Mobility Feedback Shapes Mpox Spatial Hotspots in Network Model

A new mathematical framework published in Advances in Continuous and Discrete Models demonstrates that adaptive human mobility plays a central role in shaping the spatial dynamics of Mpox. The study, led by Olumuyiwa James Peter, develops a network-based reaction–diffusion model that integrates adaptive human mobility, heterogeneous transmission, and spatially varying zoonotic spillover. The research aims to address the mechanisms that drive the formation and persistence of localized hotspots, which remain poorly understood in current epidemiological models.

The model distinguishes itself from classical diffusion models by incorporating prevalence-dependent mobility. In this framework, human movement is not constant but adapts to the local infection prevalence. As the prevalence of infection increases within a specific network node, mobility is reduced. This reduction in movement effectively modifies the diffusion process across the network, limiting the spatial spread of the virus regardless of the timing of the epidemic. The authors establish key analytical properties of the model, including positivity, boundedness, and a network-based basic reproduction number, providing a rigorous mathematical foundation for their simulations.

Numerical simulations reveal that this adaptive mobility mechanism fundamentally alters the spatial invasion of the pathogen. Unlike classical models that assume constant diffusion, the prevalence-dependent mobility slows the spatial invasion of Mpox. Furthermore, the model shows that this adaptive behavior suppresses diffusion-driven instability. Prevalence-dependent mobility also promotes persistent localized hotspots.

The study also examines the impact of higher-order transmission and heterogeneous spillover on these spatial dynamics. The results indicate that higher-order transmission amplifies local outbreaks but does not change the invasion thresholds of the epidemic.

Zoonotic spillover is modeled as spatially varying. The analysis shows that heterogeneous spillover increases transient infection levels in specific areas. However, this heterogeneity does not sustain spatial instability.

The proposed framework offers a mechanistic explanation for the persistent spatial heterogeneity and localized endemicity observed in connected populations.

Subject of Research: Network-based reaction-diffusion model of Mpox spatial dynamics

Article Title: Adaptive mobility and zoonotic spillover drive spatial localization in a network-based Mpox reaction–diffusion model

Article References: Peter, O. J. (2026). Adaptive mobility and zoonotic spillover drive spatial localization in a network-based Mpox reaction–diffusion model. Advances in Continuous and Discrete Models. https://doi.org/10.1186/s13662-026-04111-1

Image Credits: AI Generated

DOI: 10.1186/s13662-026-04111-1

Keywords: Mpox, Epidemiology, Reaction-diffusion model, Human mobility, Zoonotic spillover, Spatial dynamics, Network model, Mathematical biology, Adaptive, mobility, zoonotic, spillover