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Monitoreo y Predicción de la Seguridad Alimentaria y
Nutricional en Centroamérica 2021.

Herramienta

PREDISAN

This consultancy is part of the project "Maximising the impact of humanitarian assistance in the dry corridor by improving the generation and dissemination of Food Security and Nutrition data", where we proceeded to identify and characterise the Areas of Concern related to FNS Vulnerability using our own methodology already tested in validated research published in scientific journals of international relevance.

Some of the actions included in the project:

  • Creation of a baseline model of SAN Vulnerability using Artificial Intelligence.
  • Mapping, critical evaluation of technological solutions and elaboration of pre-agreements in different CA4 contexts.
  • Pilot experience of humanitarian pre-assistance based on AVC as a disaster preparedness strategy in high-risk areas.
  • Compilation of secondary databases related to the humanitarian field and elaboration of a baseline map of humanitarian vulnerability at the municipal level in CA4 under INFORM Index methodology. 
  • Elaboration of monthly analyses of humanitarian developments in CA4 with emphasis on agro-climatic aspects and for early warning purposes.
  • Development of sample designs and primary data collection in areas of concern through telephone household surveys and dissemination of quarterly reports.
  • Development of training manuals for expert humanitarian information managers (researchers) and users (NGOs, partners, local actors, etc.) of the HIS-CA4 and national and local workshops in disaster-affected areas.
 

Project objectives:

  • Information management for the anticipation of humanitarian crises caused by multiple causes in CA4 and the consensual identification of priority territories and populations to be addressed.
  •  Improved capacity for anticipation, advocacy and coordinated response of local, national and regional humanitarian actors, with the support of academia and the private sector, to address disasters affecting CA4 territories exposed to multiple hazards. 
  • Improved information management for the anticipation of humanitarian crises caused by multiple causes in CA4 and the consensual identification of priority territories and populations to be addressed.
  • Increased evidence-based empowerment and capacity of communities in CA4 exposed to high disaster risk to mobilise resources and manage preparedness and protection actions targeting their most vulnerable populations.

All this process is reflected in the online platform supported by Power BI PREDISAN: