Cargando…

A Flexible Regression Modeling Approach Applied to Observational Laboratory Virological Data Suggests That SARS-CoV-2 Load in Upper Respiratory Tract Samples Changes with COVID-19 Epidemiology

(1) Background. Exploring the evolution of SARS-CoV-2 load and clearance from the upper respiratory tract samples is important to improving COVID-19 control. Data were collected retrospectively from a laboratory dataset on SARS-CoV-2 load quantified in leftover nasal pharyngeal swabs (NPSs) collecte...

Descripción completa

Detalles Bibliográficos
Autores principales: Pellegrinelli, Laura, Luconi, Ester, Marano, Giuseppe, Galli, Cristina, Delbue, Serena, Bubba, Laura, Binda, Sandro, Castaldi, Silvana, Biganzoli, Elia, Pariani, Elena, Boracchi, Patrizia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610845/
https://www.ncbi.nlm.nih.gov/pubmed/37896765
http://dx.doi.org/10.3390/v15101988
_version_ 1785128352506445824
author Pellegrinelli, Laura
Luconi, Ester
Marano, Giuseppe
Galli, Cristina
Delbue, Serena
Bubba, Laura
Binda, Sandro
Castaldi, Silvana
Biganzoli, Elia
Pariani, Elena
Boracchi, Patrizia
author_facet Pellegrinelli, Laura
Luconi, Ester
Marano, Giuseppe
Galli, Cristina
Delbue, Serena
Bubba, Laura
Binda, Sandro
Castaldi, Silvana
Biganzoli, Elia
Pariani, Elena
Boracchi, Patrizia
author_sort Pellegrinelli, Laura
collection PubMed
description (1) Background. Exploring the evolution of SARS-CoV-2 load and clearance from the upper respiratory tract samples is important to improving COVID-19 control. Data were collected retrospectively from a laboratory dataset on SARS-CoV-2 load quantified in leftover nasal pharyngeal swabs (NPSs) collected from symptomatic/asymptomatic individuals who tested positive to SARS-CoV-2 RNA detection in the framework of testing activities for diagnostic/screening purpose during the 2020 and 2021 winter epidemic waves. (2) Methods. A Statistical approach (quantile regression and survival models for interval-censored data), novel for this kind of data, was applied. We included in the analysis SARS-CoV-2-positive adults >18 years old for whom at least two serial NPSs were collected. A total of 262 SARS-CoV-2-positive individuals and 784 NPSs were included: 193 (593 NPSs) during the 2020 winter wave (before COVID-19 vaccine introduction) and 69 (191 NPSs) during the 2021 winter wave (all COVID-19 vaccinated). We estimated the trend of the median value, as well as the 25th and 75th centiles of the viral load, from the index episode (i.e., first SARS-CoV-2-positive test) until the sixth week (2020 wave) and the third week (2021 wave). Interval censoring methods were used to evaluate the time to SARS-CoV-2 clearance (defined as Ct < 35). (3) Results. At the index episode, the median value of viral load in the 2021 winter wave was 6.25 log copies/mL (95% CI: 5.50–6.70), and the median value in the 2020 winter wave was 5.42 log copies/mL (95% CI: 4.95–5.90). In contrast, 14 days after the index episode, the median value of viral load was 3.40 log copies/mL (95% CI: 3.26–3.54) for individuals during the 2020 winter wave and 2.93 Log copies/mL (95% CI: 2.80–3.19) for those of the 2021 winter wave. A significant difference in viral load shapes was observed among age classes (p = 0.0302) and between symptomatic and asymptomatic participants (p = 0.0187) for the first wave only; the median viral load value is higher at the day of episode index for the youngest (18–39 years) as compared to the older (40–64 years and >64 years) individuals. In the 2021 epidemic, the estimated proportion of individuals who can be considered infectious (Ct < 35) was approximately half that of the 2020 wave. (4) Conclusions. In case of the emergence of new SARS-CoV-2 variants, the application of these statistical methods to the analysis of virological laboratory data may provide evidence with which to inform and promptly support public health decision-makers in the modification of COVID-19 control measures.
format Online
Article
Text
id pubmed-10610845
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-106108452023-10-28 A Flexible Regression Modeling Approach Applied to Observational Laboratory Virological Data Suggests That SARS-CoV-2 Load in Upper Respiratory Tract Samples Changes with COVID-19 Epidemiology Pellegrinelli, Laura Luconi, Ester Marano, Giuseppe Galli, Cristina Delbue, Serena Bubba, Laura Binda, Sandro Castaldi, Silvana Biganzoli, Elia Pariani, Elena Boracchi, Patrizia Viruses Article (1) Background. Exploring the evolution of SARS-CoV-2 load and clearance from the upper respiratory tract samples is important to improving COVID-19 control. Data were collected retrospectively from a laboratory dataset on SARS-CoV-2 load quantified in leftover nasal pharyngeal swabs (NPSs) collected from symptomatic/asymptomatic individuals who tested positive to SARS-CoV-2 RNA detection in the framework of testing activities for diagnostic/screening purpose during the 2020 and 2021 winter epidemic waves. (2) Methods. A Statistical approach (quantile regression and survival models for interval-censored data), novel for this kind of data, was applied. We included in the analysis SARS-CoV-2-positive adults >18 years old for whom at least two serial NPSs were collected. A total of 262 SARS-CoV-2-positive individuals and 784 NPSs were included: 193 (593 NPSs) during the 