{"title":"The Unknown of the Pandemic: An Agent-Based Model of Final Phase Risks","authors":"M. Cremonini, S. Maghool","doi":"10.2139/ssrn.3584368","DOIUrl":null,"url":null,"abstract":"Lifting social restrictions is one of the most critical decisions that public health authorities have to face during a pandemic such as COVID-19 This work focuses on the risk associated with such a decision We have called the period from the re-opening decision to epidemic expiration the ’final epidemic phase’, and con-sidered the critical epidemic conditions which could possibly emerge in this phase The factors we have consid-ered include: the proportion of asymptomatic cases, a mitigation strategy based on testing and the average duration of infectious states By assuming hypothetical configurations at the time of the re-opening decision and the partial knowledge concerning epidemic dynamics available to public health authorities, we have analyzed the risk of the re-opening decision based on possibly unreliable estimates We have presented a discrete-time stochastic model with state-dependent transmission probabilities and multi-agent simulations Our results show the different outcomes produced by different proportions of undetected asymptomatic cases, different probabilities of asymptomatic cases detected and contained, and a multivariate analysis of risk based on the average duration of asymptomatic and contained states Finally, our analysis highlights that enduring uncer-tainty, typical of this pandemic, requires a risk analysis approach to complement epidemiological studies © 2020, University of Surrey All rights reserved","PeriodicalId":14675,"journal":{"name":"J. Artif. Soc. Soc. Simul.","volume":"39 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Artif. Soc. Soc. Simul.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3584368","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
大流行的未知:基于主体的最后阶段风险模型
在COVID-19等大流行期间,解除社会限制是公共卫生当局必须面对的最关键决定之一,这项工作重点关注与此类决定相关的风险。我们将重新开放决定到流行病结束的这段时间称为“最后流行病阶段”,并考虑了在这一阶段可能出现的关键流行病情况。我们考虑的因素包括:无症状病例比例、基于检测的缓解策略和感染状态的平均持续时间。通过假设重新开放决定时的假设配置和公共卫生当局对流行病动态的部分了解,我们基于可能不可靠的估计分析了重新开放决策的风险。我们提出了一个离散时间随机模型,该模型具有状态依赖的传播概率和多智能体模拟。我们的结果表明,不同比例的未发现无症状病例、不同概率的发现和控制无症状病例,最后,我们的分析强调,持续的不确定性是本次大流行的典型特征,需要一种风险分析方法来补充流行病学研究©2020,萨里大学版权所有
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