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  • 4200+ Downloads
    Updated 19 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)
  • 7000+ Downloads
    Updated 18 May 2022 | Dataset date: January 01, 2018-December 31, 2022
    This dataset updates: Every year
    This dataset was compiled by the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) on behalf of the Humanitarian Country Team and partners. It provides the Humanitarian Country Team’s shared understanding of the crisis, including the most pressing humanitarian need and the estimated number of people who need assistance, and represents a consolidated evidence base and helps inform joint strategic response planning. Intersectoral People in Need 2022: For the 2022 Humanitarian Needs Overview, Yemen applied the enhanced HPC approach and the corresponding IASC Joint Inter-sector Analysis Framework (JIAF) global guidance. More details in the methodology of the HNO 2022 in the below link. https://reliefweb.int/sites/reliefweb.int/files/resources/Yemen_HNO_2022%20-%20Final%20Version%20%281%29.pdf Cluster People in Need 2022: The data file contains people in need for 2022 per cluster. The data approved for use by the Humanitarian Country Team and it’s based on the Humanitarian Needs Overview for 2022 in Yemen. The tables are suitable for database or GIS linkages to the Yemen – Administrative Boundaries. The full Humanitarian Needs Overview available in the below link: https://reliefweb.int/sites/reliefweb.int/files/resources/Yemen_HNO_2022%20-%20Final%20Version%20%281%29.pdf Yemen Population estimates for 2022: The data contains population estimates for 2022. The projections are based on 2004 Census data. The population figures are dis-aggregated by governorate and district levels, both containing p-codes. The data is further dis-aggregated by sex and age groups. The data approved for use by the Humanitarian Country Team and used in Humanitarian Needs Overview (HNO) for Yemen in 2022. These tables are suitable for database or GIS linkage to the Yemen - Administrative Boundaries boundaries. Intersectoral People in Need 2021: For the 2021 Humanitarian Needs Overview, Yemen applied the enhanced HPC approach and the corresponding IASC Joint Inter-sector Analysis Framework (JIAF) global guidance. More details in the methodology of the HNO 2021 in the below link. https://reliefweb.int/sites/reliefweb.int/files/resources/Yemen_HNO_2021_Final.pdf Cluster People in Need 2021: The data file contains people in need for 2021 per cluster. The data approved for use by the Humanitarian Country Team and it’s based on the Humanitarian Needs Overview for 2021 in Yemen. The tables are suitable for database or GIS linkages to the Yemen – Administrative Boundaries. The full Humanitarian Needs Overview available in the below link: https://reliefweb.int/sites/reliefweb.int/files/resources/Yemen_HNO_2021_Final.pdf Yemen Population estimates for 2021: The data contains population estimates for 2021. The projections are based on 2004 Census data. The population figures are dis-aggregated by governorate and district levels, both containing p-codes. The data is further dis-aggregated by sex and age groups. The data approved for use by the Humanitarian Country Team and used in Humanitarian Needs Overview (HNO) for Yemen in 2021. These tables are suitable for database or GIS linkage to the Yemen - Administrative Boundaries boundaries.
  • 400+ Downloads
    Updated 17 May 2022 | Dataset date: April 01, 2021-May 16, 2022
    This dataset updates: Every week
    This dataset contains the number of confirmed cases, recoveries and deaths by Governorate due to the Coronavirus pandemic in Palestine.
  • 20+ Downloads
    Updated 16 May 2022 | Dataset date: March 15, 2022-May 20, 2022
    This dataset updates: Every month
    The Risk List enumerates the risks ACAPS analysts have identified. ACAPS analysts conduct daily monitoring and independent analysis of more than 150 countries to support evidence-based decision-making in the humanitarian sector. The information comes from publicly available sources and expert opinions. http://crisisinsight.acaps.org/risklist Need help navigating the platform? Click here for a 2-minute video tutorial https://www.youtube.com/watch?v=f161tOOC_Yk&feature=youtu.be
  • 100+ Downloads
    Updated 15 May 2022 | Dataset date: January 01, 2022-May 04, 2022
    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.
  • 6100+ Downloads
    Updated 13 May 2022 | Dataset date: January 01, 2019-April 30, 2022
    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
  • 90+ Downloads
    Updated 7 May 2022 | Dataset date: March 13, 2020-May 20, 2022
    This dataset updates: Every day
    Number of COVID-19 confirmed cases by region and date
  • 1300+ Downloads
    Updated 7 May 2022 | Dataset date: January 01, 2019-May 20, 2022
    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.
