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  • 900+ Downloads
    Updated Live | Dataset date: Dec 1, 2019-Apr 10, 2020
    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.
  • 40+ Downloads
    Updated April 10, 2020 | Dataset date: Apr 10, 2020
    This dataset updates: Every week
    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
  • 4600+ Downloads
    Updated April 10, 2020 | Dataset date: Sep 26, 2017
    This dataset updates: As needed
    West and Central Africa Administrative boundaries, administrative level 0 to 2. Notice: The boundaries and names shown and the designations used on these shapefiles do not imply official endorsement or acceptance by the United Nations. West and Central Africa settlements with administrative capitals
  • 3800+ Downloads
    Updated April 10, 2020 | Dataset date: Apr 10, 2020
    This dataset updates: Every day
    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.
  • 2900+ Downloads
    Updated April 9, 2020 | Dataset date: Apr 9, 2020
    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.
  • Updated April 9, 2020 | Dataset date: Apr 9, 2020
    This dataset updates: Every day
    This map displays continuously updated data from the USGS Earthquakes and Shakemaps. This map is provided by the Esri Disaster Response Program.
  • 1000+ Downloads
    Updated April 9, 2020 | Dataset date: Mar 10, 2020-Apr 30, 2020
    This dataset updates: Every day
    This data has been collected from various sources and is displayed in this online dashboard: http://arcg.is/uHyuO Mobile version: http://arcg.is/0q8Xfj 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
  • 3900+ Downloads
    Updated April 9, 2020 | Dataset date: Mar 17, 2020
    This dataset updates: As needed
    The #COVID19 Government Measures Dataset puts together all the measures implemented by governments worldwide in response to the Coronavirus pandemic. Data collection includes secondary data review. The researched information available falls into five categories: Social distancing Movement restrictions Public health measures Social and economic measures Lockdowns Each category is broken down into several types of measures. ACAPS consulted government, media, United Nations, and other organisations sources. For any comments, please contact us at info@acaps.org Please note note that some measures together with non-compliance policies may not be recorded and the exact date of implementation may not be accurate in some cases, due to the different way of reporting of the primary data sources we used.
  • 10+ Downloads
    Updated April 9, 2020 | Dataset date: Apr 9, 2020
    This dataset updates: Every day
    This datasets contains information about Cases,Deaths and Recoveries per province due to corona virus pandemic in Indonesia.
  • Updated April 9, 2020 | Dataset date: Apr 9, 2020
    This dataset updates: Every day
    Recent Earthquakes from ArcGIS Online
  • 10+ Downloads
    Updated April 9, 2020 | Dataset date: Apr 9, 2020
    This dataset updates: Every year
    Aruba administrative level 0 (constituent country) and 1 (region) sex and age disaggregated 2010 population statistics
  • Updated April 9, 2020 | Dataset date: Feb 29, 2020
    This dataset updates: Every year
    Refugee population of Sudan by UNHCR
  • Updated April 9, 2020 | Dataset date: Jan 31, 2020
    This dataset updates: Every year
    Returnee population of Sudan through DTM - IOM
  • Updated April 9, 2020 | Dataset date: Feb 29, 2020
    This dataset updates: Every year
    IDP population in Sudan through Displacement Tracking Matrix by IOM
  • Updated April 9, 2020 | Dataset date: Jun 30, 2019
    This dataset updates: As needed
    Health Facilities locations across Darfur (Sudan)
  • Updated April 9, 2020 | Dataset date: Mar 30, 2020
    This dataset updates: As needed
    UNHAS air field locations
  • Updated April 9, 2020 | Dataset date: Mar 30, 2020
    This dataset updates: As needed
    Shape file for Bording crossing points
  • 1100+ Downloads
    Updated April 9, 2020 | Dataset date: Jan 18, 2020-Apr 8, 2020
    This dataset updates: As needed
    'Our World in Data' is compiling COVID-19 testing data over time for many countries around the world. They are adding further data in the coming days as more details become available for other countries. In some cases figures refer to the number of tests, in other cases to the number of individuals who have been tested. Refer to documentation provided here.
  • 1500+ Downloads
    Updated April 9, 2020 | Dataset date: Apr 9, 2020
    This dataset updates: Every year
    Guinea administrative level 0 (country), 1 (region), 2 (prefecture), and 3 (sub-prefecture) population statistics (2018 projection 2018). The .csv files are suitable for database or ArcGIS joins to the shapefiles found on HDX here using the 'AdminX_Pcode_iso2' fields.
  • 100+ Downloads
    Updated April 8, 2020 | Dataset date: Dec 31, 2020
    This dataset updates: Every year
    This dataset contains the people in need by sector and region. The dataset is produced by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners.
  • 200+ Downloads
    Updated Live | Dataset date: Jan 1, 2020-Apr 10, 2020
    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
  • 500+ Downloads
    Updated April 8, 2020 | Dataset date: Jan 1, 2019-Apr 4, 2020
    This dataset updates: Every three months
    DTM’s Displacement Tracking tool collects and reports on displaced numbers of households on a daily basis, allowing for regular reporting of new displacements in terms of numbers, geography and needs. More than 3.6 million people are displaced as per August 2018 assessment.
  • 200+ Downloads
    Updated April 8, 2020 | Dataset date: Jan 1, 2019-Mar 29, 2020
    This dataset updates: Every week
    Données hebdomadaires sur les maladies à potentiel épidémiques au Burkina Faso
  • 700+ Downloads
    Updated April 8, 2020 | Dataset date: Jan 15, 2020-Feb 26, 2020
    This dataset updates: Every three months
    A site assessment is a sub-component of mobility tracking. It aims to collect data on population presence, living conditions and needs in a particular displacement site or community.
  • 1000+ Downloads
    Updated April 8, 2020 | Dataset date: Apr 8, 2020
    This dataset updates: Every year
    Indonesia administrative level 0 (country - negara), 1 (province - provinsi), 2 (city, district, regency - kota, kabupaten), 3 (sub-district - kecamatan, distrik), and 4 (village - desa, kelurahan, kampung, nagari, pekon or gampong) boundaries Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID. Administrative boundaries from level 0 to 4 contain P-codes derived from the Badan Pusat Statistik (BPS - Statistics Indonesia).