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DATAface. Food Security Profiles of Central American Populations

For the development of this platform it has been necessary to obtain and process data on the most relevant issues in societies around the world, obtaining more specifically data from El Salvador, Guatemala, Honduras and Nicaragua. The DATAface tool allows, through the application of Artificial Intelligence techniques, the detection of groups of individuals with similar characteristics, called profiles, with which it is hoped to support the decision-making of humanitarian organisations by choosing the most necessary emergency action for each profile, checking the effectiveness of the humanitarian actions undertaken through an analysis of the evolution over time of the indicators of the profiles under study and favouring the optimisation of response times and economic resources in future interventions. 

The activities carried out are detailed below:

  • Review of specialised literature related to the characterisation of households and/or territories according to food security criteria, as well as the measurement of the impact of programmes and projects that have an impact on food security. 
  • Review of data from Gallup's global survey conducted between 2014 and 2019 with a total of 24,260 individuals in person or by telephone.
  • Different types of analysis will be applied to define typologies or profiles of households with different degrees of food security (FNS). 
  • Permanent exchange of information with the focal points designated by Action Against Hunger, in order to resolve doubts, assess different options for analysis, preliminary results, etc.
  • Report(s) in interactive Power BI format with statistical analysis generated, including methodological overview applied, most relevant results, brief discussion, graphs, tables and diagrams that help to understand the methodological aspects and results. The information system will allow the establishment of Central American SAN profiles based on databases.

The results reflected in this platform after a complex analysis are intended to contribute to a broader understanding of the causes and consequences of food insecurity and to provide a basis for more effective policies and interventions.