File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Evaluation of RT-qPCR Primer-Probe Sets to Inform Public Health Interventions Based on COVID-19 Sewage Tests

TitleEvaluation of RT-qPCR Primer-Probe Sets to Inform Public Health Interventions Based on COVID-19 Sewage Tests
Authors
Issue Date2022
Citation
Environmental Science & Technology, 2022, v. 56, p. 8875-8884 How to Cite?
AbstractAbstract Sewage surveillance is increasingly employed as a supplementary tool for COVID-19 control. Experiences learnt from large-scale trials could guide better interpretation of the sewage data for public health interventions. Here, we compared the performance of seven commonly used primer-probe sets in RT-qPCR and evaluated the usefulness in the sewage surveillance program in Hong Kong. All selected primer-probe sets reliably detected SARS-CoV-2 in pure water at 7 copies per μL. Sewage matrix did not influence RT-qPCR determination of SARS-CoV-2 concentrated from a small-volume sewage (30 mL) but introduced inhibitory impacts on a large-volume sewage (920 mL) with a ΔCt of 0.2-10.8. Diagnostic performance evaluation in finding COVID-19 cases showed that N1 was the best single primer-probe set, while the ORF1ab set is not recommended. Sewage surveillance using the N1 set for over 3200 samples effectively caught the outbreak trend and, importantly, had a 56% sensitivity and a 96% specificity in uncovering the signal sources from new cases and/or convalescent patients in the community. Our study paves the way for selecting detection primer-probe sets in wider applications in responding to the COVID-19 pandemic.
Persistent Identifierhttp://hdl.handle.net/10722/314114
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXu, X-
dc.contributor.authorDeng, Y-
dc.contributor.authorZheng, X-
dc.contributor.authorLi, S-
dc.contributor.authorDing, J-
dc.contributor.authorYang, Y-
dc.contributor.authorOn, HY-
dc.contributor.authorYang, RONG-
dc.contributor.authorChui, HO-KWONG-
dc.contributor.authorYau, CY-
dc.contributor.authorTun, HM-
dc.contributor.authorChin, WH-
dc.contributor.authorPoon, LML-
dc.contributor.authorPeiris, JSM-
dc.contributor.authorLeung, GM-
dc.contributor.authorZhang, T-
dc.date.accessioned2022-07-18T06:11:59Z-
dc.date.available2022-07-18T06:11:59Z-
dc.date.issued2022-
dc.identifier.citationEnvironmental Science & Technology, 2022, v. 56, p. 8875-8884-
dc.identifier.urihttp://hdl.handle.net/10722/314114-
dc.description.abstractAbstract Sewage surveillance is increasingly employed as a supplementary tool for COVID-19 control. Experiences learnt from large-scale trials could guide better interpretation of the sewage data for public health interventions. Here, we compared the performance of seven commonly used primer-probe sets in RT-qPCR and evaluated the usefulness in the sewage surveillance program in Hong Kong. All selected primer-probe sets reliably detected SARS-CoV-2 in pure water at 7 copies per μL. Sewage matrix did not influence RT-qPCR determination of SARS-CoV-2 concentrated from a small-volume sewage (30 mL) but introduced inhibitory impacts on a large-volume sewage (920 mL) with a ΔCt of 0.2-10.8. Diagnostic performance evaluation in finding COVID-19 cases showed that N1 was the best single primer-probe set, while the ORF1ab set is not recommended. Sewage surveillance using the N1 set for over 3200 samples effectively caught the outbreak trend and, importantly, had a 56% sensitivity and a 96% specificity in uncovering the signal sources from new cases and/or convalescent patients in the community. Our study paves the way for selecting detection primer-probe sets in wider applications in responding to the COVID-19 pandemic.-
dc.languageeng-
dc.relation.ispartofEnvironmental Science & Technology-
dc.titleEvaluation of RT-qPCR Primer-Probe Sets to Inform Public Health Interventions Based on COVID-19 Sewage Tests-
dc.typeArticle-
dc.identifier.emailDeng, Y: dengyu@hku.hk-
dc.identifier.emailYang, Y: yangyuyy@hku.hk-
dc.identifier.emailYau, CY: tansyy@hku.hk-
dc.identifier.emailTun, HM: heinmtun@hku.hk-
dc.identifier.emailChin, WH: alexchin@hku.hk-
dc.identifier.emailPoon, LML: llmpoon@hkucc.hku.hk-
dc.identifier.emailPeiris, JSM: malik@hkucc.hku.hk-
dc.identifier.emailLeung, GM: gmleung@hku.hk-
dc.identifier.emailZhang, T: zhangt@hkucc.hku.hk-
dc.identifier.authorityDeng, Y=rp02795-
dc.identifier.authorityTun, HM=rp02389-
dc.identifier.authorityChin, WH=rp02345-
dc.identifier.authorityPoon, LML=rp00484-
dc.identifier.authorityPeiris, JSM=rp00410-
dc.identifier.authorityLeung, GM=rp00460-
dc.identifier.authorityZhang, T=rp00211-
dc.identifier.doi10.1021/acs.est.2c00974-
dc.identifier.hkuros334277-
dc.identifier.volume56-
dc.identifier.spage8875-
dc.identifier.epage8884-
dc.identifier.isiWOS:000815255700001-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats