DATAface. Advanced Statistical Analysis on Beneficiary Household Profiles of the Central America Project.
Multi-Hazard Early Warning (CAMHEW)

The DATAface tool, used in this project, involved a process of data collection from primary and secondary sources through household-level surveys in Guatemala, Nicaragua, Honduras and El Salvador, its analysis and processing using Artificial Intelligence techniques (Self-Organising Maps) to detect groups of individuals with similar characteristics, called profiles. The main objectives were the following: support decision-making by prioritising specific actions on a given profile based on its strengths and vulnerabilities, quantify the effectiveness of NGOs' humanitarian interventions by analysing the evolution of indicators over time, and optimise financial resources and humanitarian response times for future surveys and interventions. The DATAface tool, used in this project, has involved a process of data collection from primary and secondary sources through household-level surveys in Guatemala, Nicaragua, Honduras and El Salvador, its analysis and processing using Artificial Intelligence techniques (Self-Organising Maps) to detect groups of individuals with similar characteristics, called profiles.

Activities carried out:

  • 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 the databases generated in the framework of the baseline, post-monitoring and final baseline studies and additional databases that will help to establish SAN household profiles.
  • 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.

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