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

Marc, Aurélien; Kerioui, Marion; Blanquart, François; Bertrand, Julie; Mitjà, Oriol; Corbacho-Monné, Marc; Marks, Micheal; Guedj, Jérémie

doi:10.1101/2021.05.07.21256341

Cited by 26 publications

(35 citation statements)

References 32 publications

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“…Whilst existing models have distinguished between infectious and non-infectious virus, to the best of our knowledge this is the first modelling study that makes use of infectious virus titres during parameter inference. Our estimate of the within-host basic reproduction number ( R 0 =11) is similar to estimates from previous modelling studies (8.5–14.2), as is our estimate of 0.85 days for the lifespan of productively infected cells during the early stages of infection (0.53–1.66 days) [11, 17, 33].…”

Section: Discussionsupporting

confidence: 88%

A within-host model of SARS-CoV-2 infection

Carruthers

Finnie

et al. 2022

Preprint

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Within-host models have been used to successfully describe the dynamics of multiple viral infections, however, the dynamics of SARS-CoV-2 virus infection remain poorly understood. A greater understanding of how the virus interacts with the host can contribute to more realistic epidemiological models and help evaluate the effect of antiviral therapies and vaccines. Here, we present a within-host model to describe SARS-CoV-2 viral dynamics in the upper respiratory tract of individuals enrolled in the UK COVID-19 Human Challenge Study. Using this model, we investigate the viral dynamics and provide timescales of infection that independently verify key epidemiological parameters important in the management of an epidemic. In particular, we estimate that an infected individual is first capable of transmitting the virus after approximately 2.1 days, remains infectious for a further 8.3 days, but can continue to test positive using a PCR test for up to 27 days.

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Section: Discussionsupporting

confidence: 88%

A within-host model of SARS-CoV-2 infection

Carruthers

Finnie

et al. 2022

Preprint

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“…Finally, Cq values are a proxy: they are linked to viral load, and there is some evidence that viral load is associated with probability of transmission, although with considerable variation between individuals [19][20][21].…”

Section: Discussionmentioning

confidence: 99%

Characterisation of vaccine breakthrough infections of SARS-CoV-2 Delta and Alpha variants and within-host viral load dynamics in the community, France, June to July 2021

Blanquart

Abad²,

Ambroise³

et al. 2021

Eurosurveillance

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We compared PCR results from SARS-CoV-2-positive patients tested in the community in France from 14 June to 30 July 2021. In asymptomatic individuals, Cq values were significantly higher in fully vaccinated than non-fully vaccinated individuals (effect size: 1.7; 95% CI: 1–2.3; p < 10−6). In symptomatic individuals and controlling for time since symptoms, the difference vanished (p = 0.26). Infections with the Delta variant had lower Cq values at symptom onset than with Alpha (effect size: −3.32; 95% CI: −4.38 to −2.25; p < 10−6).

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“…However, we reason that the evidence is not strong enough to rule out the power-law model, because the saturating behavior observed in Jaafar et al may arise from other factors that are not part of the transmission process, such as assay noise. In addition, another study estimating transmissibility from viral load and contact tracing data did not find a saturation effect on viral load (32).…”

Section: Resultsmentioning

confidence: 91%

In vivo kinetics of SARS-CoV-2 infection and its relationship with a person’s infectiousness

Zitzmann²,

et al. 2021

Preprint

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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 viral load (VL) to infectiousness, showing that 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.

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

Cited by 26 publications

References 32 publications

A within-host model of SARS-CoV-2 infection

A within-host model of SARS-CoV-2 infection

Characterisation of vaccine breakthrough infections of SARS-CoV-2 Delta and Alpha variants and within-host viral load dynamics in the community, France, June to July 2021

In vivo kinetics of SARS-CoV-2 infection and its relationship with a person’s infectiousness

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