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dc.contributor.authorHong, Pei-Ying
dc.contributor.authorRachmadi, Andri Taruna
dc.contributor.authorMantilla Calderon, David
dc.contributor.authorAlkahtani, Mohsen
dc.contributor.authorBashawri, Yasir M
dc.contributor.authorAl Qarni, Hamed
dc.contributor.authorO'Reilly, Kathleen M
dc.contributor.authorZhou, Jianqiang
dc.date.accessioned2021-02-01T13:19:03Z
dc.date.available2021-02-01T13:19:03Z
dc.date.issued2021-01-19
dc.date.submitted2020-10-07
dc.identifier.citationHong, P.-Y., Rachmadi, A. T., Mantilla-Calderon, D., Alkahtani, M., Bashawri, Y. M., Al Qarni, H., … Zhou, J. (2021). Estimating the minimum number of SARS-CoV-2 infected cases needed to detect viral RNA in wastewater: To what extent of the outbreak can surveillance of wastewater tell us? Environmental Research, 110748. doi:10.1016/j.envres.2021.110748
dc.identifier.issn0013-9351
dc.identifier.pmid33465345
dc.identifier.doi10.1016/j.envres.2021.110748
dc.identifier.urihttp://hdl.handle.net/10754/667171
dc.description.abstractThere is increasing interest in wastewater-based epidemiology (WBE) of SARS-CoV-2 RNA to serve as an early warning system for a community. Despite successful detection of SARS-CoV-2 RNA in wastewaters sampled from multiple locations, there is still no clear idea on the minimal number of cases in a community that are associated with a positive detection of the virus in wastewater. To address this knowledge gap, we sampled wastewaters from a septic tank (n = 57) and biological activated sludge tank (n = 52) located on-site of a hospital. The hospital is providing treatment for SARS-CoV-2 infected patients, with the number of hospitalized patients per day known. It was observed that depending on which nucleocapsid gene is targeted by means of RT-qPCR, a range of 253-409 positive cases out of 10,000 persons are required prior to detecting RNA SARS-CoV-2 in wastewater. There was a weak correlation between N1 and N2 gene abundances in wastewater with the number of hospitalized cases. This correlation was however not observed for N3 gene. The frequency of detecting N1 and N2 gene in wastewater was also higher than that for N3 gene. Furthermore, nucleocapsid genes of SARS-CoV-2 were detected at lower frequency in the partially treated wastewater than in the septic tank. In particular, N1 gene abundance was associated with water quality parameters such as total organic carbon and pH. In instances of positive detection, the average abundance of N1 and N3 genes in the activated sludge tank were reduced by 50 and 70% of the levels detected in septic tank, suggesting degradation of the SARS-CoV-2 gene fragments already occurring in the early stages of the wastewater treatment process.
dc.description.sponsorshipThe authors would like to thank the medical team of the studied hospital for providing access to wastewater samples and for saving lives during this pandemic. The authors would also like to thank Professor Arnab Pain for providing the RNA sample that serves as positive control, Professor Matthew McCabe and Mr Samir Almashharawi for providing the ambient temperature and solar irradiance measured at the Hada Al Sham monitoring station.
dc.publisherElsevier BV
dc.relation.urlhttps://linkinghub.elsevier.com/retrieve/pii/S0013935121000426
dc.rightsThis is an open access article under the CC BY-NC-ND license.
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleEstimating the minimum number of SARS-CoV-2 infected cases needed to detect viral RNA in wastewater: To what extent of the outbreak can surveillance of wastewater tell us?
dc.typeArticle
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentEnvironmental Microbial Safety and Biotechnology Lab
dc.contributor.departmentEnvironmental Science and Engineering Program
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)
dc.identifier.journalEnvironmental research
dc.identifier.pmcidPMC7831732
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionEnvironmental Health Laboratory, Jeddah, Ministry of Health, Saudi Arabia.
dc.contributor.institutionGeneral Directorate of Environment Health, Ministry of Health, Saudi Arabia.
dc.contributor.institutionFaculty of Epidemiology and Population Health and Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, UK.
dc.identifier.pages110748
kaust.personHong, Pei-Ying
kaust.personRachmadi, Andri Taruna
kaust.personMantilla, David
kaust.personZhou, Jianqiang
dc.date.accepted2021-01-11
refterms.dateFOA2021-02-01T13:22:21Z


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