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- Publisher Website: 10.1016/j.scitotenv.2024.175235
- Scopus: eid_2-s2.0-85200259089
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Article: Rapid and extensive SARS-CoV-2 Omicron variant infection wave revealed by wastewater surveillance in Shenzhen following the lifting of a strict COVID-19 strategy
| Title | Rapid and extensive SARS-CoV-2 Omicron variant infection wave revealed by wastewater surveillance in Shenzhen following the lifting of a strict COVID-19 strategy |
|---|---|
| Authors | Li, YinghuiDu, ChenLv, ZiquanWang, FuxiangZhou, LipingPeng, YuejingLi, WendingFu, YulinSong, JiangtengJia, ChunyanZhang, XinLiu, MujunWang, ZimiaoLiu, BinYan, ShulanYang, YuxiangLi, XueyunZhang, YongYuan, JianhuiXu, ShikuanChen, MiaolingShi, XiaoluPeng, BoChen, QiongchengQiu, YaqunWu, ShuangJiang, MinChen, MiaomeiTang, JinzhenWang, LeiHu, LuluWei, BincaiXia, YuJi, John S.Wan, ChengsongLu, HongzhouZhang, TongZou, XuanFu, SongzheHu, Qinghua |
| Keywords | Cryptic SARS-CoV-2 variant Faecal viral shedding Infection rate SARS-CoV-2 Omicron variant Wastewater surveillance |
| Issue Date | 1-Nov-2024 |
| Publisher | Elsevier |
| Citation | Science of the Total Environment, 2024, v. 949 How to Cite? |
| Abstract | Wastewater-based epidemiology (WBE) has emerged as a promising tool for monitoring the spread of COVID-19, as SARS-CoV-2 can be shed in the faeces of infected individuals, even in the absence of symptoms. This study aimed to optimize a prediction model for estimating COVID-19 infection rates based on SARS-CoV-2 RNA concentrations in wastewater, and reveal the infection trends and variant diversification in Shenzhen, China following the lifting of a strict COVID-19 strategy. Faecal samples (n = 4337) from 1204 SARS-CoV-2 infected individuals hospitalized in a designated hospital were analysed to obtain Omicron variant-specific faecal shedding dynamics. Wastewater samples from 6 wastewater treatment plants (WWTPs) and 9 pump stations, covering 3.55 million people, were monitored for SARS-CoV-2 RNA concentrations and variant abundance. We found that the viral load in wastewater increased rapidly in December 2022 in the two districts, demonstrating a sharp peak in COVID-19 infections in late-December 2022, mainly caused by Omicron subvariants BA.5.2.48 and BF.7.14. The prediction model, based on the mass balance between total viral load in wastewater and individual faecal viral shedding, revealed a surge in the cumulative infection rate from <0.1 % to over 70 % within three weeks after the strict COVID-19 strategy was lifted. Additionally, 39 cryptic SARS-CoV-2 variants were identified in wastewater, in addition to those detected through clinical surveillance. These findings demonstrate the effectiveness of WBE in providing comprehensive and efficient assessments of COVID-19 infection rates and identifying cryptic variants, highlighting its potential for monitoring emerging pathogens with faecal shedding. |
| Persistent Identifier | http://hdl.handle.net/10722/362550 |
| ISSN | 2023 Impact Factor: 8.2 2023 SCImago Journal Rankings: 1.998 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Li, Yinghui | - |
| dc.contributor.author | Du, Chen | - |
| dc.contributor.author | Lv, Ziquan | - |
| dc.contributor.author | Wang, Fuxiang | - |
| dc.contributor.author | Zhou, Liping | - |
| dc.contributor.author | Peng, Yuejing | - |
| dc.contributor.author | Li, Wending | - |
| dc.contributor.author | Fu, Yulin | - |
| dc.contributor.author | Song, Jiangteng | - |
| dc.contributor.author | Jia, Chunyan | - |
| dc.contributor.author | Zhang, Xin | - |
| dc.contributor.author | Liu, Mujun | - |
| dc.contributor.author | Wang, Zimiao | - |
| dc.contributor.author | Liu, Bin | - |
| dc.contributor.author | Yan, Shulan | - |
| dc.contributor.author | Yang, Yuxiang | - |
| dc.contributor.author | Li, Xueyun | - |
