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10.1016/j.scitotenv.2021.145608 http://scihub22266oqcxt.onion/10.1016/j.scitotenv.2021.145608 33607430!7870436!33607430     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33607430&cmd=llinks): Failed to open stream: HTTP request failed! 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COVID-19 (SARS-CoV-2) outbreak monitoring using wastewater-based epidemiology in Qatar |pdf=|usr=}}{{33607430}} gab.com Text COVID-19 (SARS-CoV-2) outbreak monitoring using wastewater-based epidemiology in Qatar JO: Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=33607430 #FOAvip Raw municipal wastewater from five wastewater treatment plants representing the vast majority of the Qatar population was sampled between the third week of June 2020 and the end of August 2020, during the period of declining cases after the peak of the first wave of infection in May 2020. The N1 region of the SARS-CoV-2 genome was used to quantify the viral load in the wastewater using RT-qPCR. The trend in Ct values in the wastewater samples mirrored the number of new daily positive cases officially reported for the country, confirmed by RT-qPCR testing of naso-pharyngeal swabs. SARS-CoV-2 RNA was detected in 100% of the influent wastewater samples (7889 +/- 1421 copy/L - 542,056 +/- 25,775 copy/L, based on the N1 assay). A mathematical model for wastewater-based epidemiology was developed and used to estimate the number of people in the population infected with COVID-19 from the N1 Ct values in the wastewater samples. The estimated number of infected population on any given day using the wastewater-based epidemiology approach declined from 542,313 +/- 51,159 to 31,181 +/- 3081 over the course of the sampling period, which was significantly higher than the officially reported numbers. However, seroprevalence data from Qatar indicates that diagnosed infections represented only about 10% of actual cases. The model estimates were lower than the corrected numbers based on application of a static diagnosis ratio of 10% to the RT-qPCR identified cases, which is assumed to be due to the difficulty in quantifying RNA losses as a model term. However, these results indicate that the presented WBE modeling approach allows for a realistic assessment of incidence trend in a given population, with a more reliable estimation of the number of infected people at any given point in time than can be achieved using human biomonitoring alone. Twit Text FOAVip COVID-19 (SARS-CoV-2) outbreak monitoring using wastewater-based epidemiology in Qatar ????Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=33607430 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33607430 #FOAvip English Wikipedia <ref>{{Cite pmid|33607430}}</ref> COVID-19 (SARS-CoV-2) outbreak monitoring using wastewater-based epidemiology in Qatar #MMPMID33607430 Saththasivam J; El-Malah SS; Gomez TA; Jabbar KA; Remanan R; Krishnankutty AK; Ogunbiyi O; Rasool K; Ashhab S; Rashkeev S; Bensaad M; Ahmed AA; Mohamoud YA; Malek JA; Abu Raddad LJ; Jeremijenko A; Abu Halaweh HA; Lawler J; Mahmoud KA Sci Total Environ 2021[Jun]; 774 (ä): 145608 PMID33607430show ga Raw municipal wastewater from five wastewater treatment plants representing the vast majority of the Qatar population was sampled between the third week of June 2020 and the end of August 2020, during the period of declining cases after the peak of the first wave of infection in May 2020. The N1 region of the SARS-CoV-2 genome was used to quantify the viral load in the wastewater using RT-qPCR. The trend in Ct values in the wastewater samples mirrored the number of new daily positive cases officially reported for the country, confirmed by RT-qPCR testing of naso-pharyngeal swabs. SARS-CoV-2 RNA was detected in 100% of the influent wastewater samples (7889 +/- 1421 copy/L - 542,056 +/- 25,775 copy/L, based on the N1 assay). A mathematical model for wastewater-based epidemiology was developed and used to estimate the number of people in the population infected with COVID-19 from the N1 Ct values in the wastewater samples. The estimated number of infected population on any given day using the wastewater-based epidemiology approach declined from 542,313 +/- 51,159 to 31,181 +/- 3081 over the course of the sampling period, which was significantly higher than the officially reported numbers. However, seroprevalence data from Qatar indicates that diagnosed infections represented only about 10% of actual cases. The model estimates were lower than the corrected numbers based on application of a static diagnosis ratio of 10% to the RT-qPCR identified cases, which is assumed to be due to the difficulty in quantifying RNA losses as a model term. However, these results indicate that the presented WBE modeling approach allows for a realistic assessment of incidence trend in a given population, with a more reliable estimation of the number of infected people at any given point in time than can be achieved using human biomonitoring alone. |*COVID-19[MESH] |*SARS-CoV-2[MESH] |Disease Outbreaks[MESH] |Humans[MESH] |Qatar/epidemiology[MESH] |RNA, Viral[MESH] |Seroepidemiologic Studies[MESH] |Wastewater[MESH]COVID-19 (SARS-CoV-2) outbreak monitoring using wastewater-based epide(epmc).pdf DeepDyve Pubget Overpricing