INFORM
Last updated on September 14, 2018
Interactive Data
Index for Risk Management Data
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  • INFORM
    Updated September 14, 2018 | Dataset date: Jan 1, 2015-Dec 31, 2015
    The overall INFORM risk index identifies countries at risk from humanitarian crises and disasters that could overwhelm national response capacity. It is made up of three dimensions - hazards and exposure, vulnerability and lack of coping capacity.
    • XLSX
    • 500+ Downloads
    • This dataset updates: Every year
  • INFORM
    Updated September 14, 2018 | Dataset date: Sep 6, 2018
    The INFORM initiative began in 2012 as a convergence of interests of UN agencies, donors, NGOs and research institutions to establish a common evidence-base for global humanitarian risk analysis. INFORM identifies the countries at a high risk of humanitarian crisis that are more likely to require international assistance. The INFORM model is based on risk concepts published in scientific literature and envisages three dimensions of risk: Hazards & Exposure, Vulnerability and Lack of Coping Capacity. The INFORM model is split into different levels to provide a quick overview of the underlying factors leading to humanitarian risk. The INFORM index supports a proactive crisis management framework. It will be helpful for an objective allocation of resources for disaster management as well as for coordinated actions focused on anticipating, mitigating, and preparing for humanitarian emergencies.
    • XLSX
    • 40+ Downloads
    • This dataset updates: Every year
  • INFORM
    Updated September 13, 2018 | Dataset date: Mar 23, 2015
    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.
    • XLSX
    • 10+ Downloads
    • This dataset updates: Every year
  • INFORM
    Updated September 13, 2018 | Dataset date: May 19, 2017
    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.
    • XLSX
    • 20+ Downloads
    • This dataset updates: Every year
  • INFORM
    Updated September 13, 2018 | Dataset date: Sep 15, 2015
    INFORM Lebanon was developed by the Lebanon Joint Analysis Unit, which supports the Resident/Humanitarian Coordinator and is a collaboration of humanitarian, development and governmental partners that supports cross sectoral planning at the national level. INFORM Lebanon is being embedded in regional processes and coordination mechanisms to help all partners quantify and prioritise humanitarian and disaster risks in Lebanon in the context of the regional Syrian Crisis Response.
    • XLSX
    • 10+ Downloads
    • This dataset updates: Never
  • INFORM
    Updated September 12, 2018 | Dataset date: May 3, 2015
    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.
    • XLSX
    • 10+ Downloads
    • This dataset updates: Every year
  • INFORM
    Updated September 12, 2018 | Dataset date: May 5, 2017
    INFORM Guatemala is a municipal risk index that identifies risks, threats, vulnerabilities and response capacities in the 340 municipalities of Guatemala. The municipal risk index simplifies information about crisis risk and is comprised of 29 indicators representing the three dimensions of risk: hazard and exposure, vulnerability, and lack of coping capacity. The results of the Guatemala INFORM index will be used by the National Coordination System for Disaster Risk Reduction (CONRED) for its analysis of risk of humanitarian crisis and disasters, municipal response capacities and potential humanitarian needs. Government institutions, civil society and international cooperation organizations can also use the results to focus the design and implementation of development programs and projects. The Guatemala INFORM initiative is supported by UNICEF, OCHA and WFP.
    • XLSX
    • 30+ Downloads
    • This dataset updates: Every year
  • INFORM
    Updated September 12, 2018 | Dataset date: Mar 28, 2018
    The INFOM Honduras tool has been implemented and will be updated by the Permanent Contingency Commission (COPECO). COPECO and other government institutions will jointly implement the INFORM initiative in the context of the National Risk Management System (SINAGER). The national Humanitarian Network, Civil Society Organizations, Academic institutions, and the Association of Municipalities of Honduras (AMHON) will also collaborate with the initiative.
    • XLSX
    • 10+ Downloads
    • This dataset updates: Every year
  • INFORM
    Updated September 12, 2018 | Dataset date: Jun 7, 2017
    The regional INFORM Sahel model was initiated by Emergency Response and Preparedness Group of regional Inter-Agency Standing Committee (IASC) and is managed by OCHA. The INFORM model is being used to support the Humanitarian Programme Cycle and 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.
    • XLSX
    • 50+ Downloads
    • This dataset updates: Every year