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  • Updated 16 September 2021 | Dataset date: April 01, 2021-September 15, 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.
  • Updated 16 September 2021 | Dataset date: December 16, 2020-September 15, 2021
    This dataset updates: Every day
    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 State-level data can be found in the us-states.csv file. date,state,fips,cases,deaths 2020-01-21,Washington,53,1,0 ... County-Level Data County-level data can be found in the us-counties.csv file. date,county,state,fips,cases,deaths 2020-01-21,Snohomish,Washington,53061,1,0 ... 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. Github Repository 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
  • 2200+ Downloads
    Updated 16 September 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)
  • 7400+ Downloads
    Updated 15 September 2021 | Dataset date: March 02, 2020-September 14, 2021
    This dataset updates: Every day
    This dataset contains the number of confirmed cases, recoveries and deaths by province due to the Coronavirus pandemic in Indonesia.
  • 1000+ Downloads
    Updated 15 September 2021 | Dataset date: January 01, 2019-September 16, 2021
    This dataset updates: Every day
    This dataset contains the number of confirmed cases, recoveries and deaths by province due to the Coronavirus pandemic in Afghanistan.
  • 20+ Downloads
    Updated 15 September 2021 | Dataset date: March 13, 2020-September 16, 2021
    This dataset updates: Every day
    Number of COVID-19 confirmed cases by region and date
  • 4300+ Downloads
    Updated 9 September 2021 | Dataset date: January 01, 2019-August 31, 2021
    This dataset updates: Every month
    The INFORM Severity Index is a regularly updated, and easily interpreted model for measuring the severity of humanitarian crisis globally. It is a composite index, which brings together 31 core indicators, organised in three dimensions: impact, conditions of affected people, and complexity. All the indicators are scored on a scale of 1 to 5. These scores are then aggregated into components, the three dimensions (Impact, Conditions, Complexity), and the overall severity category based on the analytical framework. The three dimensions have been weighted according to their contribution to severity: impact of the crisis (20%); conditions of affected people (50%); complexity (30%). The weightings are currently a best estimate and will be refined using expert analysis and statistical methods. Each crisis will fall into 1 of 5 categories based on their score ranging from very low to high. ACAPS – an INFORM technical partner – is responsible for collection, cleaning, analysis and input of data into the model and the production of the final results. Read more on the GCSI methodology here: https://www.acaps.org/methodology/severity This data is also available on ACAPS API: http://api.acaps.org/api/v1
  • 1500+ Downloads
    Updated 8 September 2021 | Dataset date: March 09, 2020-September 06, 2021
    This dataset updates: Every week
    Subnational data about Covid19 in Burkina Faso - Infected (new cases, gender), Deceased, Recovered. NEW (!) : VACCINATION DATA PER REGION (1st & 2nd dose) Type of vaccine : AstraZeneca ; Johnson&Johnson
  • 8200+ Downloads
    Updated 7 September 2021 | Dataset date: March 22, 2020-September 05, 2021
    This dataset updates: Every week
    This dataset contains the number of confirmed cases, deaths and recoveries by province due to the Coronavirus pandemic in Mozambique.
  • 100+ Downloads
    Updated 6 September 2021 | Dataset date: May 11, 2020-April 29, 2021
    This dataset updates: As needed
    COvid 19 subnational data for iraq
  • 11000+ Downloads
    Updated Live | Dataset date: January 08, 2020-September 15, 2021
    This dataset updates: Live
    Coronavirus COVID-19 daily new and cumulative cases and deaths by country.
  • Updated Live | Dataset date: January 01, 2020-September 16, 2021
    This dataset updates: Live
    This dataset contains the number of confirmed cases by state due to the Coronavirus pandemic in Venezuela.
  • 2100+ Downloads
    Updated 2 September 2021 | Dataset date: August 02, 2021-September 16, 2021
    This dataset updates: As needed
    This dataset contains the number of confirmed cases, recoveries and deaths by country and subnational region due to the Coronavirus pandemic in Europe. Since the outbreak of the COVID-19 crisis, the Joint Research Centre (JRC) has been supporting the European Commission in multidisciplinary areas to understand the COVID-19 emergency, anticipate its impacts, and support contingency planning. This data provides an overview of the monitoring in the area of the 34 UCPM Participating States plus Switzerland related to sub-national data (admin level 1) on numbers of contagious and fatalities by COVID-19, collected directly from the National Authoritative sources (National monitoring websites, when available). The sub-national granularity of the data allows to have a fit-for-purpose model to early capture the local spread and response to the COVID-19 outbreak. The data is maintained on the JRC COVID-19 Github Repository
  • 30+ Downloads
    Updated 30 August 2021 | Dataset date: August 27, 2021-September 16, 2021
    This dataset updates: As needed
    Haiti Earthquake (M7.2) Preliminary Satellite-Based Comprehensive - Damage assessment (Grande’Anse, South, and Nippes departments of Haiti, 27 August 2021)
  • 1200+ Downloads
    Updated 25 August 2021 | Dataset date: November 30, 2020-August 24, 2021
    This dataset updates: Every month
    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
  • 100+ Downloads
    Updated 16 August 2021 | Dataset date: May 05, 2019-June 30, 2021
    This dataset updates: As needed
    The dataset contains IDPs at site level.