  • 500+ Downloads
    Updated 7 May 2022 | Dataset date: March 03, 2022-May 20, 2022
    This dataset updates: Every day
    Key Figures extracted from Ukraine Flash Appeal, FTS and the daily Situation Reports.
  • 1500+ Downloads
    Updated 29 April 2022 | Dataset date: November 30, 2020-April 28, 2022
    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
  • 600+ Downloads
    Updated 26 April 2022 | Dataset date: December 31, 2020-December 31, 2022
    This dataset updates: Every year
    This dataset contains the people in need per oblast and planning figures per cluster. The dataset is produced by the United Nations for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners.
  • 50+ Downloads
    Updated 19 April 2022 | Dataset date: January 01, 2018-April 02, 2022
    This dataset updates: Every year
    The data is about emergencies caused by natural disasters such as floods and heavy rains.
  • 70+ Downloads
    Updated 18 April 2022 | Dataset date: January 01, 2017-December 31, 2021
    This dataset updates: As needed
    Esta base de datos, extraída del portal de datos abiertos de la Unidad para la Atención Integral y Reparación a las Víctimas, contiene el número de víctimas por hechos del conflicto armado en Colombia entre 2017-2021 desagregado por hecho victimizante, departamento de ocurrencia, sexo, etnia y condición de discapacidad
  • 17000+ Downloads
    Updated Live | Dataset date: January 08, 2020-May 18, 2022
    This dataset updates: Live
    Coronavirus COVID-19 daily new and cumulative cases and deaths by country.
  • 10000+ Downloads
    Updated 13 April 2022 | Dataset date: January 31, 2016-February 18, 2022
    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.
  • 2600+ Downloads
    Updated 9 April 2022 | Dataset date: August 02, 2021-May 20, 2022
    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
  • 9800+ Downloads
    Updated 4 April 2022 | Dataset date: December 19, 2020-May 18, 2022
    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
  • 400+ Downloads
    Updated 28 March 2022 | Dataset date: August 03, 2021-September 01, 2021
    This dataset updates: As needed
    The dataset contains number of people displaced and returnees at village level in Tanganyika province. The dataset also contains needs of the displaced and returned people, reason and time of displacement.
  • 2100+ Downloads
    Updated 27 March 2022 | Dataset date: March 09, 2020-March 18, 2022
    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
  • 100+ Downloads
    Updated 18 March 2022 | Dataset date: July 15, 2020-July 24, 2020
    This dataset updates: Never
    Large-scale flooding and landslides have been triggered in several districts across Nepal following heavy rainfalls in July 2020. From the onset of monsoon on 12 June until 25 July, 130 people lost their lives, 115 were injured and 51 went missing due to floods and landslides according to the National Disaster Risk Reduction and Management Authority.
  • 1100+ Downloads
    Updated Live | Dataset date: January 01, 2020-November 15, 2021
    This dataset updates: Live
    This dataset contains the number of confirmed cases by state due to the Coronavirus pandemic in Venezuela.
  • 100+ Downloads
    Updated 15 March 2022 | Dataset date: May 19, 2020-April 27, 2021
    This dataset updates: As needed
    This dataset contains the number of confirmed cases, recoveries and deaths by Location/Admin 1 due to the Coronavirus pandemic in Somalia.
  • 100+ Downloads
    Updated 15 March 2022 | Dataset date: September 24, 2020-September 24, 2020
    This dataset updates: As needed
    This dataset contains the number of confirmed cases, recoveries and deaths by locations due to the Coronavirus pandemic in Libya.
  • 300+ Downloads
    Updated 15 March 2022 | Dataset date: April 29, 2020-July 16, 2020
    This dataset updates: As needed
    This dataset contains the number of confirmed cases, recoveries and deaths by admin 1 due to the Coronavirus pandemic in Ethiopia.
  • 400+ Downloads
    Updated 9 March 2022 | Dataset date: March 15, 2021-April 20, 2021
    This dataset updates: Every year
    The dataset contains number of people displaced and returnees at village level in North Kivu province. The dataset also contains needs of the displaced and returned people, reason and time of displacement.