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Modeling the Number of People Infected With SARS-COV-2 From Wastewater Viral Load in Northwest Spain
dc.contributor.author | Vallejo, J.A. | |
dc.contributor.author | Trigo Tasende, Noelia | |
dc.contributor.author | Rumbo-Feal, Soraya | |
dc.contributor.author | Conde-Pérez, Kelly | |
dc.contributor.author | López-Oriona, Ángel | |
dc.contributor.author | Barbeito, Inés | |
dc.contributor.author | Vaamonde, Manuel | |
dc.contributor.author | Tarrío-Saavedra, Javier | |
dc.contributor.author | Reif López, Rubén | |
dc.contributor.author | Ladra, Susana | |
dc.contributor.author | Rodiño-Janeiro, Bruno Kotska | |
dc.contributor.author | Nasser-Ali, Mohammed | |
dc.contributor.author | Cid, Ángeles | |
dc.contributor.author | Veiga, María Carmen | |
dc.contributor.author | Acevedo, Antón | |
dc.contributor.author | Lamora, Carlos | |
dc.contributor.author | Bou, Germán | |
dc.contributor.author | Cao, Ricardo | |
dc.contributor.author | Poza, Margarita | |
dc.date.accessioned | 2022-03-22T19:41:48Z | |
dc.date.available | 2022-03-22T19:41:48Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | VALLEJO, 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.uri | http://hdl.handle.net/2183/30143 | |
dc.description | Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG | es_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.sponsorship | This 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/CISUG | es_ES |
dc.description.sponsorship | EDAR Bens S.A.; INV04020 | |
dc.description.sponsorship | EDAR Bens S.A.; INV12120 | |
dc.description.sponsorship | EDAR Bens S.A.; INV05921 | |
dc.description.sponsorship | Xunta de Galicia; IN607A 2016/22 | |
dc.description.sponsorship | Xunta de Galicia; ED431C-2016/015 | |
dc.description.sponsorship | Xunta de Galicia; ED431C-2020/14 | |
dc.description.sponsorship | Xunta de Galicia; ED431C 2017/58 | |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | |
dc.description.sponsorship | Xunta de Galicia; ED431C 2017/66 | |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info: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.relation | info: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.relation | info: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.relation | info: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.relation | info: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.relation | info: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.relation | info:eu-repo/grantAgreement/EC/H2020/871029 | |
dc.relation.uri | https://doi.org/10.1016/j.scitotenv.2021.152334 | es_ES |
dc.rights | Atribución 4.0 Internacional | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | SARS-CoV-2 | es_ES |
dc.subject | COVID–19 | es_ES |
dc.subject | Wastewater-based epidemiology | es_ES |
dc.subject | Generalized Additive Models (GAM) | es_ES |
dc.subject | Kernel smoothing | es_ES |
dc.subject | LOESS | es_ES |
dc.title | Modeling the Number of People Infected With SARS-COV-2 From Wastewater Viral Load in Northwest Spain | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Science of The Total Environment | es_ES |
UDC.volume | 811 | es_ES |
UDC.startPage | 152334 | es_ES |
dc.identifier.doi | 10.1016/j.scitotenv.2021.152334 |
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