A symbiotic SIR process

TL;DR

This paper analyzes a symmetric two-disease SIR co-infection model on networks, revealing how co-infection recovery rates influence epidemic dynamics and burden, with implications for understanding complex disease interactions.

Contribution

It introduces a detailed co-infection SIR model with distinct recovery rates and provides analytical and numerical insights into how these rates affect epidemic thresholds and transient behavior.

Findings

Slower co-infection recovery increases epidemic burden.

Reduced co-infection recovery extends epidemic duration.

Lower recovery rates can raise the epidemic peak.

Abstract

We study a symmetric two-disease SIR co-infection model on networks in which co-infected individuals recover at a rate distinct from that of single infections. The model explicitly represents all co-infection states and features absorbing recovered compartments for both diseases. Within a mean-field network approximation, we derive the basic reproduction number of the coupled system and show that invasion thresholds coincide with those of two independent SIR processes. Exploiting an exchange symmetry in the equal-transmission regime, we reduce the dynamics to a lower-dimensional invariant subsystem and analyze the impact of the co-infection recovery rate. We prove that slower recovery of co-infected individuals monotonically increases the co-infection burden and yields a lower bound on epidemic duration that grows as the co-infection recovery rate decreases. Numerical simulations further indicate that reduced co-infection recovery can increase the epidemic peak, an effect supported by a sensitivity-equation analysis. Together, these results highlight how co-infection-specific recovery dynamics can substantially alter transient epidemic behavior, even in the absence of endemic equilibria.