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.
HDX
Updated September 5, 2018
| Dataset date: Jan 1, 1950-Jan 1, 2005
[Source: United Nations Department of Economic and Social Affairs] Probability of dying between birth and exact age 5. It is expressed as average annual deaths per 1,000 births.
HDX
Updated September 5, 2018
| Dataset date: Jan 1, 1950-Jan 1, 2005
[Source: United Nations Department of Economic and Social Affairs] The average number of years of life expected by a hypothetical cohort of individuals who would be subject during all their lives to the mortality rates of a given period.
HDX
Updated September 5, 2018
| Dataset date: Jan 1, 1950-Jan 1, 2005
[Source: United Nations Department of Economic and Social Affairs] Number of deaths over a given period. Refers to five-year periods running from 1 July to 30 June of the initial and final years.
HDX
Updated September 5, 2018
| Dataset date: Jan 1, 1950-Jan 1, 2010
[Source: United Nations Department of Economic and Social Affairs] Total Population - Both Sexes. De facto population in a country, area or region as of 1 July of the year indicated. Figures are presented in thousands.
Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.
"People Displaced" refers to the number of people living in displacement as of the end of each year.
"New Displacement" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once.
Contains data from IDMC's data portal.
WorldPop
Updated July 17, 2018
| Dataset date: Jan 1, 2015
These datasets provide estimates of population counts for each 100 x 100m grid cell in the country for various years. Please refer to the metadata file and WorldPop website (www.worldpop.org) for full information.
HDX
Updated June 22, 2018
| Dataset date: Jan 1, 1950-Jan 1, 2005
[Source: United Nations Department of Economic and Social Affairs] Probability of dying between birth and exact age 1. It is expressed as average annual deaths per 1,000 births
OCHA FTS
Updated December 31, 2017
| Dataset date: Dec 31, 2017
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.
The GAR15 global exposure database is based on a top-down approach where statistical information including socio-economic, building type, and capital stock at a national level are transposed onto the grids of 5x5 or 1x1 using geographic distribution of population data and gross domestic product (GDP) as proxies.
