Optimal allocation and operation of sewer monitoring sites for wastewater-based disease surveillance: A methodological proposal
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, K. | - |
dc.contributor.author | Ban, M.J. | - |
dc.contributor.author | Kim, S. | - |
dc.contributor.author | Park, M.-H. | - |
dc.contributor.author | Stenstrom, M.K. | - |
dc.contributor.author | Kang, J.-H. | - |
dc.date.accessioned | 2022-08-27T04:40:28Z | - |
dc.date.available | 2022-08-27T04:40:28Z | - |
dc.date.created | 2022-08-25 | - |
dc.date.issued | 2022-10 | - |
dc.identifier.issn | 0301-4797 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/143548 | - |
dc.description.abstract | Wastewater-based epidemiology (WBE) is drawing increasing attention as a promising tool for an early warning of emerging infectious diseases such as COVID-19. This study demonstrated the utility of a spatial bisection method (SBM) and a global optimization algorithm (i.e., genetic algorithm, GA), to support better designing and operating a WBE program for disease surveillance and source identification. The performances of SBM and GA were compared in determining the optimal locations of sewer monitoring manholes to minimize the difference among the effective spatial monitoring scales of the selected manholes. While GA was more flexible in determining the spatial resolution of the monitoring areas, SBM allows stepwise selection of optimal sampling manholes with equiareal subcatchments and lowers computational cost. Upon detecting disease outbreaks at a regular sewer monitoring site, additional manholes within the catchment can be selected and monitored to identify source areas with a required spatial resolution. SBM offered an efficient method for rapidly searching for the optimal locations of additional sampling manholes to identify the source areas. This study provides strategic and technical elements of WBE including sampling site selection with required spatial resolution and a source identification method. © 2022 Elsevier Ltd | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | Academic Press | - |
dc.title | Optimal allocation and operation of sewer monitoring sites for wastewater-based disease surveillance: A methodological proposal | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, S. | - |
dc.identifier.doi | 10.1016/j.jenvman.2022.115806 | - |
dc.identifier.scopusid | 2-s2.0-85135384244 | - |
dc.identifier.wosid | 000891240400005 | - |
dc.identifier.bibliographicCitation | Journal of Environmental Management, v.320 | - |
dc.relation.isPartOf | Journal of Environmental Management | - |
dc.citation.title | Journal of Environmental Management | - |
dc.citation.volume | 320 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
dc.subject.keywordPlus | ENVIRONMENTAL SURVEILLANCE | - |
dc.subject.keywordPlus | EPIDEMIOLOGY | - |
dc.subject.keywordPlus | OPTIMIZATION | - |
dc.subject.keywordPlus | COVID-19 | - |
dc.subject.keywordPlus | SEWAGE | - |
dc.subject.keywordPlus | VIRUS | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordAuthor | Bisection method | - |
dc.subject.keywordAuthor | COVID-19 | - |
dc.subject.keywordAuthor | Early warning | - |
dc.subject.keywordAuthor | Emerging infectious diseases | - |
dc.subject.keywordAuthor | Genetic algorithm | - |
dc.subject.keywordAuthor | Wastewater-based epidemiology | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.