EVIDENCE-BASED DECISION SUPPORT
Perú
Peru — Obesity among children under 5 years of age
In Peru, obesity was modeled among boys and girls under 5 years of age. The scenario considered variables related to housing conditions, education, and social vulnerability: inadequate housing, difficulties relating to or communicating with others, mobility difficulties, households with children who do not attend school, illiteracy, and households with dirt floors or other non-consolidated materials.
These variables were prioritized because they reflect structural conditions of the household and the social environment that may be related to inequalities in children’s health and nutrition. The spreadsheet notes that environmental variables had greater predictive weight, but they were more complex to modify in a realistic scenario; therefore, changes in social and housing-related variables were chosen. The final effect was limited: average obesity decreased from 1.71% to 1.68%.
Perú's Dashboard
Work Packages
Data Architecture
- Identification and standardization of variables across scales; development of indicators
- Analysis of spatial patterns and factors associated with Food and Nutrition Security pillars
- Geospatial characterization of community food environments: individual (socioeconomic), environmental (water/food access & availability; physical-climate), political (public policies linked to health and food)
- Integration of environmental conditions via satellite data
- Evaluation of vulnerability and resilience to climate change
AI Model Training
- Definition and development of a FNS metric; training and validation of predictive AI models
- Simulation of future scenarios at 10, 30, and 50 years based on climate change and public policy interventions
Climate and Public Policy Scenario Simulator
Build an interactive and dynamic dashboard capable of simulating future scenarios based on climate change and policy interventions
Enable decision-makers to explore different intervention pathways and their projected impacts on Food and Nutrition Security
Virtual Assistant
Implement a virtual assistant (chatbot) powered by a GPT-style generative model to help users access and interpret dashboard outputs and simulations
Execute dashboard models in the background
Provide automated responses and personalized recommendations for decision-makers in real time