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

DOI Web Site 被引用文献3件 参考文献58件
  • Zhu Yifan
    Department of Frontier Sciences for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Sendai, Japan
  • Oishi Wakana
    Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai, Japan
  • Saito Mayuko
    Department of Virology, Graduate School of Medicine, Tohoku University, Sendai, Japan
  • Kitajima Masaaki
    Division of Environmental Engineering, Faculty of Engineering, Hokkaido University, Sapporo, Japan
  • Sano Daisuke
    Department of Frontier Sciences for Advanced Environment, Graduate School of Environmental Studies, Tohoku University, Sendai, Japan Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Sendai, Japan

抄録

<p>Amid the ongoing battle against COVID-19, the scientific community has high hope in wastewater-based 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.</p>

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