• Updated Live | Dataset date: December 01, 2019-November 26, 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.
    9300+ Downloads
    This dataset updates: Live
  • Updated 26 November 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)
    6400+ Downloads
    This dataset updates: Every day
  • Updated 26 November 2022 | Dataset date: November 26, 2022-November 26, 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 26 November 2022 | Dataset date: November 26, 2022-November 26, 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.
    5700+ Downloads
    This dataset updates: Every day
  • Updated 26 November 2022 | Dataset date: November 26, 2022-November 26, 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.
    6200+ Downloads
    This dataset updates: Every day
  • Updated 26 November 2022 | Dataset date: September 25, 2017-September 30, 2022
    Missing Migrants Project draws on a range of sources to track deaths of migrants along migratory routes across the globe. Data from this project are published in the report “Fatal Journeys: Tracking Lives Lost during Migration,” which provides the most comprehensive global tally of migrant fatalities for 2014, and estimates deaths over the past 15 years.
    800+ Downloads
    This dataset updates: Never
  • Updated 26 November 2022 | Dataset date: December 14, 2021-December 14, 2021
    Topline figures dataset for the Central Emergency Response Fund's organisation page
    70+ Downloads
    This dataset updates: Every week
  • Updated 26 November 2022 | Dataset date: January 01, 2019-November 26, 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
  • Updated 25 November 2022 | Dataset date: August 01, 2022-July 31, 2023
    Global Acute Malnutrition (GAM) is the presence of both moderate acute malnutrition (MAM) and severe acute malnutrition (SAM) in a population. Height and body weight ratios are measured for children between 6 months and 5 years old to determine the prevalence of malnutrition. Rates above 15 per cent are ordinarily considered an emergency but rates above 30 per cent contribute to the case for famine in a given area.
    300+ Downloads
    This dataset updates: Every year
  • Updated 25 November 2022 | Dataset date: November 25, 2022-November 26, 2022
    La metodología para el cálculo de personas en necesidad -PiN- intersectorial para el Humanitarian Needs Overview -HNO- 2023 en Colombia, se desarrolló siguiendo la metodología global JIAF (Joint Intersectoral Analysis Framework, por sus siglas en inglés) en el que se analizan los eventos o shocks que afectan las condiciones humanitarias en la población a partir de tres pilares: i Estándares de vida, ii Mecanismos para afrontar el shock y iii Bienestar Físico y Mental. De manera general encontraran todos los documentos utilizados para la construcción del PiN 2023 y sus desagregaciones.
    This dataset updates: As needed
  • Updated 25 November 2022 | Dataset date: January 01, 2018-November 23, 2023
    Data provides the Humanitarian Country team's shared understanding of the crisis, including the most pressing humanitarian needs, and reflects its joint humanitarian response planning
    2500+ Downloads
    This dataset updates: Every year
  • Updated 25 November 2022 | Dataset date: January 01, 2022-November 26, 2022
    Access constraints for humanitarian intervention in Somalia in the year 2022
    10+ Downloads
    This dataset updates: Every three months
  • Updated 25 November 2022 | Dataset date: January 01, 2022-October 31, 2022
    Drought related data: Population IDPs Affected Population Priority Areas IPC 5 (Oct - Dec 2022 projection) Severity of access
    50+ Downloads
    This dataset updates: As needed
  • Updated 25 November 2022 | Dataset date: November 16, 2021-October 26, 2022
    Road network in Somalia
    100+ Downloads
    This dataset updates: Every year
  • Updated 25 November 2022 | Dataset date: March 01, 2021-September 30, 2022
    The dataset has return location of IDPs & families. Last displacement at Governorates (admin1) level, shelter type and period of last displacement.
    8300+ Downloads
    This dataset updates: Every six months
  • Updated 25 November 2022 | Dataset date: December 29, 2021-November 26, 2022
    Air transport plays an essential role in providing aid and relief during and after a disaster. Airports are important hubs for humanitarian assistance and disaster response. The continued support and influx of goods and supplies is dependent on air transport. During a disaster, airports become staging points for rescuers, relief supplies, goods deliveries, and people evacuation. This data shows the location of name and location of airport type and class in Somalia indicating the status and humanitarian use
    70+ Downloads
    This dataset updates: As needed
  • Updated 25 November 2022 | Dataset date: July 20, 2022-September 18, 2022
    The 2022 Multi-Sectoral Needs Assessment (MSNA), conducted by the REACH Initiative in close collaboration with the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) and mandated by the Inter-cluster Coordination Group (ICCG), aims to understand the multi-sectoral and sector-specific needs, circumstances, and vulnerabilities of households across the entire territory of the Central African Republic. It also aims to understand specific needs and vulnerabilities of population groups, namely non-displaced households, returnees, internally displaced persons (IDPs) living in host communities, and IDPs living at sites. The needs assessment covers protection, health, mental health, WASH, Shelter and NFI, Education, food security, livelihoods and disabilities, as well as the perception of and satisfaction with humanitarian aid (AAP). The 2022 MSNA was conducted through a statistically representative household survey across 66 accessible sub-prefectures (admin2) out of the 72 sub-prefectures of the country. The inaccessible sub-prefectures were evaluated using a Key Informant survey. In consultation with key humanitarian partners and actors, a joint set of indicators, questions, and answer choices were developed for the assessment of needs in the context of the Central African Republic. All surveys were conducted through face-to-face interviews, using the tablet-based Kobo Collect Open Data Kit (ODK) app. Household data collection took place from July 20 to September 18, 2022. A total of 12,347 households were assessed after data cleaning. Data is statistically representative at a 92% confidence level and a +/- 10% margin of error with a buffer of 10% for the entire population on the level of sub-prefectures (admin2) and higher levels, and for specific population groups on the level of prefectures (admin1) and higher levels.
