Pool Strategy for Surveillance Testing of SARS-CoV-2

Autores
Marceca, Felipe; Rocha Viegas, Luciana; Pregi, Nicolás; Barbas, María Gabriela; Hozbor, Daniela Flavia; Pecci, Adali; Etchenique, Roberto Argentino
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Due to the great morbidity and mortality in the risk groups of the pandemic COVID-19 caused by the emerging coronavirus SARS-CoV-2 and in the absence of effective therapeutic or preventive measures, quarantines, social distancing and the use of masks were the measures most used by health systems to reduce infections. The social, economic and health impact caused by these measures have begun to be evaluated in the different countries. These analyses lead to underestimations because in general they evaluate disease confirmed by a laboratory test and in some cases by epidemiological link without considering asymptomatic or oligosymptomatic infection. Therefore, mitigating fast circulation of the virus requires continuous tracking, detection, and isolation of cases, for which active surveillance able to address asymptomatic cases can make a valuable contribution over the dynamics of the disease in a given society, and to allocate adequate health resources and evaluate the effectiveness of control measures. Mathematical models such as the Susceptible-Exposed-Infectious-Removed (SEIR) allow not only to improve the estimates of the evolution of the pandemic at the local level, but also to evaluate health strategies. In the context of large testing requirements and the expansion of such testing capacity, it is also essential to develop approaches that improve the efficient use of these resources. Active surveillance undoubtedly contributes to improving estimates of virus circulation and it is of particular importance in vulnerable groups of high population density that have one or more risk factors, difficult access to the health system, and inhabit semi-closed facilities such as residential care homes, mental hospitals, prison houses, police stations housing prisoners, etc. Group testing strategies are especially useful for routine community survey and for monitoring of cohesive groups. While the frequency of infection in a population, who have only some symptoms compatible with the disease or do not have any symptoms, may be low, diagnosing even a single positive person typically requires quarantine of the entire group to prevent further spread in the community. In these surveillance strategies, pooling may allow more routine monitoring and detection of low frequency of carriage, thereby improving estimates, informing policy makers, reducing transmission, and alleviating the strain on healthcare services. By means of molecular tests based on RT-qPCR, the pooling strategy has been assayed with different algorithms also for COVID-19, particularly in the asymptomatic population, since a low prevalence of the disease is expected there. This has increased COVID-19 testing throughput while maintaining high sensitivity. Here, we discuss the relevance of some active surveillance strategies to determine key facts about COVID-19 pandemics and review different testing strategies that different countries have applied for tracking SARS-CoV-2.
Fil: Marceca, Felipe. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina
Fil: Rocha Viegas, Luciana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina
Fil: Pregi, Nicolás. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Barbas, María Gabriela. Gobierno de la Provincia de Cordoba. Ministerio de Salud. Laboratorio Central de la Provincia.; Argentina
Fil: Hozbor, Daniela Flavia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Biotecnología y Biología Molecular. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Biotecnología y Biología Molecular; Argentina
Fil: Pecci, Adali. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina
Fil: Etchenique, Roberto Argentino. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Materia
pool testing
coronavirus
RT-qPCR
Surveillance
COVID-19
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/149942

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spelling Pool Strategy for Surveillance Testing of SARS-CoV-2Marceca, FelipeRocha Viegas, LucianaPregi, NicolásBarbas, María GabrielaHozbor, Daniela FlaviaPecci, AdaliEtchenique, Roberto Argentinopool testingcoronavirusRT-qPCRSurveillanceCOVID-19https://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1https://purl.org/becyt/ford/3.3https://purl.org/becyt/ford/3Due to the great morbidity and mortality in the risk groups of the pandemic COVID-19 caused by the emerging coronavirus SARS-CoV-2 and in the absence of effective therapeutic or preventive measures, quarantines, social distancing and the use of masks were the measures most used by health systems to reduce infections. The social, economic and health impact caused by these measures have begun to be evaluated in the different countries. These analyses lead to underestimations because in general they evaluate disease confirmed by a laboratory test and in some cases by epidemiological link without considering asymptomatic or oligosymptomatic infection. Therefore, mitigating fast circulation of the virus requires continuous tracking, detection, and isolation of cases, for which active surveillance able to address asymptomatic cases can make a valuable contribution over the dynamics of the disease in a given society, and to allocate adequate health resources and evaluate the effectiveness of control measures. Mathematical models such as the Susceptible-Exposed-Infectious-Removed (SEIR) allow not only to improve the estimates of the evolution of the pandemic at the local level, but also to evaluate health strategies. In the context of large testing requirements and the expansion of such testing capacity, it is also essential to develop approaches that improve the efficient use of these resources. Active surveillance undoubtedly contributes to improving estimates of virus circulation and it is of particular importance in vulnerable groups of high population density that have one or more risk factors, difficult access to the health system, and inhabit semi-closed facilities such as residential care homes, mental hospitals, prison houses, police stations housing prisoners, etc. Group testing strategies are especially useful for routine community survey and for monitoring of cohesive groups. While the frequency of infection in a population, who have only some symptoms compatible with the disease or do not have any symptoms, may be low, diagnosing even a single positive person typically requires quarantine of the entire group to prevent further spread in the community. In these surveillance strategies, pooling may allow more routine monitoring and detection of low frequency of carriage, thereby improving estimates, informing policy makers, reducing transmission, and alleviating the strain on healthcare services. By means of molecular tests based on RT-qPCR, the pooling strategy has been assayed with different algorithms also for COVID-19, particularly in the asymptomatic population, since a low prevalence of the disease is expected there. This has increased COVID-19 testing throughput while maintaining high sensitivity. Here, we discuss the relevance of some active surveillance strategies to determine key facts about COVID-19 pandemics and review different testing strategies that different countries have applied for tracking SARS-CoV-2.Fil: Marceca, Felipe. