Dataset Information

Quantifying the relationship between SARS-CoV-2 viral load and infectiousness.

ABSTRACT: The relationship between SARS-CoV-2 viral load and infectiousness is poorly known. Using data from a cohort of cases and high-risk contacts, we reconstructed viral load at the time of contact and inferred the probability of infection. The effect of viral load was larger in household contacts than in non-household contacts, with a transmission probability as large as 48% when the viral load was greater than 10¹⁰ copies per mL. The transmission probability peaked at symptom onset, with a mean probability of transmission of 29%, with large individual variations. The model also projects the effects of variants on disease transmission. Based on the current knowledge that viral load is increased by two- to eightfold with variants of concern and assuming no changes in the pattern of contacts across variants, the model predicts that larger viral load levels could lead to a relative increase in the probability of transmission of 24% to 58% in household contacts, and of 15% to 39% in non-household contacts.

SUBMITTER: Marc A

PROVIDER: S-EPMC8476126 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Quantifying the relationship between SARS-CoV-2 viral load and infectiousness.

Marc Aurélien A Kerioui Marion M Blanquart François F Bertrand Julie J Mitjà Oriol O Corbacho-Monné Marc M Marks Michael M Guedj Jeremie J

eLife 20210927

The relationship between SARS-CoV-2 viral load and infectiousness is poorly known. Using data from a cohort of cases and high-risk contacts, we reconstructed viral load at the time of contact and inferred the probability of infection. The effect of viral load was larger in household contacts than in non-household contacts, with a transmission probability as large as 48% when the viral load was greater than 10<sup>10</sup> copies per mL. The transmission probability peaked at symptom onset, with ...[more]

PMID: 34569939

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Project description:BackgroundViral load kinetics and duration of viral shedding are important determinants for disease transmission. We aimed to characterise viral load dynamics, duration of viral RNA shedding, and viable virus shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in various body fluids, and to compare SARS-CoV-2, SARS-CoV, and Middle East respiratory syndrome coronavirus (MERS-CoV) viral dynamics.MethodsIn this systematic review and meta-analysis, we searched databases, including MEDLINE, Embase, Europe PubMed Central, medRxiv, and bioRxiv, and the grey literature, for research articles published between Jan 1, 2003, and June 6, 2020. We included case series (with five or more participants), cohort studies, and randomised controlled trials that reported SARS-CoV-2, SARS-CoV, or MERS-CoV infection, and reported viral load kinetics, duration of viral shedding, or viable virus. Two authors independently extracted data from published studies, or contacted authors to request data, and assessed study quality and risk of bias using the Joanna Briggs Institute Critical Appraisal Checklist tools. We calculated the mean duration of viral shedding and 95% CIs for every study included and applied the random-effects model to estimate a pooled effect size. We used a weighted meta-regression with an unrestricted maximum likelihood model to assess the effect of potential moderators on the pooled effect size. This study is registered with PROSPERO, CRD42020181914.Findings79 studies (5340 individuals) on SARS-CoV-2, eight studies (1858 individuals) on SARS-CoV, and 11 studies (799 individuals) on MERS-CoV were included. Mean duration of SARS-CoV-2 RNA shedding was 17·0 days (95% CI 15·5-18·6; 43 studies, 3229 individuals) in upper respiratory tract, 14·6 days (9·3-20·0; seven studies, 260 individuals) in lower respiratory tract, 17·2 days (14·4-20·1; 13 studies, 586 individuals) in stool, and 16·6 days (3·6-29·7; two studies, 108 individuals) in serum samples. Maximum shedding duration was 83 days in the upper respiratory tract, 59 days in the lower respiratory tract, 126 days in stools, and 60 days in serum. Pooled mean SARS-CoV-2 shedding duration was positively associated with age (slope 0·304 [95% CI 0·115-0·493]; p=0·0016). No study detected live virus beyond day 9 of illness, despite persistently high viral loads, which were inferred from cycle threshold values. SARS-CoV-2 viral load in the upper respiratory tract appeared to peak in the first week of illness, whereas that of SARS-CoV peaked at days 10-14 and that of MERS-CoV peaked at days 7-10.InterpretationAlthough SARS-CoV-2 RNA shedding in respiratory and stool samples can be prolonged, duration of viable virus is relatively short-lived. SARS-CoV-2 titres in the upper respiratory tract peak in the first week of illness. Early case finding and isolation, and public education on the spectrum of illness and period of infectiousness are key to the effective containment of SARS-CoV-2.FundingNone.

