A Cost-Sensitive Behavioral Modeling Analysis of the Early Identification and Control of Infectious Diseases.

IF 2.3 4区 数学 Q2 BIOLOGY
Mohammad Sharif Ullah, Xiunan Wang, Jin Wang
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引用次数: 0

Abstract

A coupled epidemic-behavior model is proposed to assess how vaccination, testing, and treatment jointly influence early outbreak control, accounting for individual choices based on perceived risk, intervention costs, and policy incentives. In a uniformly mixing population, individuals make strategic decisions regarding vaccination and testing participation based on the trade-offs between personal costs and communal benefits, while the intensity of public health testing adjusts according to infection prevalence; the transmission model includes vaccine efficacy, the probability of false negatives in testing, treatment-related reductions in infectious duration and mortality, as well as nonlinear saturation and awareness feedback mechanisms. Analytical threshold results and simulations (time series and two-dimensional parameter sweeps) indicate that reducing vaccination and testing costs expands the disease-free region, while false negatives consistently diminish the efficacy of increased testing by delaying diagnosis and perpetuating onward transmission; treatment reduces transmission potential but maximizes population benefit when combined with prompt implementation of testing. The approach also delineates parameter regimes in which behavioral feedback provides non-monotonic responses and recurring outbreaks, notwithstanding heightened interventions. The findings suggest that effective epidemic preparedness necessitates synchronized incentives for vaccination and testing, investments to minimize false negatives (such as enhanced test accuracy or repeated testing), and treatment accessibility aligned with rapid case identification to optimize resource distribution and early-response strategies during emerging and re-emerging infectious disease threats.

传染病早期识别与控制的成本敏感行为模型分析。
提出了一个耦合的流行病行为模型来评估疫苗接种,检测和治疗如何共同影响早期疫情控制,考虑基于感知风险,干预成本和政策激励的个人选择。在均匀混合的人群中,个人根据个人成本和公共利益之间的权衡,就疫苗接种和检测参与做出战略决策,而公共卫生检测的强度根据感染流行程度进行调整;传播模型包括疫苗效力、检测中假阴性的概率、与治疗相关的感染持续时间和死亡率的减少,以及非线性饱和和意识反馈机制。分析阈值结果和模拟(时间序列和二维参数扫描)表明,减少疫苗接种和检测成本扩大了无病区域,而假阴性则通过延迟诊断和持续传播而不断削弱增加检测的效果;治疗可降低传播潜力,但如果与及时实施检测相结合,可使人群受益最大化。该方法还描述了参数制度,其中行为反馈提供非单调反应和反复爆发,尽管加强干预。研究结果表明,有效的流行病防范需要同步激励疫苗接种和检测,投资以尽量减少假阴性(例如提高检测准确性或重复检测),以及与快速病例识别相一致的治疗可及性,以优化资源分配和在新出现和再出现的传染病威胁期间的早期反应战略。
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
CiteScore
3.90
自引率
8.60%
发文量
123
审稿时长
7.5 months
期刊介绍: The Bulletin of Mathematical Biology, the official journal of the Society for Mathematical Biology, disseminates original research findings and other information relevant to the interface of biology and the mathematical sciences. Contributions should have relevance to both fields. In order to accommodate the broad scope of new developments, the journal accepts a variety of contributions, including: Original research articles focused on new biological insights gained with the help of tools from the mathematical sciences or new mathematical tools and methods with demonstrated applicability to biological investigations Research in mathematical biology education Reviews Commentaries Perspectives, and contributions that discuss issues important to the profession All contributions are peer-reviewed.
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