Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance
<p>The apparent uncertainty associated with shedding patterns, environmental impacts, and sample processing strategies have greatly influenced the variability of SARS-CoV-2 concentrations in wastewater. This study evaluates the use of a new normalization approach using human RNase P for the lo...
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2022
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| _version_ | 1864513536471859200 |
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| author | Shimaa S. El-Malah (16931790) |
| author2 | Jayaprakash Saththasivam (14151669) Khadeeja Abdul Jabbar (17017752) Arun K.K. (17545767) Tricia A. Gomez (16931793) Ayeda A. Ahmed (11847025) Yasmin A. Mohamoud (10671696) Joel A. Malek (10327973) Laith J. Abu Raddad (16931811) Hussein A. Abu Halaweh (16931814) Roberto Bertollini (9538620) Jenny Lawler (16931817) Khaled A. Mahmoud (572646) |
| author2_role | author author author author author author author author author author author author |
| author_facet | Shimaa S. El-Malah (16931790) Jayaprakash Saththasivam (14151669) Khadeeja Abdul Jabbar (17017752) Arun K.K. (17545767) Tricia A. Gomez (16931793) Ayeda A. Ahmed (11847025) Yasmin A. Mohamoud (10671696) Joel A. Malek (10327973) Laith J. Abu Raddad (16931811) Hussein A. Abu Halaweh (16931814) Roberto Bertollini (9538620) Jenny Lawler (16931817) Khaled A. Mahmoud (572646) |
| author_role | author |
| dc.creator.none.fl_str_mv | Shimaa S. El-Malah (16931790) Jayaprakash Saththasivam (14151669) Khadeeja Abdul Jabbar (17017752) Arun K.K. (17545767) Tricia A. Gomez (16931793) Ayeda A. Ahmed (11847025) Yasmin A. Mohamoud (10671696) Joel A. Malek (10327973) Laith J. Abu Raddad (16931811) Hussein A. Abu Halaweh (16931814) Roberto Bertollini (9538620) Jenny Lawler (16931817) Khaled A. Mahmoud (572646) |
| dc.date.none.fl_str_mv | 2022-08-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.eti.2022.102775 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Application_of_human_RNase_P_normalization_for_the_realistic_estimation_of_SARS-CoV-2_viral_load_in_wastewater_A_perspective_from_Qatar_wastewater_surveillance/24720465 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biological sciences Microbiology Biomedical and clinical sciences Medical microbiology Environmental sciences Environmental management Health sciences Epidemiology SARS-CoV-2 monitoring Wastewater-based epidemiology (WBE) Municipal wastewater Wastewater surveillance Variant of concern Sequencing |
| dc.title.none.fl_str_mv | Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p>The apparent uncertainty associated with shedding patterns, environmental impacts, and sample processing strategies have greatly influenced the variability of SARS-CoV-2 concentrations in wastewater. This study evaluates the use of a new normalization approach using human RNase P for the logic estimation of SARS-CoV-2 viral load in wastewater. SARS-CoV-2 variants outbreak was monitored during the circulating wave between February and August 2021. Sewage samples were collected from five major wastewater treatment plants and subsequently analyzed to determine the viral loads in the wastewater. SARS-CoV-2 was detected in all the samples where the wastewater Ct values exhibited a similar trend as the reported number of new daily positive cases in the country. The infected population number was estimated using a mathematical model that compensated for RNA decay due to wastewater temperature and sewer residence time, and which indicated that the number of positive cases circulating in the population declined from 765,729 ± 142,080 to 2,303 ± 464 during the sampling period. Genomic analyses of SARS-CoV-2 of thirty wastewater samples collected between March 2021 and April 2021 revealed that alpha (B.1.1.7) and beta (B.1.351) were among the dominant variants of concern (VOC) in Qatar. The findings of this study imply that the normalization of data allows a more realistic assessment of incidence trends within the population.</p><h2>Other Information</h2> <p> Published in: Environmental Technology & Innovation<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.eti.2022.102775" target="_blank">https://dx.doi.org/10.1016/j.eti.2022.102775</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_55f94bf9d955a666ec1ae6864ee3e4c2 |
