In this paper, we provide a statistical analysis of high-resolution contact pattern data within primary and secondary schools as collected by the SocioPatterns collaboration. Students are graphically represented as nodes in a temporally evolving network, in which links represent proximity or interaction between students. This article focuses on link- and node-level statistics, such as the on- and off-durations of links as well as the activity potential of nodes and links. Parametric models are fitted to the on- and off-durations of links, inter-event times and node activity potentials and, based on these, we propose a number of theoretical models that are able to reproduce the collected data within varying levels of accuracy. By doing so, we aim to identify the minimal network-level properties that are needed to closely match the real-world data, with the aim of combining this contact pattern model with epidemic models in future work.
The mathematics of human contact: Developing a model for social interaction in school children / Ashton, S.; Scalas, E.; Georgiou, N.; Kiss, I.. - In: ACTA PHYSICA POLONICA. A.. - ISSN 1898-794X. - 133:6(2018), pp. -1421. (Intervento presentato al convegno 13th Econophysics Colloquium (EC) and 9th Symposium of Physics in Economy and Social Sciences (FENS), 2017 tenutosi a Warsaw, Poland) [10.12693/APhysPolA.133.1421].
The mathematics of human contact: Developing a model for social interaction in school children
Scalas E.
;
2018
Abstract
In this paper, we provide a statistical analysis of high-resolution contact pattern data within primary and secondary schools as collected by the SocioPatterns collaboration. Students are graphically represented as nodes in a temporally evolving network, in which links represent proximity or interaction between students. This article focuses on link- and node-level statistics, such as the on- and off-durations of links as well as the activity potential of nodes and links. Parametric models are fitted to the on- and off-durations of links, inter-event times and node activity potentials and, based on these, we propose a number of theoretical models that are able to reproduce the collected data within varying levels of accuracy. By doing so, we aim to identify the minimal network-level properties that are needed to closely match the real-world data, with the aim of combining this contact pattern model with epidemic models in future work.File | Dimensione | Formato | |
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