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  • 2600+ Downloads
    Updated 27 October 2021 | Dataset date: May 31, 2020-May 31, 2020
    This dataset updates: Every two weeks
    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
    Updated Live | Dataset date: December 01, 2019-October 26, 2021
    This dataset updates: Live
    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.
  • 8100+ Downloads
    Updated 27 October 2021 | Dataset date: March 10, 2020-October 26, 2021
    This dataset updates: Every day
    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
  • 300+ Downloads
    Updated 26 October 2021 | Dataset date: January 04, 1999-October 27, 2021
    This dataset updates: Every day
    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.
  • 300+ Downloads
    Updated 24 October 2021 | Dataset date: January 15, 1990-October 15, 2021
    This dataset updates: Every week
    This dataset contains Countries, Commodities and Markets data which comes from the World Food Programme. The volume of data means that the actual Food Prices data is in country level datasets. These cover 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.
  • 70+ Downloads
    Updated 24 October 2021 | Dataset date: October 26, 2021-October 26, 2021
    This dataset updates: Every week
    Topline figures dataset for the Central Emergency Response Fund's organisation page
  • 200+ Downloads
    Updated 24 October 2021 | Dataset date: October 26, 2021-October 26, 2021
    This dataset updates: Every week
    This dataset lists project funding allocations from OCHA's Central Emergency Response Fund (CERF). CERF allocations are made to ensure a rapid response to sudden-onset emergencies or to rapidly deteriorating conditions in an existing emergency and to support humanitarian response activities within an underfunded emergency.
  • 100+ Downloads
    Updated 24 October 2021 | Dataset date: October 20, 2021-October 20, 2021
    This dataset updates: Every week
    This dataset lists all contributions made by donors to the Central Emergency Response Fund (CERF). CERF receives broad support from United Nations Member States, observers, regional governments and international organizations, and the private sector, including corporations, non-governmental organizations and individuals.
  • 4700+ Downloads
    Updated 22 October 2021 | Dataset date: October 21, 2021-October 21, 2021
    This dataset updates: Every day
    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.
  • 35000+ Downloads
    Updated 21 October 2021 | Dataset date: July 01, 2017-October 27, 2021
    This dataset updates: Never
    This is a repository for PDF files that are linked on the OCHA Centre for Humanitarian Data's website, https://centre.humdata.org. Please note that if you wish to access these files, we recommend you use the Resources section of the Centre's website rather than downloading from HDX.
  • 20+ Downloads
    Updated 20 October 2021 | Dataset date: September 01, 2021-October 27, 2021
    This dataset updates: Every day
    This dataset contains World Bank COVID-19 Vaccine financing support, the Gavi COVID-19 Delivery Support (early access), and the GAVI CDS (early access) Disbursed for selected countries.
  • 900+ Downloads
    Updated 19 October 2021 | Dataset date: January 01, 2013-December 31, 2020
    This dataset updates: As needed
    This dataset is extracted from the Global Coalition to Protect Education from Attack (GCPEA)’s flagship report, Education Under Attack. The report is the result of independent research conducted by GCPEA. Generous support for the report was provided by the Education Above All Foundation, the Norwegian Ministry of Foreign Affairs, and an anonymous donor. Columbia University’s Mailman School of Public Health contributed in-kind research support. For more information, visit eua2018.protectingeducation.org or protectingeducation.org.
  • 14000+ Downloads
    Updated 19 October 2021 | Dataset date: October 13, 2021-October 13, 2021
    This dataset updates: As needed
    We use an anonymized snapshot of all active Facebook users and their friendship networks to measure the intensity of connectedness between locations. The Social Connectedness Index (SCI) is a measure of the social connectedness between different geographies. Specifically, it measures the relative probability that two individuals across two locations are friends with each other on Facebook. Details on the underlying data and the construction of the index are provided in the “Facebook Social Connectedness Index - Data Notes.pdf” file. Please also see https://dataforgood.fb.com/ as well as the associated research paper “Social Connectedness: Measurement, Determinants and Effects,” published in the Journal of Economic Perspectives (https://www.aeaweb.org/articles?id=10.1257/jep.32.3.259).
