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dc.contributor.authorVallejo, J. A.
dc.contributor.authorTrigo Tasende, Noelia
dc.contributor.authorRumbo-Feal, Soraya
dc.contributor.authorConde-Pérez, Kelly
dc.contributor.authorLópez-Oriona, Ángel
dc.contributor.authorBarbeito, Inés
dc.contributor.authorVaamonde, Manuel
dc.contributor.authorTarrío-Saavedra, Javier
dc.contributor.authorReif López, Rubén
dc.contributor.authorLadra, Susana
dc.contributor.authorRodiño-Janeiro, Bruno Kotska
dc.contributor.authorNasser-Ali, Mohammed
dc.contributor.authorCid, Ángeles
dc.contributor.authorVeiga, María Carmen
dc.contributor.authorAcevedo, Antón
dc.contributor.authorLamora, Carlos
dc.contributor.authorBou, Germán
dc.contributor.authorCao, Ricardo
dc.contributor.authorPoza, Margarita
dc.date.accessioned2022-03-22T19:41:48Z
dc.date.available2022-03-22T19:41:48Z
dc.date.issued2022
dc.identifier.citationVALLEJO, Juan A., TRIGO-TASENDE, Noelia, RUMBO-FEAL, Soraya, CONDE-PÉREZ, Kelly, LÓPEZ-ORIONA, Ángel, BARBEITO, Inés, VAAMONDE, Manuel, TARRÍO-SAAVEDRA, Javier, REIF, Rubén, LADRA, Susana, RODIÑO-JANEIRO, Bruno K., NASSER-ALI, Mohammed, CID, Ángeles, VEIGA, María, ACEVEDO, Antón, LAMORA, Carlos, BOU, Germán, CAO, Ricardo and POZA, Margarita, 2022. Modeling the number of people infected with SARS-COV-2 from wastewater viral load in Northwest Spain. Science of The Total Environment. 10 March 2022. Vol. 811, p. 152334. DOI 10.1016/j.scitotenv.2021.152334.es_ES
dc.identifier.urihttp://hdl.handle.net/2183/30143
dc.descriptionFinanciado para publicación en acceso aberto: Universidade da Coruña/CISUGes_ES
dc.description.abstract[Abstract] The quantification of the SARS-CoV-2 RNA load in wastewater has emerged as a useful tool to monitor COVID–19 outbreaks in the community. This approach was implemented in the metropolitan area of A Coruña (NW Spain), where wastewater from a treatment plant was analyzed to track the epidemic dynamics in a population of 369,098 inhabitants. Viral load detected in the wastewater and the epidemiological data from A Coruña health system served as main sources for statistical models developing. Regression models described here allowed us to estimate the number of infected people (R2 = 0.9), including symptomatic and asymptomatic individuals. These models have helped to understand the real magnitude of the epidemic in a population at any given time and have been used as an effective early warning tool for predicting outbreaks in A Coruña municipality. The methodology of the present work could be used to develop a similar wastewater-based epidemiological model to track the evolution of the COVID–19 epidemic anywhere in the world where centralized water-based sanitation systems exist.es_ES
dc.description.sponsorshipThis work was supported by EDAR Bens S.A., A Coruña, Spain [grant references INV04020, INV12120 and INV05921 to MP], the National Plan for Scientific Research, Development and Technological Innovation 2013-2016 funded by the ISCIII, Spain - General Subdirection of Assessment and Promotion of the Research-European Regional Development Fund (FEDER) “A way of making Europe” [grant numbers PI15/00860 to GB, PI17/01482 and PI20/00413 to MP], the GAIN, Xunta de Galicia, Spain [grant number IN607A 2016/22 to GB, ED431C-2016/015 and ED431C-2020/14 to RC, ED431C 2017/58 to SL, ED431G 2019/01 to RC and SL, and ED431C 2017/66 to MCV], MINECO, Spain [grant number MTM2017-82724-R to RC], Ministerio de Ciencia e Innovación, Spain [grant number PID2020-113578RB-100 to RC], and the Spanish Network for Research in Infectious Diseases [REIPI RD16/0016/006 to GB]. The work was also supported by the European Virus Archive Global (EVA-GLOBAL) project that has received funding from the European Union's Horizon 2020 - Research and Innovation Framework Programme under grant agreement no 871029. SR-F was financially supported by REIPI RD16/0016/006, KC-P by IN607A 2016/22 and the Spanish Association against Cancer (AECC) and JAV by IN607A 2016/22. Funding for open access charge: Universidade da Coruña/CISUGes_ES
dc.description.sponsorshipEDAR Bens S.A.; INV04020
dc.description.sponsorshipEDAR Bens S.A.; INV12120
dc.description.sponsorshipEDAR Bens S.A.; INV05921
dc.description.sponsorshipXunta de Galicia; IN607A 2016/22
dc.description.sponsorshipXunta de Galicia; ED431C-2016/015
dc.description.sponsorshipXunta de Galicia; ED431C-2020/14
dc.description.sponsorshipXunta de Galicia; ED431C 2017/58
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01
dc.description.sponsorshipXunta de Galicia; ED431C 2017/66
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/PI15%2F00860/ES/Desarrollo de una plataforma universal de vacunas bacterianas vivas atenuadas auxótrofas para D-glutamato: prevención y erradicación de infecciones por bacterias multirresistentes/
dc.relationinfo:eu-repo/grantAgreement/ISCIII/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/PI17%2F01482/ES/EVALUACION DE NUEVAS ESTRATEGIAS ANTIMICROBIANAS MEDIANTE SILENCIAMIENTO DE ARN VEHICULIZADO EN NANOCAPSULAS E INHIBIDORES ENZIMATICOS/
dc.relationinfo:eu-repo/grantAgreement/ISCIII/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PI20%2F00413/ES/FARMACOMICROBIOMICA Y MEDICINA PERSONALIZADA EN LA TERAPIA DEL CANCER COLORECTAL/
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/MTM2017-82724-R/ES/INFERENCIA ESTADISTICA FLEXIBLE PARA DATOS COMPLEJOS DE GRAN VOLUMEN Y DE ALTA DIMENSION/
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113578RB-I00/ES/METODOS ESTADISTICOS FLEXIBLES EN CIENCIA DE DATOS PARA DATOS COMPLEJOS Y DE GRAN VOLUMEN: TEORIA Y APLICACIONES/
dc.relationinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/RD16%2F0016%2F0006/ES/RED ESPAÑOLA DE INVESTIGACIÓN EN PATOLOGÍAS INFECCIOSAS/
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/871029
dc.relation.urihttps://doi.org/10.1016/j.scitotenv.2021.152334es_ES
dc.rightsAtribución 4.0 Internacionales_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectSARS-CoV-2es_ES
dc.subjectCOVID–19es_ES
dc.subjectWastewater-based epidemiologyes_ES
dc.subjectGeneralized Additive Models (GAM)es_ES
dc.subjectKernel smoothinges_ES
dc.subjectLOESSes_ES
dc.titleModeling the Number of People Infected With SARS-COV-2 From Wastewater Viral Load in Northwest Spaines_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleScience of The Total Environmentes_ES
UDC.volume811es_ES
UDC.startPage152334es_ES
dc.identifier.doi10.1016/j.scitotenv.2021.152334


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