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; ArgentinaFil: Rocha Viegas, Luciana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Pregi, Nicolás. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Barbas, María Gabriela. Gobierno de la Provincia de Cordoba. Ministerio de Salud. Laboratorio Central de la Provincia.; ArgentinaFil: Hozbor, Daniela Flavia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Biotecnología y Biología Molecular. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Biotecnología y Biología Molecular; ArgentinaFil: Pecci, Adali. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Etchenique, Roberto Argentino. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; ArgentinaCentro de Estudios sobre Ciencia, Desarrollo y Educación Superior2021-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/149942Marceca, Felipe; Rocha Viegas, Luciana; Pregi, Nicolás; Barbas, María Gabriela; Hozbor, Daniela Flavia; et al.; Pool Strategy for Surveillance Testing of SARS-CoV-2; Centro de Estudios sobre Ciencia, Desarrollo y Educación Superior; Science Reviews: from the end of the world; 2; 2; 4-2021; 42-562683-9288CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://scirevfew.net/index.php/sciencereviews/article/view/39info:eu-repo/semantics/altIdentifier/doi/10.52712/sciencereviews.v2i2.39info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:33:22Zoai:ri.conicet.gov.ar:11336/149942instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:33:22.857CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Pool Strategy for Surveillance Testing of SARS-CoV-2
title Pool Strategy for Surveillance Testing of SARS-CoV-2
spellingShingle Pool Strategy for Surveillance Testing of SARS-CoV-2
Marceca, Felipe
pool testing
coronavirus
RT-qPCR
Surveillance
COVID-19
title_short Pool Strategy for Surveillance Testing of SARS-CoV-2
title_full Pool Strategy for Surveillance Testing of SARS-CoV-2
title_fullStr Pool Strategy for Surveillance Testing of SARS-CoV-2
title_full_unstemmed Pool Strategy for Surveillance Testing of SARS-CoV-2
title_sort Pool Strategy for Surveillance Testing of SARS-CoV-2
dc.creator.none.fl_str_mv Marceca, Felipe
Rocha Viegas, Luciana
Pregi, Nicolás
Barbas, María Gabriela
Hozbor, Daniela Flavia
Pecci, Adali
Etchenique, Roberto Argentino
author Marceca, Felipe
author_facet Marceca, Felipe
Rocha Viegas, Luciana
Pregi, Nicolás
Barbas, María Gabriela
Hozbor, Daniela Flavia
Pecci, Adali
Etchenique, Roberto Argentino
author_role author
author2 Rocha Viegas, Luciana
Pregi, Nicolás
Barbas, María Gabriela
Hozbor, Daniela Flavia
Pecci, Adali
Etchenique, Roberto Argentino
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv pool testing
coronavirus
RT-qPCR
Surveillance
COVID-19
topic pool testing
coronavirus
RT-qPCR
Surveillance
COVID-19
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/3.3
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Due to the great morbidity and mortality in the risk groups of the pandemic COVID-19 caused by the emerging coronavirus SARS-CoV-2 and in the absence of effective therapeutic or preventive measures, quarantines, social distancing and the use of masks were the measures most used by health systems to reduce infections. The social, economic and health impact caused by these measures have begun to be evaluated in the different countries. These analyses lead to underestimations because in general they evaluate disease confirmed by a laboratory test and in some cases by epidemiological link without considering asymptomatic or oligosymptomatic infection. Therefore, mitigating fast circulation of the virus requires continuous tracking, detection, and isolation of cases, for which active surveillance able to address asymptomatic cases can make a valuable contribution over the dynamics of the disease in a given society, and to allocate adequate health resources and evaluate the effectiveness of control measures. Mathematical models such as the Susceptible-Exposed-Infectious-Removed (SEIR) allow not only to improve the estimates of the evolution of the pandemic at the local level, but also to evaluate health strategies. In the context of large testing requirements and the expansion of such testing capacity, it is also essential to develop approaches that improve the efficient use of these resources. Active surveillance undoubtedly contributes to improving estimates of virus circulation and it is of particular importance in vulnerable groups of high population density that have one or more risk factors, difficult access to the health system, and inhabit semi-closed facilities such as residential care homes, mental hospitals, prison houses, police stations housing prisoners, etc. Group testing strategies are especially useful for routine community survey and for monitoring of cohesive groups. While the frequency of infection in a population, who have only some symptoms compatible with the disease or do not have any symptoms, may be low, diagnosing even a single positive person typically requires quarantine of the entire group to prevent further spread in the community. In these surveillance strategies, pooling may allow more routine monitoring and detection of low frequency of carriage, thereby improving estimates, informing policy makers, reducing transmission, and alleviating the strain on healthcare services. By means of molecular tests based on RT-qPCR, the pooling strategy has been assayed with different algorithms also for COVID-19, particularly in the asymptomatic population, since a low prevalence of the disease is expected there. This has increased COVID-19 testing throughput while maintaining high sensitivity. Here, we discuss the relevance of some active surveillance strategies to determine key facts about COVID-19 pandemics and review different testing strategies that different countries have applied for tracking SARS-CoV-2.