    This dataset updates: As needed
  • Updated 25 November 2022 | Dataset date: July 20, 2022-September 18, 2022
    The 2022 Multi-Sectoral Needs Assessment (MSNA), conducted by the REACH Initiative in close collaboration with the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) and mandated by the Inter-cluster Coordination Group (ICCG), aims to understand the multi-sectoral and sector-specific needs, circumstances, and vulnerabilities of households across the entire territory of the Central African Republic. It also aims to understand specific needs and vulnerabilities of population groups, namely non-displaced households, returnees, internally displaced persons (IDPs) living in host communities, and IDPs living at sites. The needs assessment covers protection, health, mental health, WASH, Shelter and NFI, Education, food security, livelihoods and disabilities, as well as the perception of and satisfaction with humanitarian aid (AAP). The 2022 MSNA was conducted through a statistically representative household survey across 66 accessible sub-prefectures (admin2) out of the 72 sub-prefectures of the country. The inaccessible sub-prefectures were evaluated using a Key Informant survey. In consultation with key humanitarian partners and actors, a joint set of indicators, questions, and answer choices were developed for the assessment of needs in the context of the Central African Republic. All surveys were conducted through face-to-face interviews, using the tablet-based Kobo Collect Open Data Kit (ODK) app. Household data collection took place from July 20 to September 18, 2022. A total of 12,347 households were assessed after data cleaning. Data is statistically representative at a 92% confidence level and a +/- 10% margin of error with a buffer of 10% for the entire population on the level of sub-prefectures (admin2) and higher levels, and for specific population groups on the level of prefectures (admin1) and higher levels.
    This data is by request only
  • Updated 25 November 2022 | Dataset date: October 01, 2022-November 26, 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). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations.
    This dataset updates: Every three months
  • Updated 25 November 2022 | Dataset date: October 16, 2022-November 26, 2022
    Google spreadsheet containing amount of cargo shipped under the Black Sea Grain Initiative broken down by destination countries, type of cargo and UN income group.
    80+ Downloads
    This dataset updates: Every day
  • Updated 25 November 2022 | Dataset date: March 03, 2022-November 26, 2022
    Key Figures extracted from Ukraine Flash Appeal, FTS and the daily Situation Reports.
    1000+ Downloads
    This dataset updates: Every day
  • Updated 25 November 2022 | Dataset date: March 16, 2020-November 24, 2022
    This data has been collected from various sources and is displayed in this online dashboard: https://geonode.wfp.org/travel Mobile version: https://geonode.wfp.org/travel_mobile The data is divided in two datasets: COVID-19 restrictions by country: This dataset shows current travel restrictions. Information is collected from various sources: IATA, media, national sources, WFP internal or any other. COVID-19 airline restrictions information: This dataset shows restrictions taken by individual airlines or country. Information is collected again from various sources including WFP internal and public sources. The data displayed is a collaborative effort and anybody with more accurate/updated information is highly encouraged to contact WFP GIS unit for Emergencies at the following email address: hq.gis@wfp.org
    10000+ Downloads
    This dataset updates: Every day
  • Updated 25 November 2022 | Dataset date: August 03, 2022-November 23, 2022
    This dataset contains the list of voyages completed under the Black Sea Grain Initiative since 3 August 2022.
    2700+ Downloads
    This dataset updates: Every day
  • Updated 25 November 2022 | Dataset date: December 08, 2021-November 26, 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.
    5900+ Downloads
    This dataset updates: Every day
  • Updated 24 November 2022 | Dataset date: January 01, 2017-October 20, 2022
    These datasets contain information on violent and threatening incidents affecting aid operations, education, health care, refugees and IDPs, and publicly-reported cases of sexual violence by law enforcement bodies, conflict actors, conflict-related sexual violence, and sexual violence that targets IDPs/refugees or vulnerable beneficiaries in Ethiopia to ensure staff safety and better response outcomes.
    2300+ Downloads
    This dataset updates: As needed