The Effect of Assortativity on Mpox Spreading with Two Core Groups

TL;DR

This paper analyzes mpox spread in a structured population by developing a stochastic SEIR framework with two core groups embedded in a general population. It distinguishes sexual and non-sexual transmission, derives a daily infection matrix $\boldsymbol{\beta}$ and a next-generation matrix $\boldsymbol{\mathcal N}=\boldsymbol{\beta}\,\mathrm{diag}(\gamma^{-1},\gamma^{-1},\gamma^{-1})$, and uses Gillespie simulations to assess non-pharmaceutical interventions that reduce cross-core contacts via rewiring or deletion. Key findings show that intervention effectiveness hinges on core-group symmetry and mixing: rewiring can erode control in symmetric setups, whereas in asymmetric setups, outcomes depend on whether the less influential core group remains active or inactive. The results guide targeted intervention design for mpox and related diseases in structured populations.

Abstract

The spread of infectious diseases often concentrates within specific subgroups of a broader population. For instance, during recent mpox outbreaks in non-endemic countries, transmission primarily affected men who have sex with men (MSM). However, the internal structure of these subpopulations plays a crucial role in disease dynamics and should be accurately represented in mathematical models. In this study, we highlight the importance of modeling interactions between distinct subgroups and their impact on transmission patterns. We consider a stochastic SEIR-based model with two core groups embedded into the general population, and investigate the outcome of the outbreak with different levels of symmetry between these groups and assortativity in their contacts. Our results indicate that the efficiency of commonly used non-pharmaceutical interventions is greatly influenced by these factors, hence they should be considered in the design of intervention strategies.

Figures (10)

• Figure 1: Illustation of our model structure, with two core groups (Core 1 and Core 2) embedded into the general population. Black arrows represent transitions between compartments, red and orange arrows represent transmission pathways.
• Figure 2: Final size distribution for General Group in Base Setup 1 when restrictions are applied on the core groups' sexual connections. The intervention is mostly ineffective in the Both Active and Active/Inactive scenarios, but has a remarkable influence in the Both Inactive and Inactive/Active scenarios.
• Figure 3: Final size distribution for Core Group 1 in Base Setup 1 when restrictions are applied on the core groups' sexual connections. The intervention is mostly ineffective in the Both Active and Active/Inactive scenarios, but has a remarkable influence in the Both Inactive and Inactive/Active scenarios.
• Figure 4: Final size distribution for Core Group 2 in Base Setup 1 when restrictions are applied on the core groups' sexual connections. The intervention is ineffective in the Both Active, moderately effective in the Active/Inactive scenario, but has a remarkable influence in the Both Inactive and Inactive/Active scenarios.
• Figure 5: Final size distribution for General Group in Base Setup 2 when restrictions are applied on the core groups' sexual connections. The impact of the intervention is negligible.