Outbreaks of coinfections: The critical role of cooperativity

Abstract

Modeling epidemic dynamics plays an important role in studying how diseases spread, predicting their future course, and designing strategies to control them. In this letter, we introduce a model of SIR (susceptible-infected-removed) type which explicitly incorporates the effect of cooperative coinfection. More precisely, each individual can get infected by two different diseases, and an individual already infected with one disease has an increased probability to get infected by the other. Depending on the amount of this increase, we prove different threshold scenarios. Apart from the standard continuous phase transition for single-disease outbreaks, we observe continuous transitions where both diseases must coexist, but also discontinuous transitions are observed, where a finite fraction of the population is already affected by both diseases at the threshold. All our results are obtained in a mean field model using rate equations, but we argue that they should hold also in more general frameworks.

Risk of Coinfection Outbreaks in Temporal Networks: A Case Study of a Hospital Contact Network

“…However, the presence of the abrupt outbreaks both in non-interacting and coinfection cases suggests that several temporal clusters, separated by low activity periods, are formed in the empirical network and the connection of those clusters leads to those abrupt outbreaks. This is confirmed when breaking the correlations in cases (c) and (d), where even with coinfection spreading, for which abrupt outbreaks have been reported under several conditions [18][19][20], the randomized temporal network lead to a continuous transition between disease-free and epidemic states. This means that the specific sequence and the temporal correlations that the empirical network contains are responsible for the abrupt jumps (Figure 3).…”

“…Recently, a model for cooperation between two infections has been proposed, with both infections following a dynamics that is an extension of the usual SIR (Susceptible-Infected-Recovered) model [17], but considering that individuals that previously suffered from one infection are more likely to get a second infection than susceptible ones, in a process that is called coinfection [18]. In contrast with usual SIR model applied to a single disease spreading along a network, this dynamics leads to abrupt transitions in several topologies [19,20].…”

First-order phase transition in a majority-vote model with inertia

“…Subsequently, an explosive phenomenon was found in the dynamics of cascading failures in interdependent networks [16][17][18], in contrast to the secondorder continuous phase transition found in isolated networks. More recently, such explosive phase transitions have been reported in various systems, such as explosive synchronization due to a positive correlation between the degrees of nodes and the natural frequencies of the oscillators [19][20][21] [25][26][27].In this paper we report an explosive order-disorder phase transition in a generalized majority-vote (MV) model by incorporating the effect of individuals' inertia (called inertial MV model ). The MV model is one of the simplest nonequilibrium generalizations of the Ising model that displays a continuous order-disorder phase transition at a critical value of noise [28].…”

“…Subsequently, an explosive phenomenon was found in the dynamics of cascading failures in interdependent networks [16][17][18], in contrast to the secondorder continuous phase transition found in isolated networks. More recently, such explosive phase transitions have been reported in various systems, such as explosive synchronization due to a positive correlation between the degrees of nodes and the natural frequencies of the oscillators [19][20][21] or an adaptive mechanism [22], discontinuous percolation transition due to an inducing effect [23], spontaneous recovery [24], and explosive epidemic outbreak due to cooperative coinfections of multiple diseases * Electronic address: chenhshf@ahu.edu.cn † Electronic address: hzhlj@ustc.edu.cn ‡ Electronic address: Juergen.Kurths@pik-potsdam.de [25][26][27].…”

Partial inertia induces additional phase transition in the majority vote model

“…Two groups are important in this context: those presenting absorbing states and the up-down symmetric systems. In the former, distinct mechanisms, such as the inclusion of a quadratic term in the particle creation rates [17,18], the need of a minimal neighborhood for generating subsequent offsprings [19], synergetic effects in multi species models [20,21] or cooperative coinfection in multiple diseases epidemic models [22][23][24] can be taken into account for shifting, from a continuous transition (belonging generically to the directed percolation (DP) universality class [25][26][27]) to a discontinuous one.…”