  • 8200+ Downloads
    Updated 12 August 2021 | Dataset date: May 01, 2015-June 30, 2021
    This dataset updates: Every three months
    The dataset contains IDPs individual and households at admin2 level. IOM has been developing a Displacement Tracking Matrix (DTM) since May 2015 aimed at effectively monitoring and evaluating the flows of Burundian IDPs and providing accurate information on the current IDP situation. The DTM in Burundi has been successfully used in 2014, upon the request of the humanitarian community and the GoB when some areas of Bujumbura were flooded, which caused displacement. This tool allowed registering IDPs in four IDP sites and in host families in four locations and identifying their humanitarian needs.
  • 200+ Downloads
    Updated 8 August 2021 | Dataset date: January 01, 2021-July 28, 2021
    This dataset updates: As needed
    1) Natural disaster events include avalanches, earthquakes, flooding, heavy rainfall & snowfall, and landslides & mudflows as recorded by OCHA field offices based on assessments in the field. 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) people, who may or may not require humanitarian assistance. 3) The information includes assessment figures from OCHA, ANDMA, IOM, Red Crescent Societies, national NGOs, international NGOs, and ERM. 4) The number of affected people and houses damaged or destroyed are based on the reports received. These figures may change as updates are received.
  • 90+ Downloads
    Updated 5 July 2021 | Dataset date: September 20, 2020-September 20, 2020
    This dataset updates: As needed
    The dataset contains data on the total population in Libya aggregated by mantika (admin level 2).
  • 300+ Downloads
    Updated 22 June 2021 | Dataset date: February 01, 2020-March 31, 2021
    This dataset updates: Every six months
    The dataset contains IDPs, Returnees and host community at sub-national level.
  • 7300+ Downloads
    Updated 16 June 2021 | Dataset date: April 01, 2021-April 30, 2021
    This dataset updates: Every three months
    The dataset contains IDPs, returnees at sub national level. The dataset also has reason of displacement, origin and dates of multiple displacements. The context of displacement in Mali remains complex and fluid. Movements of IDPs currently residing in the southern regions to the northern regions continue to be reported. While some have indicated that they have returned definitively, other IDPs say they travel back and forth between the place of travel and the place of origin.
  • 20+ Downloads
    Updated 15 June 2021 | Dataset date: June 08, 2021-September 16, 2021
    This dataset updates: Every year
    Zimbabwe Affected areas and needs data for 2021
  • 5300+ Downloads
    Updated 26 May 2021 | Dataset date: January 01, 2021-February 28, 2021
    This dataset updates: Every six months
    This datasets has IDPs, Household & Returnees data at Admin3 level gathered through DTM Mobility Tracking Assessment. In the context of the political instability that has prevailed since the uprising in Libya (October 2011) and culminated in the collapse of a fragile central authority accompanied by fragmentation and infighting among myriads of militias, with continued fighting since the mid-2014 escalations, estimates indicate that the number of Internally Displaced Per-sons (IDPs) in Libya has exceeded 400,000 individuals, some eight percent of the total population (HNO, September 2015). While the country struggles to achieve and maintain stability, thousands of migrants are also taking journeys to and through Libya in a desperate bid to seek a better life in Europe. These migrants are exposed to risks of being trafficked and exploited while traveling through dangerous routes in deserts and territories controlled by different armed groups, as well as dying during attempts to cross the Mediterranean Sea. However, there has been no standardized mechanism in place to verify and regularly update IDP and migrant numbers. Given that most humanitarian and international organizations operate remotely from Tunis since mid-July 2014 due to the deteriorating security situation, maintaining access to reliable and updated data on the humanitarian situation in Libya has been challenging.
  • 1800+ Downloads
    Updated 9 May 2021 | Dataset date: January 01, 2020-December 27, 2020
    This dataset updates: As needed
    1) Natural disaster events include avalanches, earthquakes, flooding, heavy rainfall & snowfall, and landslides & mudflows as recorded by OCHA field offices based on assessments in the field. 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) people, who may or may not require humanitarian assistance. 3) The information includes assessment figures from OCHA, ANDMA, IOM, Red Crescent Societies, national NGOs, international NGOs, and ERM. 4) The number of affected people and houses damaged or destroyed are based on the reports received. These figures may change as updates are received.
  • 600+ Downloads
    Updated 8 May 2021 | Dataset date: January 01, 2013-December 31, 2013
    This dataset updates: Never
    1) Natural disaster events include avalanches, extreme winter conditions, flooding, heavy rainfall, landslides & mudflows, and extreme weather (sandstorms, hail, wind, etc) as recorded by OCHA field offices and IOM Afghanistan Humanitarian Assistance Database (HADB). 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) Afghans, who may or may not require humanitarian assistance. 3) HADB information is used as a main reference and supplemented by OCHA Field Office reports for those incidents where information is not available from the HADB. OCHA information includes assessment figures from OCHA, ANDMA, Red Crescent Societies, national NGOs, international NGOs, and ERM.