4.7 Article

Surveillance of Wastewater for Early Epidemic Prediction (SWEEP): Environmental and health security perspectives in the post COVID-19 Anthropocene

期刊

ENVIRONMENTAL RESEARCH
卷 195, 期 -, 页码 -

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2021.110831

关键词

COVID-19; Early warning system; SARS-CoV-2; Surveillance of wastewater for early epidemic; prediction (SWEEP); PCR-based assays

资金

  1. Department of Biotechnology-Government of India [BT/RLF/Re-entry/12/2016]

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The study summarizes the application of wastewater-based epidemiology in COVID-19 research and introduces the SWEEP framework for future epidemic prevention. Additionally, the research found that lockdown measures have a positive impact on reducing viral loads in wastewater, providing important insights for epidemic control.
The present work summarizes the major research findings related to wastewater-based epidemiology (WBE) study of COVID-19 and puts forward a conceptual framework, termed as Surveillance of Wastewater for Early Epidemic Prediction (SWEEP) for implementation of WBE. SWEEP framework is likely to tackle few practical issues related to WBE and simultaneously proposes refinements to the approach for better outcome and efficiency to save precious lives around the globe. It is observed that the present pandemic offers an opportunity for SWEEP to get included in routine urban water management to put the humankind at front to stop such pandemic in future or at least be prepared to fight against it. With global collaboration, SWEEP can be fine-tuned to meet diverse needs, making the present and future generations resilient to future viral outbreaks. Recent WBE studies conducted to check for the presence of SARS-CoV-2 in wastewater revealed that raw sewage samples tested positive to PCR-based assays while the treated samples showed absence of viral titers. Moreover, the lockdown had a positive impact on decreasing the viral loading in sewage. The proposed SWEEP protocol has an advantage over testifying individuals for predicting the stage of pandemic.

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