28 February 2021
| Dataset date: January 01, 1960-December 31, 2019
Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.
Private markets drive economic growth, tapping initiative and investment to create productive jobs and raise incomes. Trade is also a driver of economic growth as it integrates developing countries into the world economy and generates benefits for their people. Data on the private sector and trade are from the World Bank Group's Private Participation in Infrastructure Project Database, Enterprise Surveys, and Doing Business Indicators, as well as from the International Monetary Fund's Balance of Payments database and International Financial Statistics, the UN Commission on Trade and Development, the World Trade Organization, and various other sources.
27 February 2021
| Dataset date: March 01, 2020-August 31, 2020
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/
27 February 2021
| Dataset date: May 18, 2020-February 28, 2021
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
27 February 2021
| Dataset date: May 31, 2020-May 31, 2020
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)
27 February 2021
| Dataset date: February 27, 2021-February 27, 2021
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.
26 February 2021
| Dataset date: September 21, 2020-September 21, 2020
This data contains aggregated weighted statistics at the regional level by gender for the Survey on Gender Equality At Home fielded in July 2020. Facebook’s Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. If you're interested in becoming a Survey on Gender Equality research partner, please email firstname.lastname@example.org.
26 February 2021
| Dataset date: January 01, 1997-February 28, 2021
The Armed Conflict Location & Event Data Project (ACLED) is a disaggregated data collection, analysis, and crisis mapping project. ACLED collects the dates, actors, locations, fatalities, and types of all reported political violence and protest events across Africa, the Middle East, Latin America & the Caribbean, East Asia, South Asia, Southeast Asia, Central Asia & the Caucasus, Europe, and the United States of America.
This dataset contains information on the specific dates and locations of political violence, the types of event, the groups involved, fatalities and changes in territorial control. Information is recorded on the battles, killings, riots, and recruitment activities of rebels, governments, militias, armed groups, protesters and civilians.
Data can be used for medium- and long-term analysis and mapping of political violence across developing countries through use of historical data from 1997, as well as informing humanitarian and development work in crisis and conflict-affected contexts through realtime data updates and reports. Despite the waning of civil wars across the developing world, ACLED data show that political violence rates have remained relatively stable in the past eighteen years. ACLED seeks to support research and work devoted to understanding, predicting and reducing levels of violence and their consequences.
| Dataset date: December 01, 2019-February 26, 2021
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 email@example.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 (firstname.lastname@example.org) 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.
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.
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.
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:
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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/
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.
26 February 2021
| Dataset date: December 15, 2020-February 25, 2021
The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.
Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.
We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.
The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.
United States Data
Data on cumulative coronavirus cases and deaths can be found in two files for states and counties.
Each row of data reports cumulative counts based on our best reporting up to the moment we publish an update. We do our best to revise earlier entries in the data when we receive new information.
Both files contain FIPS codes, a standard geographic identifier, to make it easier for an analyst to combine this data with other data sets like a map file or population data.
State-level data can be found in the us-states.csv file.
County-level data can be found in the us-counties.csv file.
In some cases, the geographies where cases are reported do not map to standard county boundaries. See the list of geographic exceptions for more detail on these.
This dataset contains COVID-19 data for the United States of America made available by The New York Times on github at https://github.com/nytimes/covid-19-data
26 February 2021
| Dataset date: March 10, 2020-February 25, 2021
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: email@example.com
26 February 2021
| Dataset date: January 01, 2021-February 07, 2021
Newly displaced population due to conflict between 01 January 2021 and 07 February 2021, compiled by OCHA sub offices based on inter-agency assessment results. This data is a snapshot as of 26 February 2021 and the numbers are expected to change as new assessment figures become available.
25 February 2021
| Dataset date: May 06, 2020-February 21, 2021
This dataset contains the number of suspected cases, confirmed cases, and deaths by Département due to the Coronavirus pandemic in Haiti. Released by the Ministry of Public Health and Population of Haiti.
24 February 2021
| Dataset date: August 16, 2020-November 26, 2020
This inaugural round of Sudan's Multi-Sector Needs Assessment (MSNA), conducted by REACH and OCHA in close collaboration with the Inter-Sectoral Coordination Group (ISCG), seeks to understand multi-sectoral priority humanitarian needs of populations across the whole of Sudan. The findings from this assessment are presented in this document and are intended to provide timely updates on key sectoral needs and priorities in order to inform humanitarian response and strategic programming for non-displaced, IDP and refugee households across the country.
24 February 2021
| Dataset date: February 28, 2020-February 01, 2021
Subnational data about Covid19 in Senegal- Infections (new cases), Deaths, Recoveries. Please note that the gender data is not available. Thank you for your understanding. For Senegal, the Not specified infected cases represent the confirmed contact cases, their location is not given by the government.
24 February 2021
| Dataset date: February 27, 2020-February 19, 2021
Subnational data about Covid19 in Nigeria per day - Infections (new cases), Deaths, Recoveries + Gender data per region (April - October).
Our report on Nigeria and Covid-19 (subnational analysis) will be available soon on our website.
If you have any inquiries or want to give us your feedback on how you use the datasets, please contact us at firstname.lastname@example.org