A vector logistic dynamical approach to epidemic evolution on interacting social-contact and production-capacity graphs

TL;DR

This paper introduces a vector logistic dynamical model to analyze how infectious disease spread affects economic production networks, accounting for population heterogeneity and enabling strategic social connectivity regulation.

Contribution

It presents a novel vector logistic approach for SIS epidemic dynamics on interconnected social and economic networks, incorporating probabilistic graph states for strategic planning.

Findings

The model quantifies the impact of epidemic mean and fluctuations on production capacity.

It offers proxy measures for assessing epidemic effects on economic stability.

The approach enables strategic regulation of social connectivity to mitigate epidemic impact.

Abstract

Population inhomogeneity, in the variation of the individual social contact networks and the individual infectious-recovery rates, renders the dynamics of infectious disease spreading uncertain. As a consequence the overlaying economical production network with its proper collaboration components is to extent impacted unpredictably. Our model proposes a `vector logistic' dynamical approach to SIS dynamics in a social contact network interacting with its economic capacity network. The probabilistic interpretation of the graph state in the vector logistic description provides a method to assess the effect of mean and variance of the infected on the production capacity and allows the strategic planning of social connectivity regulation. The impact of the epidemic mean effects and fluctuations on the production capacity is assessed according `cumulative',`majority' and `fragility' proxy measures.