Refine your search: Clear all
Featured:
Locations:
More
Formats:
More
Organisations:
More
Tags:
More
Licenses:
More
  • 6400+ Downloads
    Updated Live | Dataset date: December 01, 2019-October 20, 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.
  • 8000+ Downloads
    Updated 21 October 2021 | Dataset date: March 10, 2020-October 19, 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
  • 2300+ Downloads
    Updated 20 October 2021 | Dataset date: October 15, 2020-October 21, 2021
    This dataset updates: Every week
    This bucket contains FAIR COVID-19 US county level forecast data
  • 20+ Downloads
    Updated 19 October 2021 | Dataset date: October 18, 2021-October 18, 2021
    This dataset updates: Every month
    Données de base ou d'intérêt pour le secteur de la santé, extraites de la base de données OpenStreetMap, pour la province du Nord-Kivu. Ce dossier reprend actuellement des données publiées dans un contexte de formation et révision.
  • 300+ Downloads
    Updated 18 October 2021 | Dataset date: January 01, 2020-October 21, 2021
    This dataset updates: Every week
    English Description - The following contains weekly operational data of hospitals in Venezuela, inventory of health supplies, administrative entity, geographic location and type of hospital. The collection of this data is a crowdsource effort under a survey template that provides an image of the current situation of hospitals in Venezuela Descripción en Español - Esta data contiene data semanal de las operaciones en los hospitales de Venezuela, inventario de suministro de salud, gerencia del hospital, zona geográfica y el tipo de hospital. El método de recolección de esta data es a través de múltiples fuentes voluntarias en el terreno en una encuesta estandarizada. La encuesta tiene como objetivo mostrar la situación actual de hospitales en Venezuela.
  • 1100+ Downloads
    Updated 14 October 2021 | Dataset date: June 19, 2019-June 19, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Papua New Guinea: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 2800+ Downloads
    Updated 13 October 2021 | Dataset date: August 03, 2021-October 21, 2021
    This dataset updates: As needed
    Chile administrative level 0-3 boundary files Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID. These boundaries are suitable for database or GIS linkage to the Chile - Subnational Population Statistics.
  • 3200+ Downloads
    Updated 13 October 2021 | Dataset date: June 19, 2019-June 19, 2019
    This dataset updates: As needed
    VERSION 1.5. The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Indonesia: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 2900+ Downloads
    Updated 12 October 2021 | Dataset date: May 20, 2019-May 20, 2019
    This dataset updates: As needed
    VERSION 1.5. The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Nigeria: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49). There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.
  • 1500+ Downloads
    Updated 12 October 2021 | Dataset date: May 20, 2019-May 20, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Zambia: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1400+ Downloads
    Updated 12 October 2021 | Dataset date: May 20, 2019-May 20, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Madagascar: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 2400+ Downloads
    Updated 12 October 2021 | Dataset date: June 19, 2019-June 19, 2019
    This dataset updates: As needed
    VERSION 1.5. The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Bangladesh : (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1800+ Downloads
    Updated 12 October 2021 | Dataset date: May 20, 2019-May 20, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in the Democratic Republic of Congo: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1400+ Downloads
    Updated 12 October 2021 | Dataset date: May 20, 2019-May 20, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Angola: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 10+ Downloads
    Updated 12 October 2021 | Dataset date: October 12, 2021-October 12, 2021
    This dataset updates: As needed
    Limites de la République Démocratique du Congo et de 20 pays avoisinants, extraites de la base de données OpenStreetMap et mises à disposition pour faciliter la cartographie.
  • 50+ Downloads
    Updated 11 October 2021 | Dataset date: October 10, 2021-October 10, 2021
    This dataset updates: Every week
    Données de base ou d'intérêt pour le secteur de la santé, extraites de la base de données OpenStreetMap et converties suivant le schéma attributaire du Référentiel Géographique Commun de la RDC dans la mesure du possible. Cette page inclut actuellement les limites des cellules d'animation communautaire et une sélection de points d'intérêt localisés dans l'aire de santé Butsili. Les données étant en cours de mise à jour, elles sont donc susceptibles de connaître des modifications fréquentes. Elles sont publiées en version provisoire avec l'accord de la zone de santé en raison de la résurgence de la maladie à virus Ebola dans la région.
