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  • 2900+ Downloads
    Updated 4 March 2021 | Dataset date: January 01, 2014-March 31, 2020
    This dataset updates: Every year
    The Cadre Harmonisé (CH) and Integrated Food Security Phase Classification (IPC) are analytical frameworks which synthesize indicators of food and nutrition security outcomes and the inference of contributing factors into scales and figures representing the nature and severity of crisis and implications for strategic response in food security and nutrition. (Refer to the documents linked as showcases for more information).
  • 4500+ Downloads
    Updated Live | Dataset date: December 01, 2019-March 04, 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.
  • 300+ Downloads
    Updated 4 March 2021 | Dataset date: January 01, 2020-December 31, 2020
    This dataset updates: Every three months
    The data set contains the people in need, people targeted and people reached by humanitarian assistance in Sudan during the period January-December 2020
  • 20+ Downloads
    Updated 4 March 2021 | Dataset date: May 18, 2020-March 04, 2021
    This dataset updates: Every day
    Contains data crowdsourced daily from Venezuelans using the Premise Data mobile application. The data collected allows the fast measurement of Household Dietary Diversity Score (HDDS), with the goal of providing context around the food security in vulnerable communities. More relevant information below: The booklet included HERE goes into more details on how Premise's crowdsourcing works We offer a more granular version of this dataset by request HERE
  • 6400+ Downloads
    Updated 4 March 2021 | Dataset date: March 10, 2020-March 03, 2021
    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
  • 700+ Downloads
    Updated 4 March 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)
  • Updated Live | Dataset date: January 01, 2019-March 04, 2021
    This dataset updates: Live
    Live list of active aid activities for Equatorial Guinea shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from http://www.d-portal.org
  • Updated Live | Dataset date: January 01, 2019-January 01, 2020
    This dataset updates: Live
    Live list of active aid activities for Fiji shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from http://www.d-portal.org
  • 100+ Downloads
    Updated 4 March 2021 | Dataset date: December 14, 2020-March 02, 2021
    This dataset updates: Every day
    This dataset contains the number of confirmed cases, recoveries and deaths by Governorate due to the Coronavirus pandemic in Palestine.
  • 30+ Downloads
    Updated Live | Dataset date: November 16, 2015-March 04, 2021
    This dataset updates: Live
    List of aid activities by InterAction members in South Sudan. Source: http://ngoaidmap.org/location/gn_7909807
  • 100+ Downloads
    Updated Live | Dataset date: May 01, 2019-December 31, 2020
    This dataset updates: Live
    This dataset combines two sources of education-insecurity data: Machine-learning-driven counts of tweets from Africa and the Middle East on the topic of education insecurity—in Arabic, English, and French—via the Artificial Intelligence for Disaster Response (AIDR) project Human-curated reports of actual education-insecurity events in Africa and the Middle East, via the Armed Conflict Location & Event Data (ACLED) project.
  • Updated 4 March 2021 | Dataset date: October 20, 2020-October 20, 2020
    This dataset updates: As needed
    Tracking water pollution, Sweden. Conducted with Crowddroning by GLOBHE. More maps and data available on demand upon request from locations globally at: https://globhe.com/drone-data-request MORE CROWDDRONING BY GLOBHE Webb: https://globhe.com/ Facebook: https://www.facebook.com/Crowddroning Twitter: https://twitter.com/globhedrones Instagram: https://www.instagram.com/globhedrones/ LinkedIn: https://www.linkedin.com/company/globhedrones/
  • 1900+ Downloads
    Updated 4 March 2021 | Dataset date: October 22, 2019-October 22, 2019
    This dataset updates: As needed
    On 1 August 2018, the Ministry of Health of the Democratic Republic of the Congo declared a new outbreak of Ebola virus disease in North Kivu Province. The Ministry of Health, WHO and partners are responding to this event, and working to establish the full extent of this outbreak. Numbers may fluctuate on a daily basis due to many factors, including continuing monitoring, investigation and reclassification of cases. Alert and suspected cases (not reported here), are systematically investigated to confirm or exclude Ebola virus disease before inclusion in the case counts or discarded as non-cases. WHO GIS team is supporting the National Health Information System Division (DSNIS) to update the health related geographic data (health zones, areas and health facility structures) and other spatial information such as road, building, school together with the OpenStreetMap community and various partners. To carry out this work, the methodology was decided with local cartographers and together we were able to improve the data locally.
  • 10+ Downloads
    Updated 4 March 2021 | Dataset date: February 08, 2021-March 04, 2021
    This dataset updates: As needed
    Number of children 6-59 months admitted for TREATMENT OF SEVERE ACUTE MALNUTRITION (SAM) by country
  • 60+ Downloads
    Updated 4 March 2021 | Dataset date: November 20, 2020-November 20, 2020
    This dataset updates: As needed
    Data on access constraints, aid workers security, % of affected CERF and CBPF projects combined with the status of Polio vaccination in the HRP countries.
  • 6300+ Downloads
    Updated Live | Dataset date: January 01, 2015-December 31, 2020
    This dataset updates: Live
    This dataset contains agency- and publicly-reported data for events in which an aid worker was killed, kidnapped, or arrested. Categorized by country.
  • 100+ Downloads
    Updated 4 March 2021 | Dataset date: May 29, 2019-May 29, 2019
    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.
  • 3900+ Downloads
    Updated 4 March 2021 | Dataset date: February 23, 2021-February 23, 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.
  • 40+ Downloads
    Updated Live | Dataset date: January 01, 2008-March 04, 2021
    This dataset updates: Live
    List of airports in Madagascar, with latitude and longitude. Unverified community data from http://ourairports.com/countries/MG/
  • 100+ Downloads
    Updated 4 March 2021 | Dataset date: July 29, 2020-November 30, 2020
    This dataset updates: As needed
    The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts. Access the - code repository , including all the source code scripts necessary to run the model. View the - technical documentation and - FAQs explaining how to configure and run the source code in the repository. Download the - methodology paper providing details on model assumptions and the main equations. Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries. Download the - OCHA-Bucky model card created according to the Centre’s Peer Review Framework. The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels.
  • 100+ Downloads
    Updated 4 March 2021 | Dataset date: March 02, 2021-March 02, 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.
  • 10+ Downloads
    Updated 4 March 2021 | Dataset date: July 29, 2020-November 30, 2020
    This dataset updates: As needed
    The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts. Access the - code repository , including all the source code scripts necessary to run the model. View the - technical documentation and - FAQs explaining how to configure and run the source code in the repository. Download the - methodology paper providing details on model assumptions and the main equations. Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries. Download the - OCHA-Bucky model card created according to the Centre’s Peer Review Framework. The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels.
  • 100+ Downloads
    Updated 4 March 2021 | Dataset date: July 29, 2020-September 27, 2020
    This dataset updates: As needed
    The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts. Access the - code repository , including all the source code scripts necessary to run the model. View the - technical documentation and - FAQs explaining how to configure and run the source code in the repository. Download the - methodology paper providing details on model assumptions and the main equations. Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries. Download the - OCHA-Bucky model card created according to the Centre’s Peer Review Framework. The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels.
  • 1100+ Downloads
    Updated 4 March 2021 | Dataset date: November 30, 2020-February 22, 2021
    This dataset updates: Every two weeks
    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
  • 700+ Downloads
    Updated Live | Dataset date: March 13, 2020-January 03, 2021
    This dataset updates: Live
    This dataset contains the number of confirmed cases by state due to the Coronavirus pandemic in Venezuela.