Modeling and Controlling the Spread of Epidemic with Various Social and Economic Scenarios

TL;DR

This paper introduces an extended epidemic model that incorporates social, economic, and indirect transmission factors, providing a comprehensive framework for understanding and controlling disease spread, especially applicable to COVID-19 scenarios.

Contribution

It develops a novel dynamical model combining epidemic spread with socioeconomic factors and indirect transmission routes, enhancing existing models like SIR and SIQR.

Findings

Model accounts for direct and indirect transmission pathways.

Incorporates economic resources influencing recovery rates.

Supports development of various epidemic control strategies.

Abstract

We propose a dynamical model for describing the spread of epidemics. This model is an extension of the SIQR (susceptible-infected-quarantined-recovered) and SIRP (susceptible-infected-recovered-pathogen) models used earlier to describe various scenarios of epidemic spreading. As compared to the basic SIR model, our model takes into account two possible routes of contagion transmission: direct from the infected compartment to the susceptible compartment and indirect via some intermediate medium or fomites. Transmission rates are estimated in terms of average distances between the individuals in selected social environments and characteristic time spans for which the individuals stay in each of these environments. We also introduce a collective economic resource associated with the average amount of money or income per individual to describe the socioeconomic interplay between the spreading process and the resource available to infected individuals. The epidemic-resource coupling is supposed to be of activation type, with the recovery rate governed by the Arrhenius-like law. Our model brings an advantage of building various control strategies to mitigate the effect of epidemic and can be applied, in particular, to modeling the spread of COVID-19.