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  • 70+ Downloads
    Updated January 25, 2021 | Dataset date: September 28, 2015-September 28, 2015
    This dataset updates: Every year
    High exposure, High sensitivity and low adaptive capacity leads to high vulnerability. The severity of vulnerability determines the likely impacts to a system that changing climate can have. This data has been developed by RCMRD and Malawi Department of Disaster Management Affairs (DoDMA). SERVIR is a joint USAID-NASA project. For more information on SERVIR, visit http://www.servirglobal.net
  • 2400+ Downloads
    Updated January 4, 2021 | Dataset date: December 10, 2019-December 10, 2019
    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 December 28, 2020 | Dataset date: January 01, 2011-December 31, 2011
    This dataset updates: As needed
    Flood extent in 2011 Original dataset title: Cambodia Flood Extent in 2011
  • 90+ Downloads
    Updated November 4, 2020 | Dataset date: October 06, 2020-October 06, 2020
    This dataset updates: As needed
    The data shows the number of people, Household, houses damaged and destroyed by floods and was shared by the government of Sudan (HAC)
  • 100+ Downloads
    Updated October 30, 2020 | Dataset date: October 31, 2020-October 31, 2020
    This dataset updates: Every six months
    Eastern and Southern Africa Risk Analysis based on Inform, FEWSNET, OCHA, UNICEF and others
  • 2400+ Downloads
    Updated October 12, 2020 | Dataset date: September 12, 2020-September 12, 2020
    This dataset updates: As needed
    The INFORM COVID-19 Risk Index is a composite index that identifies: “countries at risk from health and humanitarian impacts of COVID-19 that could overwhelm current national response capacity, and therefore lead to a need for additional international assistance”. The INFORM COVID-19 Risk Index is primarily concerned with structural risk factors, i.e. those that existed before the outbreak. It can be used to support prioritization of preparedness and early response actions for the primary impacts of the pandemic, and identify countries where secondary impacts are likely to have the most critical humanitarian consequences. The main scope of the INFORM COVID-19 Risk Index is global and regional risk-informed resource allocation, i.e. where comparable understanding of countries’ risk is important. It cannot predict the impacts of the pandemic in individual countries. It does not consider the mechanisms behind secondary impacts - for example how a COVID-19 outbreak could increase conflict risk.
  • 400+ Downloads
    Updated May 1, 2020 | Dataset date: April 23, 2020-April 23, 2020
    This dataset updates: As needed
    INFORM is a multi-stakeholder forum for developing shared, quantitative analysis relevant to humanitarian crises and disasters. INFORM includes organisations from across the multilateral system, including the humanitarian and development sector, donors, and technical partners. The Joint Research Center of European Commission is the scientific and technical lead for INFORM. In response to the COVID-19 pandemic, INFORM has released a COVID Risk Index to support the specific decision-making needs of humanitarian and other organisations. The following is an analysis that addresses key questions for humanitarian organisations by combining information from 3 INFORM products: • The new INFORM COVID Risk Index, which identifies “countries at risk from health and humanitarian impacts of COVID-19 that could overwhelm current national response capacity, and therefore lead to a need for additional international assistance”. The INFORM COVID Risk Index is • The INFORM Risk Index (Mid-2020 version), which identifies “countries at risk from humanitarian emergencies that could overwhelm current national response capacity, and therefore lead to a need for international assistance”. The INFORM Risk Index takes into account natural and human hazards, as well as vulnerability and lack of coping capacity. • The INFORM Severity Index (March 2020 version) is a regularly updated model for measuring the severity of humanitarian crises globally, which brings together indicators of impact, conditions of affected people, and complexity.
  • 800+ Downloads
    Updated April 21, 2020 | Dataset date: March 31, 2020-March 31, 2020
    This dataset updates: As needed
    The INFORM EPIDEMIC RISK INDEX assesses the risk of countries to epidemic outbreak, which would exceed the national capacity to respond to the crisis.