Fil: Marceca, Felipe. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina
Fil: Rocha Viegas, Luciana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina
Fil: Pregi, Nicolás. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Barbas, María Gabriela. Gobierno de la Provincia de Cordoba. Ministerio de Salud. Laboratorio Central de la Provincia.; Argentina
Fil: Hozbor, Daniela Flavia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Biotecnología y Biología Molecular. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Biotecnología y Biología Molecular; Argentina
Fil: Pecci, Adali. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina
Fil: Etchenique, Roberto Argentino. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
description Due to the great morbidity and mortality in the risk groups of the pandemic COVID-19 caused by the emerging coronavirus SARS-CoV-2 and in the absence of effective therapeutic or preventive measures, quarantines, social distancing and the use of masks were the measures most used by health systems to reduce infections. The social, economic and health impact caused by these measures have begun to be evaluated in the different countries. These analyses lead to underestimations because in general they evaluate disease confirmed by a laboratory test and in some cases by epidemiological link without considering asymptomatic or oligosymptomatic infection. Therefore, mitigating fast circulation of the virus requires continuous tracking, detection, and isolation of cases, for which active surveillance able to address asymptomatic cases can make a valuable contribution over the dynamics of the disease in a given society, and to allocate adequate health resources and evaluate the effectiveness of control measures. Mathematical models such as the Susceptible-Exposed-Infectious-Removed (SEIR) allow not only to improve the estimates of the evolution of the pandemic at the local level, but also to evaluate health strategies. In the context of large testing requirements and the expansion of such testing capacity, it is also essential to develop approaches that improve the efficient use of these resources. Active surveillance undoubtedly contributes to improving estimates of virus circulation and it is of particular importance in vulnerable groups of high population density that have one or more risk factors, difficult access to the health system, and inhabit semi-closed facilities such as residential care homes, mental hospitals, prison houses, police stations housing prisoners, etc. Group testing strategies are especially useful for routine community survey and for monitoring of cohesive groups. While the frequency of infection in a population, who have only some symptoms compatible with the disease or do not have any symptoms, may be low, diagnosing even a single positive person typically requires quarantine of the entire group to prevent further spread in the community. In these surveillance strategies, pooling may allow more routine monitoring and detection of low frequency of carriage, thereby improving estimates, informing policy makers, reducing transmission, and alleviating the strain on healthcare services. By means of molecular tests based on RT-qPCR, the pooling strategy has been assayed with different algorithms also for COVID-19, particularly in the asymptomatic population, since a low prevalence of the disease is expected there. This has increased COVID-19 testing throughput while maintaining high sensitivity. Here, we discuss the relevance of some active surveillance strategies to determine key facts about COVID-19 pandemics and review different testing strategies that different countries have applied for tracking SARS-CoV-2.
publishDate 2021
dc.date.none.fl_str_mv 2021-04
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info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/149942
Marceca, Felipe; Rocha Viegas, Luciana; Pregi, Nicolás; Barbas, María Gabriela; Hozbor, Daniela Flavia; et al.; Pool Strategy for Surveillance Testing of SARS-CoV-2; Centro de Estudios sobre Ciencia, Desarrollo y Educación Superior; Science Reviews: from the end of the world; 2; 2; 4-2021; 42-56
2683-9288
CONICET Digital
CONICET
url http://hdl.handle.net/11336/149942
identifier_str_mv Marceca, Felipe; Rocha Viegas, Luciana; Pregi, Nicolás; Barbas, María Gabriela; Hozbor, Daniela Flavia; et al.; Pool Strategy for Surveillance Testing of SARS-CoV-2; Centro de Estudios sobre Ciencia, Desarrollo y Educación Superior; Science Reviews: from the end of the world; 2; 2; 4-2021; 42-56
2683-9288
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
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