Early Warning of COVID-19 in Tokyo Via Wastewater-Based Epidemiology: How Feasible It Really Is?

Yifan Zhu, Wakana Oishi, Mayuko Saito, Masaaki Kitajima, Daisuke Sano

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)170-183
Number of pages14
JournalJournal of Water and Environment Technology
Volume19
Issue number3
DOIs
Publication statusPublished - 2021

Keywords

  • COVID-19
  • dynamic modeling
  • epidemic early warning
  • fecal shedding
  • wastewater-based epidemiology

ASJC Scopus subject areas

  • Environmental Engineering
  • Ecological Modelling
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution
  • Health, Toxicology and Mutagenesis

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