Coupling plankton and cholera dynamics Insights into outbreak prediction and practical disease management
| Authors |
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| Publication date | 29-09-2025 |
| Journal | PLoS Computational Biology |
| Article number | e1013523 |
| Volume | Issue number | 21 | 9 |
| Number of pages | 21 |
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| Abstract |
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. |
| Document type | Article |
| Note | With supplementary files |
| Language | English |
| Published at | https://doi.org/10.1371/journal.pcbi.1013523 |
| Other links | https://www.scopus.com/pages/publications/105018324716 |
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