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Proximity networks and epidemics

Author

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  • Toroczkai, Zoltán
  • Guclu, Hasan

Abstract

Disease spread in most biological populations requires the proximity of agents. In populations where the individuals have spatial mobility, the contact graph is generated by the “collision dynamics” of the agents, and thus the evolution of epidemics couples directly to the spatial dynamics of the population. We first briefly review the properties and the methodology of an agent-based simulation (EPISIMS) to model disease spread in realistic urban dynamic contact networks. Using the data generated by this simulation, we introduce the notion of dynamic proximity networks which takes into account the relevant time-scales for disease spread: contact duration, infectivity period, and rate of contact creation. This approach promises to be a good candidate for a unified treatment of epidemic types that are driven by agent collision dynamics. In particular, using a simple model, we show that it can account for the observed qualitative differences between the degree distributions of contact graphs of diseases with short infectivity period (such as air-transmitted diseases) or long infectivity periods (such as HIV).

Suggested Citation

  • Toroczkai, Zoltán & Guclu, Hasan, 2007. "Proximity networks and epidemics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(1), pages 68-75.
    • Handle: RePEc:eee:phsmap:v:378:y:2007:i:1:p:68-75
    DOI: 10.1016/j.physa.2006.11.088
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    Citations

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    Cited by:

    1. Aledo, Juan A. & Diaz, Luis G. & Martinez, Silvia & Valverde, Jose C., 2019. "Dynamical attraction in parallel network models," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 874-888.
    2. Juan A. Aledo & Ali Barzanouni & Ghazaleh Malekbala & Leila Sharifan & Jose C. Valverde, 2020. "On the Periodic Structure of Parallel Dynamical Systems on Generalized Independent Boolean Functions," Mathematics, MDPI, vol. 8(7), pages 1-14, July.
    3. Sanahuja, Silvia M., 2016. "New rough approximations for n-cycles and n-paths," Applied Mathematics and Computation, Elsevier, vol. 276(C), pages 96-108.
    4. Xie He & Amir Ghasemian & Eun Lee & Aaron Clauset & Peter J. Mucha, 2024. "Sequential stacking link prediction algorithms for temporal networks," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    5. Juan A. Aledo & Luis G. Diaz & Silvia Martinez & Jose C. Valverde, 2017. "On the Periods of Parallel Dynamical Systems," Complexity, Hindawi, vol. 2017, pages 1-6, January.
    6. Christensen, Claire & Albert, István & Grenfell, Bryan & Albert, Réka, 2010. "Disease dynamics in a dynamic social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(13), pages 2663-2674.
    7. Juan A. Aledo & Luis G. Diaz & Silvia Martinez & Jose C. Valverde, 2019. "Predecessors Existence Problems and Gardens of Eden in Sequential Dynamical Systems," Complexity, Hindawi, vol. 2019, pages 1-10, March.
    8. Juan A. Aledo & Luis G. Diaz & Silvia Martinez & Jose C. Valverde, 2020. "Coexistence of Periods in Parallel and Sequential Boolean Graph Dynamical Systems over Directed Graphs," Mathematics, MDPI, vol. 8(10), pages 1-14, October.
    9. Aledo, Juan A. & Diaz, Luis G. & Martinez, Silvia & Valverde, Jose C., 2019. "Solution to the predecessors and Gardens-of-Eden problems for synchronous systems over directed graphs," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 22-28.
    10. Sascha Holzhauer & Friedrich Krebs & Andreas Ernst, 2013. "Considering baseline homophily when generating spatial social networks for agent-based modelling," Computational and Mathematical Organization Theory, Springer, vol. 19(2), pages 128-150, June.
    11. Hegemann, Rachel A. & Smith, Laura M. & Barbaro, Alethea B.T. & Bertozzi, Andrea L. & Reid, Shannon E. & Tita, George E., 2011. "Geographical influences of an emerging network of gang rivalries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3894-3914.

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