A year into the COVID-19 pandemic: Rethinking of wastewater monitoring as a preemptive approach

新冠疫情爆发一年后:重新思考废水监测作为一种预防性方法

阅读:1

Abstract

Under the current pandemic situation caused by the novel coronavirus SARS-CoV-2, wastewater monitoring has been increasingly investigated as a surveillance tool for community-wide disease prevalence. After a year into the pandemic, this review critically discusses the real progress made in the detection of SARS-CoV-2 using wastewater monitoring. The limitations and the key challenges faced in improving the detection methods are highlighted. As per the literature, the complex nature of the wastewater matrix poses problems in processing the samples and achieving high sensitivity at low loads of viral RNA using the current detection methods. Furthermore, in the absence of a gold standard analytical method for wastewater, the validation of the generated data for use in wastewater-based epidemiological modeling of the disease becomes practically difficult. However, research is advancing in adopting clinical methods to the wastewater by using appropriate processing controls, and recovery methods. Besides, the technological advances made by the industry including the development of PCR kits with improved detection limits, easy-to-use viral RNA concentration methods, ability to detect the coronavirus variants, and artificial intelligence and advanced data modeling for continuous and remote monitoring greatly help to debottleneck some of these problems. Currently, these technologies are limited to healthcare systems, however, their use for wastewater monitoring is expected to provide opportunities for wide-scale applications of wastewater-based epidemiology (WBE). Moreover, the data from wastewater monitoring act as the initial checkpoint for human health even before the appearance of symptoms, hence WBE needs more attention to manage current and future infectious transmissions.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。