| identifier_str_mv | 10.1016/j.eti.2022.102775 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24720465 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillanceShimaa S. El-Malah (16931790)Jayaprakash Saththasivam (14151669)Khadeeja Abdul Jabbar (17017752)Arun K.K. (17545767)Tricia A. Gomez (16931793)Ayeda A. Ahmed (11847025)Yasmin A. Mohamoud (10671696)Joel A. Malek (10327973)Laith J. Abu Raddad (16931811)Hussein A. Abu Halaweh (16931814)Roberto Bertollini (9538620)Jenny Lawler (16931817)Khaled A. Mahmoud (572646)Biological sciencesMicrobiologyBiomedical and clinical sciencesMedical microbiologyEnvironmental sciencesEnvironmental managementHealth sciencesEpidemiologySARS-CoV-2 monitoringWastewater-based epidemiology (WBE)Municipal wastewaterWastewater surveillanceVariant of concernSequencing<p>The apparent uncertainty associated with shedding patterns, environmental impacts, and sample processing strategies have greatly influenced the variability of SARS-CoV-2 concentrations in wastewater. This study evaluates the use of a new normalization approach using human RNase P for the logic estimation of SARS-CoV-2 viral load in wastewater. SARS-CoV-2 variants outbreak was monitored during the circulating wave between February and August 2021. Sewage samples were collected from five major wastewater treatment plants and subsequently analyzed to determine the viral loads in the wastewater. SARS-CoV-2 was detected in all the samples where the wastewater Ct values exhibited a similar trend as the reported number of new daily positive cases in the country. The infected population number was estimated using a mathematical model that compensated for RNA decay due to wastewater temperature and sewer residence time, and which indicated that the number of positive cases circulating in the population declined from 765,729 ± 142,080 to 2,303 ± 464 during the sampling period. Genomic analyses of SARS-CoV-2 of thirty wastewater samples collected between March 2021 and April 2021 revealed that alpha (B.1.1.7) and beta (B.1.351) were among the dominant variants of concern (VOC) in Qatar. The findings of this study imply that the normalization of data allows a more realistic assessment of incidence trends within the population.</p><h2>Other Information</h2> <p> Published in: Environmental Technology & Innovation<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.eti.2022.102775" target="_blank">https://dx.doi.org/10.1016/j.eti.2022.102775</a></p>2022-08-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.eti.2022.102775https://figshare.com/articles/journal_contribution/Application_of_human_RNase_P_normalization_for_the_realistic_estimation_of_SARS-CoV-2_viral_load_in_wastewater_A_perspective_from_Qatar_wastewater_surveillance/24720465CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/247204652022-08-01T00:00:00Z |
| spellingShingle | Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance Shimaa S. El-Malah (16931790) Biological sciences Microbiology Biomedical and clinical sciences Medical microbiology Environmental sciences Environmental management Health sciences Epidemiology SARS-CoV-2 monitoring Wastewater-based epidemiology (WBE) Municipal wastewater Wastewater surveillance Variant of concern Sequencing |
| status_str | publishedVersion |
| title | Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance |
| title_full | Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance |
| title_fullStr | Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance |
| title_full_unstemmed | Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance |
| title_short | Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance |
| title_sort | Application of human RNase P normalization for the realistic estimation of SARS-CoV-2 viral load in wastewater: A perspective from Qatar wastewater surveillance |
| topic | Biological sciences Microbiology Biomedical and clinical sciences Medical microbiology Environmental sciences Environmental management Health sciences Epidemiology SARS-CoV-2 monitoring Wastewater-based epidemiology (WBE) Municipal wastewater Wastewater surveillance Variant of concern Sequencing |