Advances in <i>Vibrio</i>-related infection management: an integrated technology approach for aquaculture and human health
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<i>Vibrio</i> species pose significant threats worldwide, causing mortalities in aquaculture and infections in humans. Global warming and the emergence of worldwide strains <i>of Vibrio</i> diseases are increasing day by day. Control of <i>Vibrio</i> species requires effective monitoring, diagnosis, and treatment strategies at the global scale. Despite current efforts based on chemical, biological, and mechanical means, <i>Vibrio</i> control management faces limitations due to complicated implementation processes. This review explores the intricacies and challenges of <i>Vibrio</i>-related diseases, including accurate and cost-effective diagnosis and effective control. The global burden due to emerging <i>Vibrio</i> species further complicates management strategies. We propose an innovative integrated technology model that harnesses cutting-edge technologies to address these obstacles. The proposed model incorporates advanced tools, such as biosensing technologies, the Internet of Things (IoT), remote sensing devices, cloud computing, and machine learning. This model offers invaluable insights and supports better decision-making by integrating real-time ecological data and biological phenotype signatures. A major advantage of our approach lies in leveraging cloud-based analytics programs, efficiently extracting meaningful information from vast and complex datasets. Collaborating with data and clinical professionals ensures logical and customized solutions tailored to each unique situation. Aquaculture biotechnology that prioritizes sustainability may have a large impact on human health and the seafood industry. Our review underscores the importance of adopting this model, revolutionizing the prognosis and management of <i>Vibrio</i>-related infections, even under complex circumstances. Furthermore, this model has promising implications for aquaculture and public health, addressing the United Nations Sustainable Development Goals and their development agenda.
弧菌属（Vibrio）物种在全球范围内均构成严重威胁，可引发水产养殖动物大批量死亡，并导致人类感染疾病。全球变暖与弧菌病全球流行菌株的出现日益加剧，使得弧菌相关疾病的防控压力与日俱增。对弧菌属物种的防控需要在全球层面推行有效的监测、诊断与防治策略。尽管当前已基于化学、生物及机械手段开展了诸多防控工作，但弧菌防控管理仍因实施流程复杂而存在诸多局限。本综述探讨了弧菌相关疾病的复杂机制与防控挑战，涵盖精准且具成本效益的诊断方法与高效防控手段。新兴弧菌物种带来的全球疾病负担进一步复杂化了防控策略的制定与实施。我们提出了一种创新性的集成技术模型，该模型依托前沿技术以应对上述防控障碍。该模型整合了生物传感技术、物联网（Internet of Things, IoT）、遥感设备、云计算与机器学习等先进技术工具。该模型通过整合实时生态数据与生物表型特征，能够提供极具价值的分析视角，并辅助制定更优化的决策方案。本方案的核心优势在于依托基于云端的分析程序，可高效从海量复杂的数据集中提取有价值的信息。与数据及临床专业人员开展协作，能够确保针对不同具体场景制定合理且定制化的解决方案。以可持续发展为核心的水产养殖生物技术，有望对人类健康与海鲜产业产生深远影响。本综述强调了推广该模型的重要性，该模型可在复杂场景下革新弧菌相关感染的预后与管理模式。此外，该模型对水产养殖与公共卫生领域均具有良好的应用前景，可助力落实联合国可持续发展目标及其发展议程。
