Skip to main content

Tutorials

Video Tutorial — FEAST Video tutorial

Example Use Case​

  1. Add a Store: Place a new supermarket in an underserved area—for example, add "Charlie’s Market" to a park location.
  2. Simulate: Step through multiple months to observe how the addition improves food access, particularly for households without vehicles.
  3. Remove a Store: Remove "Charlie’s Market" and/or surrounding stores and examine how food access challenges re-emerge in the affected area.

Explanation

Introduction​

The FEAST tool is a powerful resource for analyzing and simulating the effects of adding or removing stores on household food access. This guide provides clear, step-by-step instructions to help you navigate and utilize the tool effectively.

Why Agent-Based Modeling for Food Access?​

Traditional food access research relies on aggregate statistics and simple distance measurements. However, real household food shopping involve interactions between:

  • Individual Constraints: Income, vehicle access, work schedules, family size
  • Geographic Factors: Store locations, transportation networks, neighborhood characteristics
  • Economic Dynamics: Price variations and store quality differences

Key Features of the Interface​

  1. Map Overview

    • Legend:
      • Supermarkets: Represented by hexagons.
      • Convenience Stores: Represented by small triangles.
      • Households: Shaped like houses.
        • High Food Access: Green.
        • Medium Food Access: Orange/Yellow.
        • Low Food Access: Red.
    • The map is interactive, allowing you to navigate, zoom, and click on specific elements to explore detailed information about stores and households.

  2. Household Data

  • Attributes available for each household include:
    • Income
      • Household size
      • Number of vehicles
      • Number of workers
      • Proximity to the nearest store (within a mile)
      • Transit time (public and private)
      • Food access score
    • Data is sourced from the Census Bureau and Google Maps, ensuring accuracy and relevance. The data reflects real-world locations as closely as possible, with granularity at the census tract level.
  1. Community Data Bar
  • Aggregated metrics displayed for the selected area:
    • Total number of households
    • Number of supermarkets and convenience stores
    • Average household income
    • Average number of household vehicles