Abstract
Introduced in its contemporary form in 1946 (ref. 1), but with roots that go back to the eighteenth century2, the gravity law1,3,4 is the prevailing framework with which to predict population movement3,5,6, cargo shipping volume7 and inter-city phone calls8,9, as well as bilateral trade flows between nations10. 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 processes11,12,13,14,15,16,17,18,19,20,21,22,23.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 51 print issues and online access
£199.00 per year
only £3.90 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Zipf, G. K. The P1P2/D hypothesis: on the intercity movement of persons. Am. Sociol. Rev. 11, 677–686 (1946)
Monge, G. Mémoire sur la Théorie des Déblais et de Remblais. Histoire de l’Académie Royale des Sciences de Paris, avec les Mémoires de Mathématique et de Physique pour la même année 666–704 (De l’Imprimerie Royale, 1781)
Barthélemy, M. Spatial networks. Phys. Rep. 499, 1–101 (2010)
Erlander, S. & Stewart, N. F. The Gravity Model in Transportation Analysis: Theory and Extensions (VSP, 1990)
Jung, W. S., Wang, F. & Stanley, H. E. Gravity model in the Korean highway. EPL 81, 48005 (2008)
Thiemann, C., Theis, F., Grady, D., Brune, R. & Brockmann, D. The structure of borders in a small world. PLoS ONE 5, e15422 (2010)
Kaluza, P., Kölzsch, A., Gastner, M. T. & Blasius, B. The complex network of global cargo ship movements. J. R. Soc. Interf. 7 1093–1103 (2010)
Krings, G., Calabrese, F., Ratti, C. & Blondel, V. D. Urban gravity: a model for inter-city telecommunication flows. J. Stat. Mech. 2009, L07003 (2009)
Expert, P., Evans, T. S., Blondel, V. D. & Lambiotte, R. Uncovering space-independent communities in spatial networks. Proc. Natl Acad. Sci. USA 108, 7663–7668 (2011)
Pöyhönen, P. A tentative model for the volume of trade between countries. Weltwirtschaftliches Arch. 90, 93–100 (1963)
Balcan, D. et al. Multiscale mobility networks and the spatial spreading of infectious diseases. Proc. Natl Acad. Sci. USA 106, 21484–21489 (2009)
Helbing, D. Traffic and related self-driven many-particle systems. Rev. Mod. Phys. 73, 1067–1141 (2001)
Colizza, V., Barrat, A., Barthélemy, M. & Vespignani, A. The role of the airline transportation network in the prediction and predictability of global epidemics. Proc. Natl Acad. Sci. USA 103, 2015–2020 (2006)
Viboud, C. et al. Synchrony, waves, and spatial hierarchies in the spread of influenza. Science 312, 447–451 (2006)
Ferguson, N. M. et al. Strategies for mitigating an influenza pandemic. Nature 442, 448–452 (2006)
Xu, X. J., Zhang, X. & Mendes, J. F. F. Impacts of preference and geography on epidemic spreading. Phys. Rev. E 76, 056109 (2007)
Lind, P. G., Da Silva, L. R., Andrade, J. S., Jr & Herrmann, H. J. Spreading gossip in social networks. Phys. Rev. E 76, 036117 (2007)
Roth, C., Kang, S. M., Batty, M. & Barthélemy, M. Structure of urban movements: polycentric activity and entangled hierarchical flows. PLoS ONE 6, e15923 (2011)
Makse, H. A., Havlin, S. & Stanley, H. E. Modelling urban growth patterns. Nature 377, 608–612 (1995)
Bettencourt, L. M. A., Lobo, J., Helbing, D., Kühnert, C. & West, G. B. Growth, innovation, scaling, and the pace of life in cities. Proc. Natl Acad. Sci. USA 104, 7301–7306 (2007)
Batty, M. The size, scale, and shape of cities. Science 319, 769–771 (2008)
Garlaschelli, D., Di Matteo, T., Aste, T., Caldarelli, G. & Loffredo, M. I. Interplay between topology and dynamics in the World Trade Web. The Eur. Phys. J. B 57, 159–164 (2007)
Eubank, S. et al. Modelling disease outbreaks in realistic urban social networks. Nature 429, 180–184 (2004)
Krueckeberg, D. A. & Silvers, A. L. Urban Planning Analysis: Methods and Models (Wiley, 1974)
Wilson, A. G. The use of entropy maximising models in the theory of trip distribution, mode split and route split. J. Transp. Econ. Policy 108–126 (1969)
Stouffer, S. A. Intervening opportunities: a theory relating mobility and distance. Am. Sociol. Rev. 5, 845–867 (1940)
Block, H. D. & Marschak, J. Random Orderings and Stochastic Theories of Responses (Cowles Foundation, 1960)
Rogerson, P. A. Parameter estimation in the intervening opportunities model. Geogr. Anal. 18, 357–360 (1986)
González, M. C., Hidalgo, C. A. & Barabási, A. L. Understanding individual human mobility patterns. Nature 453, 779–782 (2008)
Onnela, J. P. et al. Structure and tie strengths in mobile communication networks. Proc. Natl Acad. Sci. USA 104, 7332–7336 (2007)
Acknowledgements
We thank J. P. Bagrow, A. Fava, F. Giannotti, Y.-R. Lin, J. Menche, Z. Néda, D. Pedreschi, D. Wang, G. Wilkerson and D. Bauer for many discussions, and N. Ferguson for prompting us to look into the gravity law. A.M. and F.S. acknowledge the Cariparo foundation for financial support. This work was supported by the Network Science Collaborative Technology Alliance sponsored by the US Army Research Laboratory under Agreement Number W911NF-09-2-0053; the Office of Naval Research under Agreement Number N000141010968; the Defense Threat Reduction Agency awards WMD BRBAA07-J-2-0035 and BRBAA08-Per4-C-2-0033; and the James S. McDonnell Foundation 21st Century Initiative in Studying Complex Systems.
Author information
Authors and Affiliations
Contributions
All authors designed and did the research. F.S. analysed the empirical data and performed the numerical calculations. A.M. and F.S. developed the analytical calculations. A.-L.B. was the lead writer of the manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Supplementary information
Supplementary Information
This file contains Supplementary Text and Data 1-9 (see Contents for more details), additional references and Supplementary Figures 1-8 with legends. (PDF 4564 kb)
Rights and permissions
About this article
Cite this article
Simini, F., González, M., Maritan, A. et al. A universal model for mobility and migration patterns. Nature 484, 96–100 (2012). https://doi.org/10.1038/nature10856
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/nature10856
This article is cited by
-
Higher-order non-Markovian social contagions in simplicial complexes
Communications Physics (2024)
-
Network constraints on worker mobility
Nature Cities (2024)
-
Infrequent activities predict economic outcomes in major American cities
Nature Cities (2024)
-
A generalized vector-field framework for mobility
Communications Physics (2024)
-
Forecasting first-year student mobility using explainable machine learning techniques
Review of Regional Research (2024)