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Waterborne pathogen mitigation: decoding techno-ecological synergies in multiscale transmission networks

dc.contributor.authorTeng, Miaomiao
dc.contributor.authorHuo, Zheng-Yang
dc.contributor.authorZhang, Zixuan
dc.contributor.authorXie, Ming
dc.contributor.authorWang, Xiaoxiong
dc.contributor.authorWu, Qianyuan
dc.contributor.authorYang, Zhugen
dc.contributor.authorBowen, Chris R.
dc.contributor.authorZhang, Wei
dc.contributor.authorLiu, Gang
dc.contributor.authorWu, Fengchang
dc.date.accessioned2025-11-05T14:51:08Z
dc.date.available2025-11-05T14:51:08Z
dc.date.freetoread2025-11-05
dc.date.issued2025-10-01
dc.date.pubOnline2025-10-13
dc.description.abstractPathogen spread and infection represent paramount global challenges, their intricate transmission pathways fundamentally shaped by human behavior and anthropogenic influences. Here, we elucidate pathogen transmission networks in the environment and identify the increasing risks resulting from mutant viruses and resistant bacteria. We examine the advantages and limitations of techniques for pathogen detection and advocate the development of real-time, high-precision, point-of-need assays capable of detecting microorganisms in waterborne matrices, providing a new conceptual and technological approach to future detection methods. We also highlight the inadequate protection of existing centralized disinfection methods and propose the implementation of decentralized disinfection (i.e., chemical-free and energy-efficient point-of-use disinfection) as a form of multi-barrier protection throughout the different pathways of pathogen transmission. A robust and resilient ecosystem can prevent containment sources and inhibit the bioactivity of residual pathogens, and when working in synergy with multi-barrier disinfection, can achieve a techno-ecological framework for pathogen mitigation. We further address the fact that data-driven technologies (e.g., artificial neural networks and machine learning methods) provide a route for intelligent detection-guided disinfection and the accurate selection of pathogen indicators that are directly relevant to human health. Finally, we highlight concerns regarding potential high-risk pathogens due to climate change.
dc.description.journalNameThe Innovation
dc.description.sponsorshipThis work was supported by the National Key R&D Program of China (grants 2022YFC3205400 and 2022YFC3204703), the National Natural Science Foundation of China (grant 52200079), and the UKRI Horizon Europe Guarantee funding of Marie Skłodowska-Curie Actions Postdoctoral Fellowship (grant EP/X022730/1).
dc.identifier.citationTeng M, Huo Z-Y, Zhang Z, et al., (2025) Waterborne pathogen mitigation: decoding techno-ecological synergies in multiscale transmission networks. The Innovation, Volume 7, Issue 3, March 2026, Article number 101145en_UK
dc.identifier.elementsID866152
dc.identifier.issn2666-6758
dc.identifier.issueNo3
dc.identifier.paperNo101145
dc.identifier.urihttps://doi.org/10.1016/j.xinn.2025.101145
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/24632
dc.identifier.volumeNo7
dc.languageEnglish
dc.language.isoen
dc.publisherElsevieren_UK
dc.publisher.urihttps://www.cell.com/the-innovation/fulltext/S2666-6758(25)00348-0?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2666675825003480%3Fshowall%3Dtrue
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject46 Information and Computing Sciencesen_UK
dc.subject3207 Medical Microbiologyen_UK
dc.subject32 Biomedical and Clinical Sciencesen_UK
dc.subjectMachine Learning and Artificial Intelligenceen_UK
dc.subjectPreventionen_UK
dc.subjectInfectious Diseasesen_UK
dc.subject2.2 Factors relating to the physical environmenten_UK
dc.subjectInfectionen_UK
dc.subject3 Good Health and Well Beingen_UK
dc.subjectenvironmental pathogenen_UK
dc.subjectreal-time detectionen_UK
dc.subjectecological resilienceen_UK
dc.subjectdecentralized disinfectionen_UK
dc.subjectdata-driven pathogen controlen_UK
dc.titleWaterborne pathogen mitigation: decoding techno-ecological synergies in multiscale transmission networksen_UK
dc.typeArticle
dcterms.dateAccepted2025-10-10

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