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Early Warning of COVID-19 in Tokyo via Wastewater-based Epidemiology: How Feasible It Really Is?
- Source :
- Journal of Water and Environment Technology, Vol 19, Iss 3, Pp 170-183 (2021)
- Publication Year :
- 2021
- Publisher :
- Japan Society on Water Environment, 2021.
-
Abstract
- Amid the ongoing battle against COVID-19, the scientific community has high hope in wastewaterbased epidemiology (WBE). It was not only proposed as a complement to capacity-plagued clinical testing, but also an early warning tool that may enable timely intervention measures. In this study, we developed a wastewater SARS-CoV-2 RNA load model based on the fecal shedding profile of infected individuals. The epidemic data of COVID-19 in the Tokyo metropolitan area were used to perform a simulation to analyze the capability of WBE in providing early warning. The simulation result suggests that under the current settings, WBE is not a feasible approach as the detection limit is too high to provide a warning signal in the early stage of the epidemic. However, it also indicates that if the methodology can be reasonably improved by new experimental practices, optimized sampling strategy, and refined model, the concentration of viral RNA in Tokyo wastewater would exceed the detection limit as early as in April 2020, when Tokyo was being hit by the first wave of COVID-19 outbreak. This early detection may have great social benefit if the detection can be used to facilitate the decision-making process and form epidemic emergency response. © 2021. All Rights Reserved.
- Subjects :
- TC401-506
Environmental Engineering
Coronavirus disease 2019 (COVID-19)
Warning system
epidemic early warning
Computer science
Health, Toxicology and Mutagenesis
Ecological Modeling
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Early detection
Wastewater based epidemiology
Environmental technology. Sanitary engineering
Pollution
wastewater-based epidemiology
River, lake, and water-supply engineering (General)
Emergency response
covid-19
fecal shedding
Intervention measures
Risk analysis (engineering)
dynamic modeling
Viral rna
Waste Management and Disposal
TD1-1066
Water Science and Technology
Subjects
Details
- ISSN :
- 13482165
- Volume :
- 19
- Database :
- OpenAIRE
- Journal :
- Journal of Water and Environment Technology
- Accession number :
- edsair.doi.dedup.....a7cb433b1797e1e574089e531b579fef
- Full Text :
- https://doi.org/10.2965/jwet.21-024