Details

Autor(en) / Beteiligte

• Mulholland, Leo Patrick
• Feld, Yannick
• Hartmann, Alexander K

Titel

Non-analytic behaviour in large-deviations of the susceptible-infected-recovered model under the influence of lockdowns

Ist Teil von

• New journal of physics, 2023-11, Vol.25 (11), p.113034

Ort / Verlag

Bristol: IOP Publishing

Erscheinungsjahr

2023

Quelle

EZB Free E-Journals

Beschreibungen/Notizen

• Abstract We numerically investigate the dynamics of an SIR model with infection level-based lockdowns on Small-World networks. Using a large-deviation approach, namely the Wang–Landau algorithm, we study the distribution of the cumulative fraction of infected individuals. We are able to resolve the density of states for values as low as 10 −85 . Hence, we measure the distribution on its full support giving a complete characterization of this quantity. The lockdowns are implemented by severing a certain fraction of the edges in the Small-World network, and are initiated and released at different levels of infection, which are varied within this study. We observe points of non-analytical behaviour for the pdf and discontinuous transitions for correlations with other quantities such as the maximum fraction of infected and the duration of outbreaks. Further, empirical rate functions were calculated for different system sizes, for which a convergence is clearly visible indicating that the large-deviation principle is valid for the system with lockdowns.