A Parrondo paradox in susceptible-infectious-susceptible dynamics over periodic temporal networks

TL;DR

This paper investigates how periodic switching between static networks in SIS epidemic models can paradoxically suppress outbreaks, revealing a Parrondo effect influenced by network structure and subpopulation interactions.

Contribution

It introduces a novel Parrondo paradox in epidemic dynamics over periodic networks and analyzes how network structure affects this counterintuitive phenomenon.

Findings

Alternating networks can reduce epidemic spread below the threshold despite individual networks being above it.

Network connectivity influences the emergence of the Parrondo paradox.

Anti-phase oscillations in subpopulations are linked to the paradoxical suppression of epidemics.

Abstract

Many social and biological networks periodically change over time with daily, weekly, and other cycles. Thus motivated, we formulate and analyze susceptible-infectious-susceptible (SIS) epidemic models over temporal networks with periodic schedules. More specifically, we assume that the temporal network consists of a cycle of alternately used static networks, each with a given duration. We observe a phenomenon in which two static networks are individually above the epidemic threshold but the alternating network composed of them renders the dynamics below the epidemic threshold, which we refer to as a Parrondo paradox for epidemics. We find that network structure plays an important role in shaping this phenomenon, and we study its dependence on the connectivity between and number of subpopulations in the network. We associate such paradoxical behavior with anti-phase oscillatory dynamics of the number of infectious individuals in different subpopulations.