  • 10+ Downloads
    Updated 9 October 2021 | Dataset date: October 09, 2021-October 09, 2021
    This dataset updates: Every week
    Données de base ou d'intérêt pour le secteur de la santé, extraites de la base de données OpenStreetMap et converties suivant le schéma attributaire du Référentiel Géographique Commun de la RDC. Ce dossier reprend actuellement des données en cours de mise à jour, elles sont donc susceptibles de connaître des modifications fréquentes. Elles sont publiées en version provisoire avec l'accord de la zone de santé en raison de la résurgence de la maladie à virus Ebola dans la région.
  • 300+ Downloads
    Updated 8 October 2021 | Dataset date: August 18, 2021-October 21, 2021
    This dataset updates: Every two weeks
    This bi-weekly dataset provides an overview of the latest areas of control in Yemen and includes a map, excel spreadsheet and GIS layer. All datasets are fully PCODED to Admin 2 district level, enabling interoperability with other datasets. Through understanding the latest areas of control, it is possible to enhance analysis in areas such as political-economy through adjusting tools to take into account the current geographic situation. This dataset forms part of the Yemen CrisisInsight product suite which includes the Yemen Core Dataset, Yemen: Crisis Impact Overview and Yemen Risk Overview.
  • 1900+ Downloads
    Updated 7 October 2021 | Dataset date: May 20, 2019-May 20, 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Uganda: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 1800+ Downloads
    Updated 7 October 2021 | Dataset date: January 01, 2018-January 01, 2019
    This dataset updates: Never
    This dataset contains shapefiles for Guinea, Liberia, and Sierra Leone from the OpenStreetMap (OSM) project. Each country has its individual file. The dataset counts with contributions of hundreds of users. This dataset is updated daily. The original dataset can be downloaded from the OSM West Africa Ebola response wiki.
  • 2900+ Downloads
    Updated 7 October 2021 | Dataset date: November 07, 2017-October 21, 2021
    This dataset updates: Every year
    Burundi administrative level 0 (country), 1 (province), and 2 (commune) boundary polygons, lines, and central points in shapefile, geodatabase, and live service formats, and attribute / P-code tables. Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID. These boundary files are suitable for database or GIS linkage to the Burundi - Subnational Population Statistics using the P-codes as keys.
  • 60+ Downloads
    Updated 5 October 2021 | Dataset date: October 04, 2021-October 04, 2021
    This dataset updates: Every month
    Données de base ou d'intérêt pour le secteur de la santé, extraites de la base de données OpenStreetMap et converties suivant le schéma attributaire du Référentiel Géographique Commun de la RDC. Ce dossier reprend actuellement des données en cours de vérification, elles sont donc susceptibles de connaître des modifications fréquentes.
  • 60+ Downloads
    Updated 2 October 2021 | Dataset date: September 20, 2021-October 02, 2021
    This dataset updates: Every month
    Données de base ou d'intérêt pour le secteur de la santé, extraites de la base de données OpenStreetMap et converties suivant le schéma attributaire du Référentiel Géographique Commun de la RDC. Ce dossier reprend actuellement des données en cours de vérification, elles sont donc susceptibles de connaître des modifications fréquentes.
  • 1400+ Downloads
    Updated 29 September 2021 | Dataset date: January 12, 2018-October 21, 2021
    This dataset updates: Every year
    Solomon Islands administrative level 0 (country), 1 (province or capital territory), 2 (constituency), and 3 (ward) boundary polygons Suitable for GIS or database linkage to the Solomon Islands administrative level 0, 1, 2, and 3 population statistics Common Operational Dataset.
  • 7200+ Downloads
    Updated 29 September 2021 | Dataset date: November 30, 2015-October 21, 2021
    This dataset updates: Every year
    Saudi Arabia administrative level 0-1 boundaries and populated places Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.