© ACNUR/Melissa Pinel

Context

Since mid-2021, Central and South America, particularly the perilous Darién Jungle, have faced an unprecedented migratory crisis characterized by severe hazards like water scarcity, natural risks, wildlife encounters, theft, abuse, and exploitation. Panamanian authorities reported that over 240,000 individuals, representing 50 different nationalities, traversed the jungle in 2022, with 60% originating from Venezuela. From January to August 2023, a record-breaking 333,704 transit migrants were recorded, and notably, 21% of these were children and adolescents.
 
Amid this situation, acquiring real-time information on evolving population needs, distinctive characteristics of traveling groups, and satisfaction levels with aid becomes crucial for enhancing humanitarian responses. In this context, chatbots have emerged as an innovative solution for gathering high-frequency data in humanitarian crises

Current Projects

Monitoring of Mixed Migratory Flows and their Access to Services in Chile, Colombia, Costa Rica, and Panama
3iSolutions, together with UNICEF, proposes a novel methodology for the characterization and monitoring of the demand and supply of humanitarian services to the migrant population in Chile, Colombia, Panama, and Costa Rica: Aurora, a chatbot designed for the migrant population and implemented through WhatsApp.
With Aurora, travel groups are characterized (demographic profiles, needs, age, aid received,…) and obtain feedback on humanitarian aid services through the route while providing information on self-care, safety recommendations, location of humanitarian assistance, news and educational material for children and adolescents. The data collected is shared with decision-makers.
 
The goal is to optimize humanitarian aid on the route using high frequency data. Allowing the population to be consulted enables better aid targeting and recipient satisfaction. This will also provide a new objective information tool to combat misinformation, allowing better decision making to avoid dangerous outcomes. This also has strong policy-making and data science research potential as it would provide high quality data on migration in the region.