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

Oriol Mitjà,Michael Marks,Marion Kerioui,Julie Bertrand,Aurélien Marc,Jeremie Guedj,François Blanquart,Marc Corbacho-Monné

doi:10.7554/elife.69302

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.

Highlights

After more than 18 months of an unprecedented pandemic, some key aspects of virus transmission remain poorly understood
We evaluated the impact of a change in the viral production rate, p, by a fold 2–100, which corresponds to an average increase in viral load of 1–7 cycle thresholds (Ct), at each time point (Figure 4—figure supplement 1)
The effect of viral load was large in household contacts, with a mean transmission probability that increased to as much as 48% when the viral load was over 10 log10 copies per mL

Summary

Introduction

After more than 18 months of an unprecedented pandemic, some key aspects of virus transmission remain poorly understood. While respiratory droplets and aerosols have rapidly been demonstrated as a major route of transmission of SARS-CoV-2 (Tang et al, 2020), the role of the viral load as a driver of infectiousness has been established (He et al, 2020) but not quantified. This lack of evidence is due to the fact that high-risk contacts occur mostly before the index has been diagnosed, with no information on the viral load level at the time of the contact. We used the model to predict the effects of changes in viral load levels on the probability of transmission, representing the effects of infection with a variant of concern or infection in an individual in which vaccine would confer a partial protection against viral replication

Results

Discussion

Materials and methods

Study participants

Funding Funder