2020 winter wave (before COVID-19 vaccine introduction) and 69 (191 NPSs) during the 2021 winter wave (all COVID-19 vaccinated). We estimated the trend of the median value, as well as the 25th and 75th centiles of the viral load, from the index episode (i.e., first SARS-CoV-2-positive test) until the sixth week (2020 wave) and the third week (2021 wave). Interval censoring methods were used to evaluate the time to SARS-CoV-2 clearance (defined as Ct < 35). (3) Results. At the index episode, the median value of viral load in the 2021 winter wave was 6.25 log copies/mL (95% CI: 5.50–6.70), and the median value in the 2020 winter wave was 5.42 log copies/mL (95% CI: 4.95–5.90). In contrast, 14 days after the index episode, the median value of viral load was 3.40 log copies/mL (95% CI: 3.26–3.54) for individuals during the 2020 winter wave and 2.93 Log copies/mL (95% CI: 2.80–3.19) for those of the 2021 winter wave. A significant difference in viral load shapes was observed among age classes (p = 0.0302) and between symptomatic and asymptomatic participants (p = 0.0187) for the first wave only; the median viral load value is higher at the day of episode index for the youngest (18–39 years) as compared to the older (40–64 years and >64 years) individuals. In the 2021 epidemic, the estimated proportion of individuals who can be considered infectious (Ct < 35) was approximately half that of the 2020 wave. (4) Conclusions. In case of the emergence of new SARS-CoV-2 variants, the application of these statistical methods to the analysis of virological laboratory data may provide evidence with which to inform and promptly support public health decision-makers in the modification of COVID-19 control measures. MDPI 2023-09-23 /pmc/articles/PMC10610845/ /pubmed/37896765 http://dx.doi.org/10.3390/v15101988 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pellegrinelli, Laura
Luconi, Ester
Marano, Giuseppe
Galli, Cristina
Delbue, Serena
Bubba, Laura
Binda, Sandro
Castaldi, Silvana
Biganzoli, Elia
Pariani, Elena
Boracchi, Patrizia
A Flexible Regression Modeling Approach Applied to Observational Laboratory Virological Data Suggests That SARS-CoV-2 Load in Upper Respiratory Tract Samples Changes with COVID-19 Epidemiology
title A Flexible Regression Modeling Approach Applied to Observational Laboratory Virological Data Suggests That SARS-CoV-2 Load in Upper Respiratory Tract Samples Changes with COVID-19 Epidemiology
title_full A Flexible Regression Modeling Approach Applied to Observational Laboratory Virological Data Suggests That SARS-CoV-2 Load in Upper Respiratory Tract Samples Changes with COVID-19 Epidemiology
title_fullStr A Flexible Regression Modeling Approach Applied to Observational Laboratory Virological Data Suggests That SARS-CoV-2 Load in Upper Respiratory Tract Samples Changes with COVID-19 Epidemiology
title_full_unstemmed A Flexible Regression Modeling Approach Applied to Observational Laboratory Virological Data Suggests That SARS-CoV-2 Load in Upper Respiratory Tract Samples Changes with COVID-19 Epidemiology
title_short A Flexible Regression Modeling Approach Applied to Observational Laboratory Virological Data Suggests That SARS-CoV-2 Load in Upper Respiratory Tract Samples Changes with COVID-19 Epidemiology
title_sort flexible regression modeling approach applied to observational laboratory virological data suggests that sars-cov-2 load in upper respiratory tract samples changes with covid-19 epidemiology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610845/
https://www.ncbi.nlm.nih.gov/pubmed/37896765
http://dx.doi.org/10.3390/v15101988
work_keys_str_mv AT pellegrinellilaura aflexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT luconiester aflexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT maranogiuseppe aflexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT gallicristina aflexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT delbueserena aflexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT bubbalaura aflexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT bindasandro aflexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT castaldisilvana aflexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT biganzolielia aflexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT parianielena aflexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT boracchipatrizia aflexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT pellegrinellilaura flexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT luconiester flexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT maranogiuseppe flexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT gallicristina flexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT delbueserena flexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT bubbalaura flexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT bindasandro flexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT castaldisilvana flexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT biganzolielia flexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT parianielena flexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology
AT boracchipatrizia flexibleregressionmodelingapproachappliedtoobservationallaboratoryvirologicaldatasuggeststhatsarscov2loadinupperrespiratorytractsampleschangeswithcovid19epidemiology