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

Q1 Medicine
Sonya O. Vysochanskaya , S. Tatiana Saltykova , Yury V. Zhernov , Alexander M. Zatevalov , Artyom A. Pozdnyakov , Oleg V. Mitrokhin
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引用次数: 0

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 %).

基于代理的小群体环境下麻疹疫情发展模型
麻疹感染是一个重大的全球公共卫生问题,一名患者可感染易感人群中的 12-18 人。数学建模有助于了解影响麻疹爆发的因素,包括疫苗接种水平、人口密度和人口流动模式。基于代理的建模尤其适用于医院或教学楼等有组织的人群,可以预测传染病爆发的动态。这项工作的目的是创建一个基于代理的麻疹感染模型,从而预测在教学楼等小群体环境中各种抗流行措施的效果。本文研究了疫苗接种和隔离对麻疹流行过程的影响。建模发现,疫苗接种和隔离措施的组合最为有效,这些防疫措施可将易感人群的数量从没有措施时的 199/199(100%)减少到 73-80/199(36.7-40.2%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Informatics in Medicine Unlocked
Informatics in Medicine Unlocked Medicine-Health Informatics
CiteScore
9.50
自引率
0.00%
发文量
282
审稿时长
39 days
期刊介绍: Informatics in Medicine Unlocked (IMU) is an international gold open access journal covering a broad spectrum of topics within medical informatics, including (but not limited to) papers focusing on imaging, pathology, teledermatology, public health, ophthalmological, nursing and translational medicine informatics. The full papers that are published in the journal are accessible to all who visit the website.
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