SARA

EVIDENCE-BASED DECISION SUPPORT

Paraguay

Paraguay — Overweight among children under 5 years of age

In Paraguay, overweight was modeled among boys and girls under 5 years of age. Since international targets for excess weight generally aim to prevent it from increasing, the scenario sought to explore possible reductions. Variables related to health coverage, access to water inside the household, overcrowding, unmet basic needs, characteristics of the urban and peri-urban built environment, urban vegetation, and average temperature were considered.

These variables were prioritized because they integrate household conditions, access to services, social vulnerability, and environmental factors that may influence children’s nutritional health. Compared with other variables, those selected were the ones the model allowed to be modified in a counterfactual scenario and that could be associated with territorial or social interventions. The scenario estimated a reduction of 0.44 percentage points in overweight, reaching a final prevalence of 15.26%.

Estas variables fueron priorizadas porque integran condiciones del hogar, acceso a servicios, vulnerabilidad social y factores ambientales que pueden influir sobre la salud nutricional infantil. Frente a otras variables, se seleccionaron aquellas que el modelo permitió modificar en un escenario contrafactual y que podían asociarse a intervenciones territoriales o sociales. El escenario estimó una reducción de 0,44 puntos porcentuales del sobrepeso, alcanzando una prevalencia final de 15,26%.

Paraguay'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
  • 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
  • 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

  • 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