{"title":"Transmission of Acute Respiratory Infections in a City: Agent-Based Approach","authors":"A. Vlad, T. E. Sannikova, A. Romanyukha","doi":"10.17537/2020.15.338","DOIUrl":null,"url":null,"abstract":"An incidence curve of acute respiratory infections in Moscow hasthree picks between September and April and reaches its maximum in January-February The emergence of new strains of influenza A could account for onlyone pick a year The most cases of common cold are caused by ubiquitous lowpathogenic viruses In order to simulate weekly fluctuation of incidence rate ofacute respiratory illnesses we developed an agent-based model It contains 10 millions agents with such attributes as sex, age, social status, levels of specific immune memory and lists of contacts Each agent can contact with members of its household, colleagues or classmates Through such contacts susceptible agent can be infected with one of seven circulating respiratory viruses Viruses differ in their immunologic properties and assume to present influenza A virus, influenza B virus, parainfluenza, adenovirus, coronavirus, rhinovirus and respiratory syncytial virus The rate of transmission depends on duration of contact, vulnerability of susceptible agent, infectivity of infected agent and air temperature Proposed network of social interactions proved to be sufficiently detailed as it provided good fitting for observed incidence rate including periods of school holidays and winter public holidays Additionally, the estimates of basic reproductive rate for the viruses confirm that all these viruses except new strains of influenza A are relatively harmless and unable to cause significant growth of acute respiratory infections morbidity © 2020 All Rights Reserved","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"4 1","pages":"338-356"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Biology and Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17537/2020.15.338","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 10
城市急性呼吸道感染的传播:基于主体的方法
莫斯科急性呼吸道感染的发病率曲线在9月至4月之间有三个拐点,在1月至2月达到最大值甲型流感新毒株的出现每年只能占一个拐点,大多数普通感冒病例是由普遍存在的低致病性病毒引起的。为了模拟急性呼吸道疾病发病率的每周波动,我们开发了一个基于agent的模型,该模型包含1000万个具有性别、年龄、社会地位、特定免疫记忆水平和接触者名单每个病原体可与其家庭成员、同事或同学接触,通过这些接触,易感病原体可感染七种循环呼吸道病毒中的一种。病毒的免疫特性不同,可能呈现甲型流感病毒、乙型流感病毒、副流感病毒、腺病毒、冠状病毒、传播速度取决于接触时间、易感病原体的易感性、受感染病原体的传染性和气温。所提出的社会互动网络被证明是足够详细的,因为它很好地拟合了观察到的发病率,包括学校假期和冬季公共假期。此外,对病毒基本繁殖率的估计证实,除甲型流感新毒株外,所有这些病毒都相对无害,不会造成急性呼吸道感染发病率的显著增长©2020版权所有
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