Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics

TL;DR

This paper demonstrates that bursty human interaction patterns, characterized by short intense activity periods followed by silence, generally facilitate the spread of contagion in a history-dependent epidemic model based on real temporal network data.

Contribution

It introduces a history-dependent contagion model and shows through simulations that bursty activity patterns promote epidemic spreading.

Findings

Bursty patterns accelerate epidemic spread in the model.

Repeated short interactions are crucial for infection transmission.

Real temporal data confirms burstiness facilitates spreading.

Abstract

Records of social interactions provide us with new sources of data for understanding how interaction patterns affect collective dynamics. Such human activity patterns are often bursty, i.e., they consist of short periods of intense activity followed by long periods of silence. This burstiness has been shown to affect spreading phenomena; it accelerates epidemic spreading in some cases and slows it down in other cases. We investigate a model of history-dependent contagion. In our model, repeated interactions between susceptible and infected individuals in a short period of time is needed for a susceptible individual to contract infection. We carry out numerical simulations on real temporal network data to find that bursty activity patterns facilitate epidemic spreading in our model.