Food insecurity modeling approaches generally involve compiling demographic data at a given level of spatial granularity and projecting an expected food insecurity rate among a certain population. Arguably the most commonly referenced model/data is Map The Meal Gap produced by Feeding America. While regularly updated and robust, the model only provides data at the county level and for the overall and child populations, which limits utility for local planning.

A robust model that functions spatially at the census level and various facets demographically was developed to assess and project food insecurity in Atlanta. Their study on The Suburbanization of Food Insecurity: An Analysis of Projected Trends in the Atlanta Metropolitan Area brought together researchers from the University of Georgia and the Atlanta Food Bank to produce spatial and temporal forecasts of food insecurity.

Discussion with lead researcher Dr. Jerry Shannon provided insight on the model approach as well access to the code used for the study. The study engaged a demographer to work on population estimation, fortunately the Hawaii Data Collaborative's Synthetic Population Model may afford a useful mechanism to develop a similar approach locally.

Jerry Shannon

Resource Repos

Food Insecurity Regression / Time Series Study

RyanCMcDonald/lancelot_group_project

Streamlit

Heroku App with Tableau Dashboards

The resources below utilize various data to model spatial (both) and temporal (second only) food insecurity.

They provide insight into the key aspects of model building for food insecurity through regression analysis of demographic characteristics.

Projecting Food Insecurity