平衡病毒爆发的缓解战略。

IF 2.6 4区 工程技术 Q1 Mathematics Mathematical Biosciences and Engineering Pub Date : 2024-12-04 DOI:10.3934/mbe.2024337
Hamed Karami, Pejman Sanaei, Alexandra Smirnova
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引用次数: 0

摘要

控制和预防战略是管理传染病传播不可或缺的工具。这篇论文研究了病毒爆发后接种疫苗阶段的生物学模型,该模型整合了两种重要的缓解工具:旨在降低疾病传播率的社会距离,以及增强免疫系统的疫苗接种。考虑了流行病发展的五种不同情况:(ⅰ)“无控制”情景,反映疾病在没有任何安全措施的情况下的自然演变;(ⅱ)“重建”情景,代表现实世界的数据和干预措施;(ⅲ)“社会距离控制”情景,涵盖广泛的行为变化;(ⅳ)“疫苗控制”情景,展示疫苗接种对流行病传播的影响;(ⅴ)“两种控制同时进行”情景,包括社会距离和疫苗控制同时进行。通过比较这些情况,我们提供了各种干预策略的综合分析,为疾病动态提供了有价值的见解。我们对控制成本建模的创新方法产生了一个鲁棒的计算算法,用于解决与不同公共卫生法规相关的最优控制问题。数值结果得到了美国COVID-19大流行Delta变体的实际数据的支持。
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Balancing mitigation strategies for viral outbreaks.

Control and prevention strategies are indispensable tools for managing the spread of infectious diseases. This paper examined biological models for the post-vaccination stage of a viral outbreak that integrate two important mitigation tools: social distancing, aimed at reducing the disease transmission rate, and vaccination, which boosts the immune system. Five different scenarios of epidemic progression were considered: (ⅰ) the "no control" scenario, reflecting the natural evolution of a disease without any safety measures in place, (ⅱ) the "reconstructed" scenario, representing real-world data and interventions, (ⅲ) the "social distancing control" scenario covering a broad set of behavioral changes, (ⅳ) the "vaccine control" scenario demonstrating the impact of vaccination on epidemic spread, and (ⅴ) the "both controls concurrently" scenario incorporating social distancing and vaccine controls simultaneously. By comparing these scenarios, we provided a comprehensive analysis of various intervention strategies, offering valuable insights into disease dynamics. Our innovative approach to modeling the cost of control gave rise to a robust computational algorithm for solving optimal control problems associated with different public health regulations. Numerical results were supported by real data for the Delta variant of the COVID-19 pandemic in the United States.

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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).
期刊最新文献
Correction to "Data augmentation based semi-supervised method to improve COVID-19 CT classification" [Mathematical Biosciences and Engineering 20(4) (2023) 6838-6852]. Correction to "IMC-MDA: Prediction of miRNA-disease association based on induction matrix completion" [Mathematical Biosciences and Engineering 20(6) (2023) 10659-10674]. A semi-supervised deep neuro-fuzzy iterative learning system for automatic segmentation of hippocampus brain MRI. Revisiting the classical target cell limited dynamical within-host HIV model - Basic mathematical properties and stability analysis. Intra-specific diversity and adaptation modify regime shifts dynamics under environmental change.
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