Agent‑Based Computational Epidemiological Modeling

Abstract

The study of epidemics is useful for not only understanding
outbreaks and trying to limit their adverse effects, but also because epidemics
are related to social phenomena such as government instability,
crime, poverty, and inequality. One approach for studying epidemics is
to simulate their spread through populations. In this work, we describe
an integrated multi-dimensional approach to epidemic simulation, which
encompasses: (1) a theoretical framework for simulation and analysis;
(2) synthetic population (digital twin) generation; (3) (social contact)
network construction methods from synthetic populations, (4) stylized
network construction methods; and (5) simulation of the evolution of a
virus or disease through a social network. We describe these aspects
and end with a short discussion on simulation results that inform public
policy.