| dc.contributor.author | Zhang, Yong | - |
| dc.contributor.author | Yuan, Jianhui | - |
| dc.contributor.author | Xu, Shikuan | - |
| dc.contributor.author | Chen, Miaoling | - |
| dc.contributor.author | Shi, Xiaolu | - |
| dc.contributor.author | Peng, Bo | - |
| dc.contributor.author | Chen, Qiongcheng | - |
| dc.contributor.author | Qiu, Yaqun | - |
| dc.contributor.author | Wu, Shuang | - |
| dc.contributor.author | Jiang, Min | - |
| dc.contributor.author | Chen, Miaomei | - |
| dc.contributor.author | Tang, Jinzhen | - |
| dc.contributor.author | Wang, Lei | - |
| dc.contributor.author | Hu, Lulu | - |
| dc.contributor.author | Wei, Bincai | - |
| dc.contributor.author | Xia, Yu | - |
| dc.contributor.author | Ji, John S. | - |
| dc.contributor.author | Wan, Chengsong | - |
| dc.contributor.author | Lu, Hongzhou | - |
| dc.contributor.author | Zhang, Tong | - |
| dc.contributor.author | Zou, Xuan | - |
| dc.contributor.author | Fu, Songzhe | - |
| dc.contributor.author | Hu, Qinghua | - |
| dc.date.accessioned | 2025-09-26T00:36:05Z | - |
| dc.date.available | 2025-09-26T00:36:05Z | - |
| dc.date.issued | 2024-11-01 | - |
| dc.identifier.citation | Science of the Total Environment, 2024, v. 949 | - |
| dc.identifier.issn | 0048-9697 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/362550 | - |
| dc.description.abstract | <p>Wastewater-based epidemiology (WBE) has emerged as a promising tool for monitoring the spread of COVID-19, as SARS-CoV-2 can be shed in the faeces of infected individuals, even in the absence of symptoms. This study aimed to optimize a prediction model for estimating COVID-19 infection rates based on SARS-CoV-2 RNA concentrations in wastewater, and reveal the infection trends and variant diversification in Shenzhen, China following the lifting of a strict COVID-19 strategy. Faecal samples (n = 4337) from 1204 SARS-CoV-2 infected individuals hospitalized in a designated hospital were analysed to obtain Omicron variant-specific faecal shedding dynamics. Wastewater samples from 6 wastewater treatment plants (WWTPs) and 9 pump stations, covering 3.55 million people, were monitored for SARS-CoV-2 RNA concentrations and variant abundance. We found that the viral load in wastewater increased rapidly in December 2022 in the two districts, demonstrating a sharp peak in COVID-19 infections in late-December 2022, mainly caused by Omicron subvariants BA.5.2.48 and BF.7.14. The prediction model, based on the mass balance between total viral load in wastewater and individual faecal viral shedding, revealed a surge in the cumulative infection rate from <0.1 % to over 70 % within three weeks after the strict COVID-19 strategy was lifted. Additionally, 39 cryptic SARS-CoV-2 variants were identified in wastewater, in addition to those detected through clinical surveillance. These findings demonstrate the effectiveness of WBE in providing comprehensive and efficient assessments of COVID-19 infection rates and identifying cryptic variants, highlighting its potential for monitoring emerging pathogens with faecal shedding.</p> | - |
| dc.language | eng | - |
| dc.publisher | Elsevier | - |
| dc.relation.ispartof | Science of the Total Environment | - |
| dc.subject | Cryptic SARS-CoV-2 variant | - |
| dc.subject | Faecal viral shedding | - |
| dc.subject | Infection rate | - |
| dc.subject | SARS-CoV-2 Omicron variant | - |
| dc.subject | Wastewater surveillance | - |
| dc.title | Rapid and extensive SARS-CoV-2 Omicron variant infection wave revealed by wastewater surveillance in Shenzhen following the lifting of a strict COVID-19 strategy | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1016/j.scitotenv.2024.175235 | - |
| dc.identifier.scopus | eid_2-s2.0-85200259089 | - |
| dc.identifier.volume | 949 | - |
| dc.identifier.eissn | 1879-1026 | - |
| dc.identifier.issnl | 0048-9697 | - |
