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对流行病病毒动力学中主动疫苗接种博弈和追溯治疗博弈中双重困境的共存进行建模与分析。

Modelling and analysing the coexistence of dual dilemmas in the proactive vaccination game and retroactive treatment game in epidemic viral dynamics.

作者信息

Kabir K M Ariful, Tanimoto Jun

机构信息

Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka 816-8580, Japan.

Department of Mathematics, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh.

出版信息

Proc Math Phys Eng Sci. 2019 Dec;475(2232):20190484. doi: 10.1098/rspa.2019.0484. Epub 2019 Dec 4.

Abstract

The dynamics of a spreadable disease are largely governed by four factors: proactive vaccination, retroactive treatment, individual decisions, and the prescribing behaviour of physicians. Under the imposed vaccination policy and antiviral treatment in society, complex factors (costs and expected effects of the vaccines and treatments, and fear of being infected) trigger an emulous situation in which individuals avoid infection by the pre-emptive or provision. Aside from the established voluntary vaccination game, we propose a treatment game model associated with the resistance evolution of antiviral/antibiotic overuse. Moreover, the imperfectness of vaccinations has inevitably led to anti-vaccine behaviour, necessitating a proactive treatment policy. However, under the excessively heavy implementation of treatments such as antiviral medicine, resistant strains emerge. The model explicitly exhibits a dual social dilemma situation, in which the treatment behaviour changes on a local time scale, and the vaccination uptake later evolves on a global time scale. The impact of resistance evolution and the coexistence of dual dilemmas are investigated by the control reproduction number and the social efficiency deficit, respectively. Our investigation might elucidate the substantial impacts of both vaccination and treatment in the framework of epidemic dynamics, and hence suggest the appropriate use of antiviral treatment.

摘要

一种可传播疾病的传播动态在很大程度上由四个因素决定

主动接种疫苗、追溯治疗、个人决策以及医生的开药行为。在社会实施的疫苗接种政策和抗病毒治疗下,复杂因素(疫苗和治疗的成本及预期效果,以及对感染的恐惧)引发了一种竞争局面,即个体通过抢先行动或预防措施来避免感染。除了既定的自愿接种疫苗博弈外,我们提出了一个与抗病毒/抗生素过度使用导致的耐药性演变相关的治疗博弈模型。此外,疫苗接种的不完善不可避免地导致了反疫苗行为,因此需要积极的治疗政策。然而,在过度大量实施抗病毒药物等治疗措施的情况下,会出现耐药菌株。该模型明确呈现出一种双重社会困境局面,即治疗行为在局部时间尺度上发生变化,而疫苗接种率随后在全球时间尺度上演变。分别通过控制繁殖数和社会效率赤字来研究耐药性演变的影响以及双重困境的共存情况。我们的研究可能会阐明疫苗接种和治疗在疫情动态框架中的重大影响,从而建议合理使用抗病毒治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0836/6936617/5bf285869ad6/rspa20190484-g1.jpg

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