{"title":"Modelling the transmission dynamics of coronavirus disease 2019 with treatment as a control strategy: the case of India","authors":"Sonam Gyeltshen, Thinley Tobgay","doi":"10.1504/ijmmno.2022.119778","DOIUrl":null,"url":null,"abstract":"This paper models the transmission dynamics of coronavirus disease 2019 (COVID-19) and its treatment based on the cases in India, by extending the classic SIR model to include exposed, asymptomatic, and treatment classes with a special focus to investigate the effect of ineffective treatment on the transmissibility of the infection with variation in the treatment initiation. The basic reproduction number was computed to understand the relative effect of early treatment initiation from the delayed treatment initiation on the transmissibility of the infection. With the estimated parameters obtained by faithfully fitting the simulation to the observed data, a global sensitivity analysis carried out indicated the treatment initiation to be one of the most influential parameters to infection control. With this concept, a further analysis revealed that an early treatment initiation can be a helpful control strategy on the transmissibility of the infection. However, for it to happen, an intervention such as proactively doing case finding is deemed important. Copyright © 2022 Inderscience Enterprises Ltd.","PeriodicalId":13553,"journal":{"name":"Int. J. Math. Model. Numer. Optimisation","volume":"47 1","pages":"29-42"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Math. Model. Numer. Optimisation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijmmno.2022.119778","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
以治疗为控制策略的2019冠状病毒病传播动力学建模:以印度为例
本文以印度病例为基础,将经典SIR模型扩展到暴露、无症状和治疗类别,建立了2019冠状病毒病(COVID-19)的传播动力学和治疗模型,并特别关注治疗无效对感染传播力的影响,以及治疗起始时间的变化。计算基本繁殖数,以了解早期开始治疗与延迟开始治疗对感染传播力的相对影响。通过模拟得到的估计参数与观测数据的拟合,进行了全局敏感性分析,表明治疗起始时间是影响感染控制的最重要参数之一。根据这一概念,进一步的分析表明,早期开始治疗可能是控制感染传播的有益策略。然而,为了实现这一目标,积极主动地寻找案例等干预措施被认为是重要的。版权所有©2022 Inderscience Enterprises Ltd。
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