title: A universal model for mobility and migration patterns.
abstract: Introduced in its contemporary form in 1946 (ref. 1), but with roots that go back to the eighteenth century, the gravity law is the prevailing framework with which to predict population movement, cargo shipping volume and inter-city phone calls, as well as bilateral trade flows between nations. Despite its widespread use, it relies on adjustable parameters that vary from region to region and suffers from known analytic inconsistencies. Here we introduce a stochastic process capturing local mobility decisions that helps us analytically derive commuting and mobility fluxes that require as input only information on the population distribution. The resulting radiation model predicts mobility patterns in good agreement with mobility and transport patterns observed in a wide range of phenomena, from long-term migration patterns to communication volume between different regions. Given its parameter-free nature, the model can be applied in areas where we lack previous mobility measurements, significantly improving the predictive accuracy of most of the phenomena affected by mobility and transport processes.
authors.affiliation: Center for Complex Network Research and Department of Physics, Biology and Computer Science, Northeastern University, Boston, Massachusetts 02115, USA.
authors.forename: Filippo
authors.initials: F
authors.lastname: Simini
authors.forename: Marta C
authors.initials: MC
authors.lastname: González
authors.forename: Amos
authors.initials: A
authors.lastname: Maritan
authors.forename: Albert-László
authors.initials: AL
authors.lastname: Barabási
mesh_terms: D004641:Emigration and Immigration / Q000706:statistics & numerical data; D005060:Europe; D038622:Internationality; D015233:Models, Statistical; D011156:Population Density; D011157:Population Dynamics; D016008:Statistical Distributions; D013269:Stochastic Processes; D013689:Telephone / Q000706:statistics & numerical data; D014186:Transportation / Q000706:statistics & numerical data; D014481:United States; D006801:Humans