Modelling behavioural interactions in infection disclosure during an outbreak: An evolutionary game theory approach.

IF 2.6 4区 工程技术 Q1 Mathematics
Pranav Verma, Viney Kumar, Samit Bhattacharyya
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引用次数: 0

Abstract

In confronting the critical challenge of disease outbreak management, health authorities consistently encourage individuals to voluntarily disclose a potential exposure to infection and adhere to self-quarantine protocols by assuring medical care (hospital beds, oxygen, and constant health monitoring) and helplines for severe patients. These have been observed during pandemics; for example, COVID-19 phases in many middle-income countries, such as India, promoted quarantine and reduced stigma. Here, we present a game-theoretic model to elucidate the behavioural interactions in infection disclosure during an outbreak. By employing a fractional derivative approach to model disease propagation, we determine the minimum level of voluntary disclosure required to disrupt the chain of transmission and allow the epidemic to fade. Our findings suggest that higher transmission rates and an increased perceived severity of infection may change the externality of the disclosing strategy, leading to an increase in the proportion of individuals who choose disclosure, and ultimately reducing disease incidence. We estimate the behavioural parameters and transmission rates by fitting the model to COVID-19 hospitalized cases in Chile, South America. The results from our paper underscore the potential for promoting the voluntary disclosure of infection during emerging outbreaks through effective risk communication, thereby emphasizing the severity of the disease and providing accurate information to the public about capacities within hospitals and medical care facilities.

暴发期间感染披露中的行为相互作用建模:进化博弈论方法。
面对疾病暴发管理的严峻挑战,卫生当局一贯鼓励个人自愿披露潜在的感染暴露,并通过确保医疗护理(医院床位、氧气和持续健康监测)和对重症患者的帮助热线来遵守自我隔离协议。在大流行期间曾观察到这些现象;例如,在印度等许多中等收入国家,COVID-19阶段促进了隔离并减少了耻辱感。在这里,我们提出了一个博弈论模型来阐明疫情期间感染披露中的行为相互作用。通过采用分数导数方法来模拟疾病传播,我们确定了破坏传播链和允许流行病消退所需的自愿披露的最低水平。我们的研究结果表明,较高的传播率和感染严重程度的增加可能会改变披露策略的外部性,导致选择披露的个体比例增加,并最终降低疾病发病率。我们通过将模型拟合到南美洲智利的COVID-19住院病例中来估计行为参数和传播率。我们论文的结果强调了通过有效的风险沟通,在新爆发的疫情期间促进自愿披露感染情况的潜力,从而强调疾病的严重性,并向公众提供有关医院和医疗机构能力的准确信息。
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
Mathematical Biosciences and Engineering
Mathematical Biosciences and Engineering 工程技术-数学跨学科应用
CiteScore
3.90
自引率
7.70%
发文量
586
审稿时长
>12 weeks
期刊介绍: Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing. MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).
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