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

研究成果: Article査読

3 被引用数 (Scopus)


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.

ジャーナルJournal of Water and Environment Technology
出版ステータスPublished - 2021

ASJC Scopus subject areas

  • 環境工学
  • 生態モデリング
  • 水の科学と技術
  • 廃棄物管理と処理
  • 汚染
  • 健康、毒物学および変異誘発


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