022 | Dataset date: December 27, 2017-October 01, 2022
    Cabo Verde - administrative level 0-2 and island boundaries with level 0-4 and islands gazetteer. The administrative level 0, 1, and island shapefiles are suitable for database or GIS linkage to the Cabo Verde - Subnational Population Statistics using the ADM0, ADM1, and ISL_PCODE items. Note that island feature "SANTA LUZIA" [CV0] is uninhabited and does not have a corresponding COD-PS record. Santa Luiza does not belong to any administrative level 1-4 features and is excluded from the attached gazetteer.
    2900+ Downloads
    This dataset updates: As needed
  • Updated 30 September 2022 | Dataset date: July 13, 2021-October 01, 2022
    Cabo Verde administrative level 0-1 and island sex and age disaggregated 2021 projected population statistics REFERENCE YEAR: 2022 Gazetteer available to administrative level 4 The administrative level 0, 1, and island tables are suitable for database or GIS linkage to the Cabo Verde - Administrative Boundaries administrative level 0, 1, and 2 shapefiles using the ADM0, ADM1, and ISL_PCODE items.
    3000+ Downloads
    This dataset updates: Every year
  • Updated 30 September 2022 | Dataset date: June 01, 2019-August 31, 2022
    The Who Does What Where is a core humanitarian dataset for coordination. This data contains operational presence of humanitarian partners in Chad at admin1 (region) level by cluster.
    2800+ Downloads
    This dataset updates: Every six months
  • Updated 30 September 2022 | Dataset date: November 01, 2016-June 30, 2022
    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).
    6200+ Downloads
    This dataset updates: Every six months
  • Updated 30 September 2022 | Dataset date: August 01, 2019-June 30, 2022
    Ce jeu de données porte sur la présence opérationnelle des partenaires humanitaires par secteur au niveau administratif 2 dans la République Centrafricaine.
    2600+ Downloads
    This dataset updates: Every three months
  • Updated 30 September 2022 | Dataset date: November 01, 2020-September 28, 2022
    This data contains operational presence of humanitarian partners in Cameroon at admin2 level by cluster.
    1500+ Downloads
    This dataset updates: Every six months
  • Updated 30 September 2022 | Dataset date: June 14, 2022-October 01, 2022
    The dataset captures weekly progress updates from UN agencies involved in implementing the Central Emergency Response Fund's (CERF) US$ 15 million Early Action allocation to mitigate the impacts of expected severe floods in Unity State during the 2022 rainy season
    10+ Downloads
    This dataset updates: Every week
  • Updated 30 September 2022 | Dataset date: March 01, 2022-May 21, 2022
    This dataset is part of the Ukraine Data Explorer Consolidated Multi-Purpose Cash (MPC) 4W and 5W data (Who does What, Where) from Ukraine Cash Working Group (CWG), collected from partners involved in the MPC assistance.
    700+ Downloads
    This dataset updates: As needed
  • Updated 30 September 2022 | Dataset date: January 01, 2018-December 01, 2021
    This data includes information about the number of deployments, countries of deployment and duty stations for the years 2018, 2019, 2020 and 2021.
    30+ Downloads
    This dataset updates: Every year
  • Updated 30 September 2022 | Dataset date: March 03, 2022-October 01, 2022
    Key Figures extracted from Ukraine Flash Appeal, FTS and the daily Situation Reports.
    900+ Downloads
    This dataset updates: Every day
  • Updated 30 September 2022 | Dataset date: January 04, 1999-October 01, 2022
    Reference historic FX rates quoted by the European Central Bank (ECB) converted to USD base currency. There are two resources - one with USD as the quote currency (more standard x/USD) and another with USD as the base currency (USD/x). Note that where the rate is 0 or NaN, it means that the currency existed in the past but no longer exists.
    1000+ Downloads
    This dataset updates: Every day
  • Updated 30 September 2022 | Dataset date: December 08, 2021-October 01, 2022
    This dataset contains key figures (topline numbers) on the world's most pressing humanitarian crises. The data, curated by ReliefWeb's editorial team based on its relevance to the humanitarian community, is updated regularly. The description of the files and columns can be found in the additional metadata spreadsheet file.
    5700+ Downloads
    This dataset updates: Every day
  • Updated 30 September 2022 | Dataset date: January 01, 2019-October 01, 2022
    This dataset contains the number of confirmed cases, recoveries and deaths by province due to the Coronavirus pandemic in Afghanistan.
    1400+ Downloads
    This dataset updates: Every day