Effect of risk perception on epidemic spreading in temporal networks

Antoine Moinet, Romualdo Pastor-Satorras, and Alain Barrat, Phys. Rev. E 97, 012313 (2018)

Many progresses in the understanding of epidemic spreading models have been obtained thanks to numerous modeling efforts and analytical and numerical studies, considering host populations with very different structures and properties, including complex and temporal interaction networks. Moreover, a number of recent studies have started to go beyond the assumption of an absence of coupling between the spread of a disease and the structure of the contacts on which it unfolds. Models including awareness of the spread have been proposed, to mimic possible precautionary measures taken by individuals that decrease their risk of infection, but have mostly considered static networks. Here, we adapt such a framework to the more realistic case of temporal networks of interactions between individuals. We study the resulting model by analytical and numerical means on both simple models of temporal networks and empirical time-resolved contact data. Analytical results show that the epidemic threshold is not affected by the awareness but that the prevalence can be significantly decreased. Numerical studies on synthetic temporal networks highlight, however, the presence of very strong finite-size effects, resulting in a significant shift of the effective epidemic threshold in the presence of risk awareness. For empirical contact networks, the awareness mechanism leads as well to a shift in the effective threshold and to a strong reduction of the epidemic prevalence.

URL: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.97.012313

PDF: https://arxiv.org/pdf/1710.05589.pdf

BIBTEX:

@article{PhysRevE.97.012313,
  title = {Effect of risk perception on epidemic spreading in temporal networks},
  author = {Moinet, Antoine and Pastor-Satorras, Romualdo and Barrat, Alain},
  journal = {Phys. Rev. E},
  volume = {97},
  issue = {1},
  pages = {012313},
  numpages = {11},
  year = {2018},
  month = {Jan},
  publisher = {American Physical Society},
  doi = {10.1103/PhysRevE.97.012313},
  url = {https://link.aps.org/doi/10.1103/PhysRevE.97.012313}
}