Pool testing on random and natural clusters of individuals: Optimisation of SARS-CoV-2 surveillance in the presence of low viral load samples

Facing the SARS-CoV-2 epidemic requires intensive testing on the population to early identify and isolate infected subjects. During the first emergency phase of the epidemic, RT-qPCR on nasopharyngeal (NP) swabs, which is the most reliable technique to detect ongoing infections, exhibited limitation...

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Veröffentlicht in:PloS one 2021-05, Vol.16 (5), p.e0251589
Hauptverfasser: Baccini, Michela, Rocco, Emilia, Paganini, Irene, Mattei, Alessandra, Sani, Cristina, Vannucci, Giulia, Bisanzi, Simonetta, Burroni, Elena, Peluso, Marco, Munnia, Armelle, Cellai, Filippo, Pompeo, Giampaolo, Micio, Laura, Viti, Jessica, Mealli, Fabrizia, Carozzi, Francesca Maria
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container_start_page e0251589
container_title PloS one
container_volume 16
creator Baccini, Michela
Rocco, Emilia
Paganini, Irene
Mattei, Alessandra
Sani, Cristina
Vannucci, Giulia
Bisanzi, Simonetta
Burroni, Elena
Peluso, Marco
Munnia, Armelle
Cellai, Filippo
Pompeo, Giampaolo
Micio, Laura
Viti, Jessica
Mealli, Fabrizia
Carozzi, Francesca Maria
description Facing the SARS-CoV-2 epidemic requires intensive testing on the population to early identify and isolate infected subjects. During the first emergency phase of the epidemic, RT-qPCR on nasopharyngeal (NP) swabs, which is the most reliable technique to detect ongoing infections, exhibited limitations due to availability of reagents and budget constraints. This stressed the need to develop screening procedures that require fewer resources and are suitable to be extended to larger portions of the population. RT-qPCR on pooled samples from individual NP swabs seems to be a promising technique to improve surveillance. We performed preliminary experimental analyses aimed to investigate the performance of pool testing on samples with low viral load and we evaluated through Monte Carlo (MC) simulations alternative screening protocols based on sample pooling, tailored to contexts characterized by different infection prevalence. We focused on the role of pool size and the opportunity to develop strategies that take advantage of natural clustering structures in the population, e.g. families, school classes, hospital rooms. Despite the use of a limited number of specimens, our results suggest that, while high viral load samples seem to be detectable even in a pool with 29 negative samples, positive specimens with low viral load may be masked by the negative samples, unless smaller pools are used. The results of MC simulations confirm that pool testing is useful in contexts where the infection prevalence is low. The gain of pool testing in saving resources can be very high, and can be optimized by selecting appropriate group sizes. Exploiting natural groups makes the definition of larger pools convenient and potentially overcomes the issue of low viral load samples by increasing the probability of identifying more than one positive in the same pool.
doi_str_mv 10.1371/journal.pone.0251589
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Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health &amp; Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied &amp; Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Baccini, Michela</au><au>Rocco, Emilia</au><au>Paganini, Irene</au><au>Mattei, Alessandra</au><au>Sani, Cristina</au><au>Vannucci, Giulia</au><au>Bisanzi, Simonetta</au><au>Burroni, Elena</au><au>Peluso, Marco</au><au>Munnia, Armelle</au><au>Cellai, Filippo</au><au>Pompeo, Giampaolo</au><au>Micio, Laura</au><au>Viti, Jessica</au><au>Mealli, Fabrizia</au><au>Carozzi, Francesca Maria</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Pool testing on random and natural clusters of individuals: Optimisation of SARS-CoV-2 surveillance in the presence of low viral load samples</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-05-18</date><risdate>2021</risdate><volume>16</volume><issue>5</issue><spage>e0251589</spage><pages>e0251589-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Facing the SARS-CoV-2 epidemic requires intensive testing on the population to early identify and isolate infected subjects. During the first emergency phase of the epidemic, RT-qPCR on nasopharyngeal (NP) swabs, which is the most reliable technique to detect ongoing infections, exhibited limitations due to availability of reagents and budget constraints. This stressed the need to develop screening procedures that require fewer resources and are suitable to be extended to larger portions of the population. RT-qPCR on pooled samples from individual NP swabs seems to be a promising technique to improve surveillance. We performed preliminary experimental analyses aimed to investigate the performance of pool testing on samples with low viral load and we evaluated through Monte Carlo (MC) simulations alternative screening protocols based on sample pooling, tailored to contexts characterized by different infection prevalence. We focused on the role of pool size and the opportunity to develop strategies that take advantage of natural clustering structures in the population, e.g. families, school classes, hospital rooms. Despite the use of a limited number of specimens, our results suggest that, while high viral load samples seem to be detectable even in a pool with 29 negative samples, positive specimens with low viral load may be masked by the negative samples, unless smaller pools are used. The results of MC simulations confirm that pool testing is useful in contexts where the infection prevalence is low. The gain of pool testing in saving resources can be very high, and can be optimized by selecting appropriate group sizes. Exploiting natural groups makes the definition of larger pools convenient and potentially overcomes the issue of low viral load samples by increasing the probability of identifying more than one positive in the same pool.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>34003878</pmid><doi>10.1371/journal.pone.0251589</doi><orcidid>https://orcid.org/0000-0002-1076-9249</orcidid><orcidid>https://orcid.org/0000-0002-4365-427X</orcidid><orcidid>https://orcid.org/0000-0001-6867-0244</orcidid><oa>free_for_read</oa></addata></record>
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identifier ISSN: 1932-6203
ispartof PloS one, 2021-05, Vol.16 (5), p.e0251589
issn 1932-6203
1932-6203
language eng
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source MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS)
subjects Asymptomatic
Biology and Life Sciences
Cancer
Computer programs
Computer science
Coronaviruses
COVID-19
COVID-19 - diagnosis
COVID-19 - virology
COVID-19 Nucleic Acid Testing - methods
Disease prevention
DNA-directed RNA polymerase
Drafting software
Editing
Electronic mail
Evaluation
Humans
Infections
Laboratories
Mail
Medical screening
Medicine and Health Sciences
Methodology
Monte Carlo Method
Nasopharynx - virology
Nucleocapsids
Optimization
Pandemics
Performance evaluation
Physical sciences
Polymerase chain reaction
Prevention
Real-Time Polymerase Chain Reaction
Research and analysis methods
Respiratory diseases
Respiratory tract
Reviews
Ribonucleic acid
RNA
RNA polymerase
RNA, Viral - analysis
RNA-directed RNA polymerase
Samples
SARS-CoV-2 - genetics
SARS-CoV-2 - isolation & purification
Severe acute respiratory syndrome
Severe acute respiratory syndrome coronavirus 2
Software
Specimen Handling
Statistical analysis
Statistical methods
Statistics
Viral diseases
Viral Load
title Pool testing on random and natural clusters of individuals: Optimisation of SARS-CoV-2 surveillance in the presence of low viral load samples
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