# A computational model of epidemic process with three variants on a synthesized human interaction network

## TL;DR

The paper presents a computational model to study how three virus variants spread through a network representing human interactions.

## Contribution

A new epidemiological model is introduced that incorporates a synthesized human interaction network and three virus variants.

## Key findings

- The model captures epidemic dynamics influenced by network structure and contact frequency.
- Results from various scenarios show behaviors not achievable with traditional compartmental models.
- The model highlights the impact of social structure features on pandemic waves.

## Abstract

Virus mutations give rise to new variants that cause multiple waves of pandemics and escalate the infected number of individuals. In this paper, we develop both a simple random network that we define as a synthesized human interaction network and an epidemiological model based on the microscopic process of disease spreading to describe the epidemic process with three variants in a population with some features of social structure. The features of social structure we take into account in the model are the average number of degrees and the frequency of contacts. This paper shows many computational results from several scenarios both in varying network structures and epidemiological parameters that cannot be obtained numerically by using the compartmental model.