Incorporating measures of living conditions and job opportunities into mathematical models of human mobility improves predictions of migration flows, researchers say.

Traditional gravity models estimate migration based on distance and city population, while radiation models focus on opportunities available at a destination. Maurizio Porfiri and colleagues expanded the radiation model by adding indicators such as conflict, natural hazards, political persecution, and income inequality.

The team tested the approach in South Sudan, where conflict combined with flooding strongly influenced migration, and in the United States, where commuting patterns were better explained by variables including rent burden, poverty rates and income inequality.

Although predictions still diverge from reality, the enhanced model consistently outperformed the standard radiation model. The authors said accounting for inequalities between locations could sharpen migration forecasts, particularly as climate-driven displacement rises.