Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Optimal allocation and operation of sewer monitoring sites for wastewater-based disease surveillance: A methodological proposalopen access

Authors
Kim, K.Ban, M.J.Kim, S.Park, M.-H.Stenstrom, M.K.Kang, J.-H.
Issue Date
10월-2022
Publisher
Academic Press
Keywords
Bisection method; COVID-19; Early warning; Emerging infectious diseases; Genetic algorithm; Wastewater-based epidemiology
Citation
Journal of Environmental Management, v.320
Indexed
SCIE
SCOPUS
Journal Title
Journal of Environmental Management
Volume
320
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/143548
DOI
10.1016/j.jenvman.2022.115806
ISSN
0301-4797
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
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Environmental Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Sung pyo photo

Kim, Sung pyo
환경공학과
Read more

Altmetrics

Total Views & Downloads

BROWSE