Agent-based model of measles epidemic development in small-group settings

Abstract

Measles infection is a significant global public health concern, with one patient able to infect 12–18 people in a susceptible population. Mathematical modeling helps understand the factors influencing measles outbreaks, including vaccination levels, population density and movement patterns of the people who comprise it. Agent-based modeling, particularly useful in organized populations like hospitals or academic buildings, can predict the dynamics of infectious disease outbreaks. The aim of this work is to create an agent-based model of measles infection, which would predict the effectiveness of various anti-epidemic measures in small-group settings such as academic buildings. In this article, the effects of vaccination and isolation on the measles epidemic process were studied. The modeling found that combinations of vaccination and isolation measures are most effective, and these anti-epidemic measures allow to reduce the number of susceptible people that were infected from 199/199 (100 %) in the absence of measures to 73–80/199 (36.7–40.2 %).