NishMath

A new mathematical model developed by the University of Rovira i Virgili's SeesLab research group, along with researchers from Northeastern University and the University of Pennsylvania, has made it possible to predict human mobility between cities with high precision. The model offers a simpler and more efficient way than current systems and is a valuable tool for understanding how people move in different contexts, which is crucial for transport planning, migration studies, and epidemiology. The research was published in the journal *Nature Communications*.

The model builds on traditional "gravitational models," which estimate mobility based on population size and distance between cities. While these models are simple, they lack accuracy. Modern approaches leverage artificial intelligence and machine learning to incorporate many variables besides origin and destination, such as the density of restaurants and schools, and the socio-demographic characteristics of the population. The COVID-19 pandemic highlighted the importance of predicting mobility for understanding the spread and evolution of viruses.

ImgSrc: scx2.b-cdn.net

References :

• phys.org: Mathematical model improves prediction of human mobility between cities

Classification:

• HashTags: #statistics #bayesian #modeling
• Target: Forecasting
• Product: Statistics
• Feature: Prediction
• Type: Research
• Severity: Medium