Project description:ObjectiveTo investigate the association of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load and infection-to-delivery interval with maternal and cord serum concentrations of anti-SARS-CoV-2 immunoglobulin G (IgG) antibodies and transplacental transfer ratio in pregnant women with active or recovered SARS-CoV-2 infection.MethodsThis was a prospective case series of consecutive pregnant women with laboratory-confirmed SARS-CoV-2 infection between 27 March 2020 and 24 January 2021. We collected information regarding deep throat saliva or nasopharyngeal swab (NPS) reverse transcription polymerase chain reaction (RT-PCR) test results, serial cycle threshold (Ct) values at and after diagnosis, demographic, clinical and outcome data, and neonatal NPS RT-PCR results. Qualitative and quantitative analysis of IgG and immunoglobulin M (IgM) antibodies against SARS-CoV-2 was performed in maternal and cord blood serum samples obtained at delivery. Correlation of maternal Ct values, infection-to-delivery interval, infection duration and viral load area under the curve (AUC) with gestational age (GA) at diagnosis, maternal and cord serum IgG concentrations and transplacental transfer ratio of IgG were evaluated using Pearson's correlation.ResultsTwenty pregnant women who consented to participate and who had delivered their babies by 31 January 2021 were included in the study, comprising 14 who had recovered from coronavirus disease 2019 (COVID-19) and six with active infection at delivery. The median GA at clinical manifestation was 32.7 (range, 11.9-39.4) weeks. The median infection-to-delivery interval and infection duration were 41.5 (range, 2-187) days and 10.0 (range, 1-48) days, respectively. The median GA at delivery was 39.1 (range, 32.4-40.7) weeks and the median seroconversion interval was 14 (range, 1-19) days. Of 13 neonates born to seropositive mothers with recovered infection at delivery, 12 tested positive for anti-SARS-CoV-2 IgG. All neonatal NPS samples were negative for SARS-CoV-2 and all cord sera tested negative for IgM. The median transplacental transfer ratio of IgG was 1.3 (interquartile range, 0.9-1.6). There was a negative correlation between infection-to-delivery interval and anti-SARS-CoV-2 IgG concentrations in maternal (r = -0.6693, P = 0.0087) and cord (r = -0.6554, P = 0.0068) serum and a positive correlation between IgG concentration in maternal serum and viral load AUC (r = 0.5109, P = 0.0310). A negative correlation was observed between transfer ratio and viral load AUC (r = -0.4757, P = 0.0409).ConclusionsIn pregnant women who have recovered from COVID-19, anti-SARS-CoV-2 IgG concentrations at delivery increased with increasing viral load during infection and decreased with increasing infection-to-delivery interval. The median transplacental transfer ratio of IgG was 1.3 and it decreased with increasing viral load during infection. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Project description:BackgroundSolid organ and haematopoietic stem cell transplant recipients are more vulnerable to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) than non-transplant recipients due to immunosuppression, and may pose a continued transmission risk, especially within hospital settings. Detailed case reports including symptoms, viral load and infectiousness, defined by the presence of replication-competent viruses in culture, provide an opportunity to examine the relationship between clinical course, burden and contagiousness, and provide guidance on release from isolation.ObjectivesTo investigate the relationship between serial SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) cycle threshold (Ct) value or cycle of quantification value, or other measures of viral burden and the likelihood and duration of the presence of infectious virus based on viral culture, including the influence of age, sex, underlying pathologies, degree of immunosuppression, and/or vaccination on this relationship, in transplant recipients.MethodsLitCovid, medRxiv, Google Scholar and the World Health Organization COVID-19 database were searched from 1st November 2019 to 26th October 2022. Studies reporting relevant data (results from serial RT-PCR testing and viral culture data from the same respiratory samples) for transplant recipients with SARS-CoV-2 infection were included in this systematic review: Methodological quality was assessed using five criteria, and the data were synthesized narratively and graphically.ResultsThirteen case reports and case series reporting on 41 transplant recipients (22 renal, five cardiac, one bone marrow, two liver, one bilateral lung and 10 blood stem cell) were included in this review. A relationship was observed between proxies of viral burden and likelihood of shedding replication-competent SARS-CoV-2. Three individuals shed replication-competent viruses for >100 days after symptom onset. Lack of standardization of testing and reporting platforms precludes establishing a definitive viral burden cut-off. However, the majority of transplant recipients stopped shedding replication-competent viruses when the Ct value was >30 despite differences across platforms.ConclusionsViral burden is a reasonable proxy for infectivity when considered within the context of the clinical status of each patient. Standardized study design and reporting are essential to standardize guidance based on an increasing evidence base.

Project description:The within-host viral kinetics of SARS-CoV-2 infection and how they relate to a person's infectiousness are not well understood. This limits our ability to quantify the impact of interventions on viral transmission. Here, we develop data-driven viral dynamic models of SARS-CoV-2 infection and estimate key within-host parameters such as the infected cell half-life and the within-host reproductive number. We then develop a model linking VL to infectiousness, showing that a person's infectiousness increases sub-linearly with VL. We show that the logarithm of the VL in the upper respiratory tract (URT) is a better surrogate of infectiousness than the VL itself. Using data on VL and the predicted infectiousness, we further incorporated data on antigen and reverse transcription polymerase chain reaction (RT-PCR) tests and compared their usefulness in detecting infection and preventing transmission. We found that RT-PCR tests perform better than antigen tests assuming equal testing frequency; however, more frequent antigen testing may perform equally well with RT-PCR tests at a lower cost, but with many more false-negative tests. Overall, our models provide a quantitative framework for inferring the impact of therapeutics and vaccines that lower VL on the infectiousness of individuals and for evaluating rapid testing strategies. Quantifying the kinetics of SARS-CoV-2 infection and individual infectiousness is key to quantitatively understanding SARS-CoV-2 transmission and evaluating intervention strategies. Here we developed data-driven within-host models of SARS-CoV-2 infection and by fitting them to clinical data we estimated key within-host viral dynamic parameters. We also developed a mechanistic model for viral transmission and show that the logarithm of the viral load in the upper respiratory tract serves an appropriate surrogate for a person's infectiousness. Using data on how viral load changes during infection, we further evaluated the effectiveness of PCR and antigen-based testing strategies for averting transmission and identifying infected individuals.

Dataset Information

Quantifying the relationship between SARS-CoV-2 viral load and infectiousness.

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Quantifying the relationship between SARS-CoV-2 viral load and infectiousness.

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