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  • 4200+ Downloads
    Updated 21 May 2022 | Dataset date: May 31, 2020-May 31, 2020
    This dataset updates: Every day
    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)
  • 6700+ Downloads
    Updated 21 May 2022 | Dataset date: May 21, 2022-May 21, 2022
    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.
  • 8000+ Downloads
    Updated Live | Dataset date: December 01, 2019-May 20, 2022
    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.
  • 42000+ Downloads
    Updated 20 May 2022 | Dataset date: March 01, 2020-May 21, 2022
    This dataset updates: Every day
    NOTE: We plan to no longer update this dataset after May 24 2022. These data sets are intended to inform researchers and public health experts about how populations are responding to physical distancing measures. In particular, there are two metrics, Change in Movement and Stay Put, that provide a slightly different perspective on movement trends. Change in Movement looks at how much people are moving around and compares it with a baseline period that predates most social distancing measures, while Stay Put looks at the fraction of the population that appear to stay within a small area during an entire day. Full details, including the privacy protections in this data, are available here: https://research.fb.com/blog/2020/06/protecting-privacy-in-facebook-mobility-data-during-the-covid-19-response/
  • 20+ Downloads
    Updated 20 May 2022 | Dataset date: March 01, 2022-May 21, 2022
    This dataset updates: As needed
    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.
  • 1800+ Downloads
    Updated 20 May 2022 | Dataset date: July 11, 2020-July 11, 2020
    This dataset updates: As needed
    This dataset is showing the health boundaries data of the Democratic Republic of Congo.
  • 5300+ Downloads
    Updated 20 May 2022 | Dataset date: February 01, 2014-December 31, 2021
    This dataset updates: Every month
    The Who does What Where is a core humanitarian dataset for coordination. This data contains operational presence of humanitarian partners in South Sudan at Admin 2 level.
  • 7000+ Downloads
    Updated 20 May 2022 | Dataset date: January 01, 2019-October 31, 2021
    This dataset updates: Every month
    This dataset provides information on IDP movements and spontaneous IDP returns estimations on a monthly basis. In each resource, there is a summary table for IDP arrival estimations at the governorate level since January 2016. Each resource also includes a summary table for spontaneous IDP returns estimations at the governorate level since August 2018.
  • 300+ Downloads
    Updated 20 May 2022 | Dataset date: January 01, 2021-May 21, 2022
    This dataset updates: Every month
    At the time of the Global Humanitarian Overview 2022 launch in December 2021, 274 million people need humanitarian assistance and protection. This number means that 1 in 29 people worldwide needs humanitarian assistance – a significant increase from 1 in 33 in 2020 and 1 in 45 in 2019, which were already the highest figures in decades. The UN and partner organizations aim to assist 183 million people most in need across 30 countries and 7 regions and require a total of $ 41 billion to do so.
  • 10000+ Downloads
    Updated 20 May 2022 | Dataset date: May 20, 2022-May 20, 2022
    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.
  • 500+ Downloads
    Updated 19 May 2022 | Dataset date: July 08, 2021-May 21, 2022
    This dataset updates: Every year
    Chile administrative level 0-3 projected 2022 sex and age disaggregated population statistics REFERENCE YEAR: 2022 These tables are suitable for database or GIS linkage to the Chile - Subnational Administrative Boundaries layers using the ADM0, ADM1, ADM2, and ADM3_PCODE fields.
  • 200+ Downloads
    Updated 19 May 2022 | Dataset date: January 01, 2022-May 19, 2022
    This dataset updates: Every week
    Number of Refugees returning to Afghanistan for the period of 01 January 2022 to 19 May 2022 by district of destination and origin.
  • Updated 19 May 2022 | Dataset date: May 19, 2022-May 21, 2022
    This dataset updates: Every year
    Central African Republic administrative level 0-3 and Bangui level 4 gazetteer, shapefiles, geodatabase, and geoservice. These layers are suitable for database or GIS linkage to the Central African Republic - Subnational Population Statistics tables using the ADM0, ADM1, ADM2, and ADM3_PCODE fields. Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
  • 1800+ Downloads
    Updated 18 May 2022 | Dataset date: May 18, 2022-May 21, 2022
    This dataset updates: Every year
    Colombia administrative level 0-2 projected 2022 sex and age disaggregated population statistics REFERENCE YEAR: 2022 These tables are suitable for database or GIS linkage to the Colombia - Subnational Administrative Boundaries layers using the ADM0, ADM1, and ADM2_PCODE fields.
  • Updated 18 May 2022 | Dataset date: January 31, 1995-May 21, 2022
    This dataset updates: Every month
    Somalia Monthly staple food price data collected by FEWS NET since 1995.
  • Updated 18 May 2022 | Dataset date: January 31, 2004-May 21, 2022
    This dataset updates: Every week
    Djibouti Weekly staple food price data collected by FEWS NET since 2004.
  • Updated 18 May 2022 | Dataset date: April 30, 2004-May 21, 2022
    This dataset updates: Every month
    Zimbabwe Monthly staple food price data collected by FEWS NET since 2004.
  • Updated 18 May 2022 | Dataset date: December 18, 2019-May 21, 2022
    This dataset updates: Every week
    Ethiopia Weekly staple food price data collected by FEWS NET since 2019.
  • Updated 18 May 2022 | Dataset date: January 31, 2017-May 21, 2022
    This dataset updates: Every week
    Congo, The Democratic Republic of the Weekly staple food price data collected by FEWS NET since 2017.
  • Updated 18 May 2022 | Dataset date: December 31, 2013-May 21, 2022
    This dataset updates: Every month
    Angola Monthly staple food price data collected by FEWS NET since 2013.
  • Updated 18 May 2022 | Dataset date: April 30, 2004-May 21, 2022
    This dataset updates: Every month
    Zimbabwe Monthly staple food price data collected by FEWS NET since 2004.
  • Updated 18 May 2022 | Dataset date: November 05, 2014-May 21, 2022
    This dataset updates: Every week
    Malawi Weekly staple food price data collected by FEWS NET since 2014.
  • Updated 18 May 2022 | Dataset date: January 04, 2005-May 21, 2022
    This dataset updates: Every week
    Haiti Weekly staple food price data collected by FEWS NET since 2005.
  • Updated 18 May 2022 | Dataset date: January 31, 2002-May 21, 2022
    This dataset updates: Every week
    Mauritania Weekly staple food price data collected by FEWS NET since 2002.
  • Updated 18 May 2022 | Dataset date: January 31, 2005-May 21, 2022
    This dataset updates: Every month
    Kenya Monthly staple food price data collected by FEWS NET since 2005.