  • Updated April 17, 2020 | Dataset date: January 01, 2018-December 31, 2018
    This dataset updates: As needed
    This layer contains information about the natural shock risk (floods and droughts) estimated during the Integrated Context Analysis (ICA) performed in Niger between 2017 and 2018. The analysis was a joint effort between the Regional Bureau in Dakar (RBD), the HQ GIS Unit and Programme division. Data sources: UNEP/UNISDR GAR 2013, HQ VAM Analysis of CHIRPS Rainfall Estimates (RFE) 1981-2015. Cette couche contient informations regard le risque des chocs naturels (inondations et sècheresse) estimé pendant l’Analyse Integrée du Contexte (AIC) executée en Niger entre 2017 et 2018. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données : UNEP/UNISDR GAR 2013, HQ VAM Analyse des données CHIRPS d’estimation des precipitations 1981-2015. Original dataset title: ICA Niger, 2018 - Natural Shock Risk
  • 10+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: As needed
    This layer contains information about the additional environmental hazards - landslides, Glacial Lake Outburst Flood (GLOF) and earthquakes - estimated during the Integrated Context Analysis (ICA) run in Pakistan in 2017. Data source: NDMA 1950-2015 (landslides and GLOF), NDMA 1905-2015 (earthquakes). The key indicators used for the analysis were 5-point scales of hazard levels ranging from very low to very high. It should be noted that these additional hazards represent aggravating factors that can provide further details to refine broad programmatic strategies, but are not to be considered as stand-alone maps. For the purpose of this analysis, only the high and very high hazards have been mapped on top of the ICA Areas (see the relative static maps for further details). Original dataset title: ICA Pakistan, 2017 - Additional Hazards
  • 10+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 1951-December 31, 2010
    This dataset updates: As needed
    This layer contains information about the drought risk estimated during the Integrated Context Analysis (ICA) performed in Pakistan in 2017. Data source: National Drought Monitoring Centre of the Pakistan Meteorological Department (PMD), 1951-2010. The key indicator used for the analysis was a drought hazard index based on SPI data. Original dataset title: ICA Pakistan, 2017 - Drought Hazard, 1951-2010
  • 10+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 2013-December 31, 2013
    This dataset updates: As needed
    This layer contains information about the flood risk - by second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Niger between 2017 and 2018. The analysis is the result of a joint effort between the Regional Bureau in Dakar (RBD) and the HQ GIS Unit and Programme division. Data sources: UNEP/UNISDR GAR 2013. The main indicators used for the analysis were the percentage of district surface at flood risk and the maximum expected frequency of flood events with a 100-year return period. Cette couche contient informations regard le risque d’inondations – par unité administrative de deuxième niveau – estimé pendant l’Analyse Integrée du Contexte (AIC) executée en Niger entre 2017 et 2018. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données : UNEP/UNISDR GAR, 2013. Les indicateurs principaux utilisées pour l’analyse étaient la pourcentage de surface a risuqe d’inondation et l’attente maximale attendue des inondations. Original dataset title: ICA Niger, 2018 - Flood Risk, 2013
  • 20+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 2014-December 31, 2014
    This dataset updates: As needed
    This layer contains information about the average landslide risk - by second-level administrative area - used for the purposes of the Integrated Context Analysis (ICA) run in the Philippines in 2014. Data source: National Household Targeting System and Mines and Geosciences Bureau. The main indicator used for the analysis was the average flandslide risk by barangay reaggregated by province level. Original dataset title: ICA Philippines, 2014 - Average Landslide Risk, 2014
  • 30+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 1930-December 31, 2000
    This dataset updates: As needed
    This layer contains information about the cyclone hazard estimated during the Integrated Context Analysis (ICA) run in Mozambique in 2017. Data source: Fewsnet, 1930-2000. The indicator used for the analysis was the average frequency of cyclone events. Original dataset title: ICA Mozambique, 2017 - Cyclone Hazard, 1930-2000
  • 20+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 1981-December 31, 2015
    This dataset updates: As needed
    This layer contains information about the drought risk - by second-level administrative area - estimated during the Integrated Context Analysis (ICA) run in Niger between 2017 and 2018. The analysis is a joint effort between the Regional Bureau in Dakar (RBD), the HQ GIS Unit and Programme division. Data source: HQ VAM Analysis of Chirps Rainfall Estimates (RFE), 1981-2015. The main indicator used for the analysis was the number of poor growing seasons observed in the time window of interest. Cette couche contient informations regard le risque de sècheresse – par unité administrative de deuxième niveau – estimée pendant l’Analyse Integrée du Contexte (AIC) executée en Niger entre 2017 et 2018. L’analyse a été executée grâce à la collaboration entre le Bureau Régional de Dakar (RBD), l’unité GIS et la division de Programme au quartier générale du PAM. Source des données: HQ VAM Analyse des données CHIRPS d’estimation des precipitations, 1981-2015. L'indicateur principale utilisé pour l'analyse était le nombre de saisons qui ont connu un déficit hydrique (mauvaises saisons de croissance). Original dataset title: ICA Niger, 2018 - Drought Risk, 1981-2015