  • 1300+ Downloads
    Updated 19 October 2021 | Dataset date: November 30, 2020-September 28, 2021
    This dataset updates: Every month
    Understanding gender is essential to understanding the risk factors of poor health, early death and health inequities. The COVID-19 outbreak is no different. At this point in the pandemic, we are unable to provide a clear answer to the question of the extent to which sex and gender are influencing the health outcomes of people diagnosed with COVID-19. However, experience and evidence thus far tell us that both sex and gender are important drivers of risk and response to infection and disease. In order to understand the role gender is playing in the COVID-19 outbreak, countries urgently need to begin both collecting and publicly reporting sex-disaggregated data. At a minimum, this should include the number of cases and deaths in men and women. In collaboration with CNN, Global Health 50/50 began compiling publicly available sex-disaggregated data reported by national governments to date and is exploring how gender may be driving the higher proportion of reported deaths in men among confirmed cases so far. For more, please visit: http://globalhealth5050.org/covid19
  • 6500+ Downloads
    Updated 19 October 2021 | Dataset date: January 01, 1960-December 31, 2019
    This dataset updates: As needed
    World Bank Indicators of Interest to the COVID-19 Outbreak. This link is to a collection in the World Bank data catalog that contains datasets that may be useful for analysis, response or modelling.
  • 4900+ Downloads
    Updated Live | Dataset date: February 16, 2020-October 31, 2021
    This dataset updates: Live
    The number of children, youth and adults not attending schools or universities because of COVID-19 is soaring. Governments all around the world have closed educational institutions in an attempt to contain the global pandemic. According to UNESCO monitoring, over 100 countries have implemented nationwide closures, impacting over half of world’s student population. Several other countries have implemented localized school closures and, should these closures become nationwide, millions of additional learners will experience education disruption.
  • 5700+ Downloads
    Updated Live | Dataset date: January 01, 2020-October 27, 2021
    This dataset updates: Live
    Governments are taking a wide range of measures in response to the COVID-19 outbreak. The Oxford COVID-19 Government Response Tracker (OxCGRT) aims track and compare government responses to the coronavirus outbreak worldwide rigorously and consistently. The OxCGRT systematically collects information on several different common policy responses governments have taken, scores the stringency of such measures, and aggregates these scores into a common Stringency Index. For more, please visit > https://www.bsg.ox.ac.uk/research/research-projects/oxford-covid-19-government-response-tracker
  • 12000+ Downloads
    Updated Live | Dataset date: January 08, 2020-October 26, 2021
    This dataset updates: Live
    Coronavirus COVID-19 daily new and cumulative cases and deaths by country.
  • 90+ Downloads
    Updated Live | Dataset date: June 01, 2018-October 27, 2021
    This dataset updates: Live
    Subset of the full list of crisis identifiers available at GLIDEnumber.net. OCHA provides these GLIDE numbers for interoperability purposes only, so that partners will know what identifiers we are using internally. Please refer to GLIDEnumber.net for the complete and most up-to-date list.
  • 200+ Downloads
    Updated Live | Dataset date: April 15, 2020-October 27, 2021
    This dataset updates: Live
    Contains Country and Territory names from the United Nations Protocol and Liaison Office (DGACM), UN m49 standard, and ReliefWeb Countries list, together with mappings to related Terms and IDs found in UNTERM, ISO 3166, the humanitarianresponse.info API, and the FTS API. For more information, please visit http://vocabulary.unocha.org/
  • 2700+ Downloads
    Updated Live | Dataset date: December 16, 2020-October 25, 2021
    This dataset updates: Live
    The map and chart below show the number of COVID-19 vaccination doses administered per 100 people within a given population. Note that this does not measure the total number of people that have been vaccinated (which is usually two doses).
  • 100+ Downloads
    Updated Live | Dataset date: September 18, 2019-October 27, 2021
    This dataset updates: Live
    These datasets include the approval projects allocated from CBPFs and the current contributions linked to each pooled fund.
  • 30+ Downloads
    Updated Live | Dataset date: August 09, 2018-August 09, 2018
    This dataset updates: Live
    Active Country based Pooled fund
  • 900+ Downloads
    Updated 5 October 2021 | Dataset date: May 01, 2020-May 01, 2020
    This dataset updates: As needed
    This dataset contains two APIs with daily COVID-19 Trends and Impact Survey data. The University of Maryland API is for accessing global survey data and CMU API is for accessing US survey data.
  • 10+ Downloads
    Updated Live | Dataset date: June 08, 2020-October 27, 2021
    This dataset updates: Live
    The IDMC’s Internal Displacement Updates (IDU) are preliminary estimates of new displacements reported in the last 180 days. The IDU API presents provisional data that is updated on daily basis, according to the availability of data. Curated and validated estimates are published in the Global Internal Displacement Database (GIDD) –See https://www.internaldisplacement.org/database/displacement-data. For a detailed description of methodology please refer to the IDMC GRID methodological annex (https://www.internal-displacement.org/global-report/grid2020/downloads/2020-IDMC-GRID-methodology.pdf) and IDMC’s monitoring guidelines (https://monitoringguidance.wixsite.com/idmc). The IDU dataset contains preliminary estimates of aggregated from diverse publishers or sources. New displacement estimates are provided for three different causes of internal displacement: disasters, conflict and violence, and development projects. The documentation of the API is available at bit.ly/IDU_API_DOC.