耦合浮游生物和霍乱动力学:洞察爆发预测和实际疾病管理。

IF 3.6 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
PLoS Computational Biology Pub Date : 2025-09-29 eCollection Date: 2025-09-01 DOI:10.1371/journal.pcbi.1013523
Biplab Maity, Swarnendu Banerjee, Abhishek Senapati, Jon Pitchford, Joydev Chattopadhyay
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引用次数: 0

摘要

尽管几个世纪以来作出了广泛的控制努力,但霍乱仍然是一个全球性的重大卫生问题。霍乱病例有季节性出现的报告,特别是在孟加拉三角洲地区,这往往与浮游生物大量繁殖同步。这一现象被广泛认为是霍乱弧菌与水生浮游动物之间的共生相互作用。浮游生物动态在霍乱流行病学中的作用已经得到承认,但仍然知之甚少,因此,它在有效决策中的重要性在很大程度上被忽视了。为此,我们提出并分析了一种新的基于隔室的传播模型,该模型将浮游植物-浮游动物的相互作用整合到人类-细菌霍乱框架中。我们的研究表明,除了繁殖数量之外,细菌与浮游动物介导的传播的相对贡献在塑造流行病的进展和严重程度方面起着至关重要的作用。在存在浮游动物介导传播的情况下,延迟和较低峰值的暴发仍可能导致更大的总体暴发规模。此外,与通常的直觉相反,即使是大规模和早期暴发,由于在高峰后阶段维持较低水平的感染,疫情超调可能会加剧。此外,我们的分析表明,类似过滤的干预措施的时机可以通过生态指标(如浮游植物繁殖)进行战略指导。我们的研究强调了将生态学方面纳入流行病学研究以更好地预测和管理疾病暴发的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coupling plankton and cholera dynamics: Insights into outbreak prediction and practical disease management.

Despite extensive control efforts over the centuries, cholera remains a globally significant health issue. Seasonal emergence of cholera cases has been reported, particularly in the Bengal delta region, which is often synchronized with plankton blooms. This phenomenon has been widely attributed to the commensal interaction between Vibrio cholerae and zooplankton in aquatic environments. The role of plankton dynamics in cholera epidemiology has been acknowledged but remains poorly understood, and consequently, its importance in effective policymaking is largely overlooked. To this end, we propose and analyze a novel compartment-based transmission model that integrates phytoplankton-zooplankton interactions into a human-bacteria cholera framework. Our study shows that, beyond the reproduction number, the relative contribution of bacterial versus zooplankton-mediated transmission plays a crucial role in shaping epidemic progression and severity. In presence of zooplankton-mediated transmission, an outbreak with a delayed and lower peak may still result in a larger overall outbreak size. Additionally, contrary to common intuition, even for a large and early outbreak, the epidemic overshoot may intensify due to the maintenance of lower-level infections during the post-peak phase. Furthermore, our analysis reveals that the timing of filtration-like interventions can be strategically guided by ecological indicators, such as phytoplankton blooms. Our study underscores the importance of incorporating ecological aspects in epidemiological research to better predict and manage disease outbreaks.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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