A systematic literature review of forecasting and predictive models for enterococci intrusion in aquatic ecosystems

Philomina Onyedikachi Peter , Edoardo Bertone , Rodney A. Stewart
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Abstract

Ensuring the quality of recreational waters is critical for safeguarding public health and supporting tourism-driven economies. However, rising levels of Enterococci (ENT) present significant risks to aquatic ecosystems and human well-being. Predicting ENT concentrations and understanding their environmental and anthropogenic drivers are essential for effective water resource management and the mitigation of health risks. This systematic review explores the existing body of research on water quality modeling by analyzing various model types, their applications, and their effectiveness. It identifies rainfall and storms as primary drivers of elevated ENT concentrations, emphasizing the critical role of environmental factors in shaping water quality. Additionally, human and animal waste, particularly from sewage intrusion, are highlighted as significant sources of ENT, underscoring the need to address anthropogenic impacts on water contamination. Process-based and data-driven models emerge as prominent tools for forecasting ENT levels in recreational waters. While both approaches are widely utilized, the review notes the difficulty in directly comparing their performance due to methodological variations. By synthesizing findings from diverse studies, the review provides insights into the complex relationships between predictors such as rainfall, ENT levels, and associated health risks from human exposure. The review also addresses the health implications of ENT contamination by identifying its primary sources and associated diseases, enhancing understanding of its broader impacts on public health. Furthermore, it offers evidence-based recommendations for selecting appropriate models to predict ENT levels, empowering researchers and water resource managers to design more effective water quality management strategies. These insights may contribute to reducing the prevalence of waterborne diseases associated with recreational water use, ultimately promoting safer and more sustainable aquatic environments.
水生生态系统肠球菌入侵预测和预测模型的系统文献综述
确保休闲水域的质量对于保障公众健康和支持旅游业驱动的经济至关重要。然而,肠球菌(ENT)水平的上升对水生生态系统和人类福祉构成了重大风险。预测耳鼻喉炎浓度并了解其环境和人为驱动因素对于有效的水资源管理和减轻健康风险至关重要。本文通过分析各种模型类型及其应用和有效性,对现有的水质建模研究进行了系统的综述。它确定降雨和风暴是ENT浓度升高的主要驱动因素,强调环境因素在塑造水质方面的关键作用。此外,人类和动物的废物,特别是来自污水入侵的废物,被强调为耳鼻喉炎的重要来源,强调需要解决人为对水污染的影响。基于过程和数据驱动的模型成为预测休闲水域中ENT水平的重要工具。虽然这两种方法都被广泛使用,但审查指出,由于方法上的差异,很难直接比较它们的表现。通过综合不同研究的结果,该综述深入了解了降雨、耳鼻喉炎水平等预测因素与人类暴露的相关健康风险之间的复杂关系。该审查还通过确定耳鼻喉科污染的主要来源和相关疾病来处理耳鼻喉科污染对健康的影响,加强对其对公共卫生的广泛影响的了解。此外,它还为选择合适的模型来预测ENT水平提供了基于证据的建议,使研究人员和水资源管理者能够设计更有效的水质管理策略。这些见解可能有助于减少与娱乐用水有关的水传播疾病的流行,最终促进更安全和更可持续的水生环境。
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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