  • Updated April 17, 2020 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: As needed
    This layer contains information about the reclassification of the natural shocks risk (floods and drought) into a single combined score according to the Integrated Context Analysis (ICA) performed in Pakistan in 2017. Original dataset title: ICA Pakistan, 2017 - Combined Hazard (Floods and Droughts)
  • 40+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 1950-December 31, 2015
    This dataset updates: As needed
    This layer contains information about the flood risk estimated during the Integrated Context Analysis (ICA) performed in Pakistan in 2017. The indicator used was the number of flood events recorded between 1950 and 2015 and the severity by which they were affected by the super-flood in 2010. Source: National Disaster Management Agency (NDMA) for Pakistan. Original dataset title: ICA Pakistan, 2017 - Flood Hazard, 1950-2015
  • 10+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 2002-December 31, 2012
    This dataset updates: As needed
    This layer contains information about the occurrence of tropical storms above Category 3 - according to the Saffir-Simpson scale and by second-level administrative area - used for the purposes of the Integrated Context Analysis (ICA) run in the Philippines in 2014. Data source: National Oceanic and Atmospheric Administration (NOAA) IBTrACS, 2002-2012. The main indicator used for the analysis was the number of times that a province was hit, in the time frame of interest, by a tropical storm above Category 3. Original dataset title: ICA Philippines, 2014 - Tropical Storm (above Category 3) Occurrence, 2002-2012
  • 20+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 1981-December 31, 2015
    This dataset updates: As needed
    This layer contains information about the drought hazard estimated during the Integrated Context Analysis (ICA) run in Mozambique in 2017. Data source: HQ VAM Analysis of CHIRPS Rainfall Estimates (RFE), 1981-2015, National Institute of Disaster Management (INGC). The indicators used for the analysis were the number of poor growing seasons and the drought hazard classification provided by INGC. Original dataset title: ICA Mozambique, 2017 - Drought Hazard, 1981-2015
  • 20+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: As needed
    This layer contains information about the combined natural shock (floods, droughts and cyclones) hazard estimated during the Integrated Context Analysis (ICA) run in Mozambique in 2017. Data source: Fewsnet 1975-2012, DRFI 2012, INGC, HQ VAM Analysis of CHIRPS Rainfall Estimates (RFE) 1981-2015, Fewsnet 1930-2000. Original dataset title: ICA Mozambique, 2017 - Natural Shocks Hazard
  • 80+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 2014-December 31, 2014
    This dataset updates: As needed
    This layer contains information about the average flood risk - by second-level administrative area - used for the purposes of the Integrated Context Analysis (ICA) run in the Philippines in 2014. Data source: National Household Targeting System and Mines and Geosciences Bureau. The main indicator used for the analysis was the average flood risk by barangay reaggregated by province level. Original dataset title: ICA Philippines, 2014 - Flood Risk, 2014
  • 40+ Downloads
    Updated April 17, 2020 | Dataset date: January 01, 1975-December 31, 2012
    This dataset updates: As needed
    This layer contains information about the flood hazard estimated during the Integrated Context Analysis (ICA) run in Mozambique in 2017. Data source: Fewsnet 1975-2012, Disaster Risk Financing and Insurance (DRFI), 2012. The indicators used for the analysis were the percentage of flood extent and a qualitative classification of the district at high or very high flood risk. It should be noted that the analysis did not consider information about the flood frequency and that, in the last 5 years, flood patterns are changing and affecting the northern part of the country, which is not registering extreme flood events anymore. Original dataset title: ICA Mozambique, 2017 - Flood Hazard, 1975-2012
  • 100+ Downloads
    Updated March 10, 2020 | Dataset date: May 03, 2015-May 03, 2015
    This dataset updates: Never
    The development of the INFORM Colombia model was initiated by OCHA and UNICEF. It is a municipallevel risk index, which identifis threats, vulnerabilities and response capacities throughout the country. The results have been used in the Humanitarian Needs Overview 2016 and by UNICEF planners and donors. The model includes specific components to evaluate risk levels for children and adolescents. Partners are now investigating if the model can be extended to cover additional countries in the region.
  • 100+ Downloads
    Updated March 10, 2020 | Dataset date: March 23, 2015-March 23, 2015
    This dataset updates: Never
    The INFORM Greater Horn of Africa model is part of an initiative of Intergovernmental Authority on Development (IGAD) and OCHA to improve IGAD’s ability to analyse, visualise and disseminate information to support the prevention, preparedness and response to humanitarian crises in the region. The model will be updated regularly to support regional coordination and prioritise humanitarian, development, risk management and resilience investments.
  • 100+ Downloads
    Updated March 10, 2020 | Dataset date: May 19, 2017-May 19, 2017
    This dataset updates: Never
    The sub national INFORM model for Caucasus and Central Asia was initiated by the Regional Inter-Agency Standing Committee (IASC) Task Force for Caucasus and Central Asia and is managed by OCHA. The INFORM model is being used to support coordinated preparedness actions. Partners hope to use the model to improve cooperation between humanitarian and development actors in managing risk and building resilience across the region.