4.8 Article

Modelling upper respiratory viral load dynamics of SARS-CoV-2

Journal

BMC MEDICINE
Volume 20, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12916-021-02220-0

Keywords

-

Funding

  1. UKRI (MRC) [MR/V027409/1]
  2. DHSC (NIHR)
  3. Imperial College Covid-19 Response Fund
  4. MRC Centre for Global Infectious Disease Analysis by the UK Medical Research Council (MRC) under the MRC/FCDO Concordat agreement [MR/R015600/1]
  5. MRC Centre for Global Infectious Disease Analysis by the UK Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement [MR/R015600/1]
  6. European Union
  7. Wellcome Trust [103865Z/14/Z]
  8. MRC [MR/V027409/1] Funding Source: UKRI

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The relationships between viral load, severity of illness, and transmissibility of the virus are crucial for understanding the pathogenesis of COVID-19 and developing effective therapeutic and preventive strategies. In this study, a within-host model was used to analyze the viral load dynamics in the upper respiratory tract (URT) based on data from 605 subjects. The study revealed wide variation in URT viral load between individuals, which was not explained by demographic or clinical variables. A mechanistic model was developed to describe viral load dynamics and host response, and it was found that neutralising antibodies were strongly correlated with immune-mediated control of viral load.
Relationships between viral load, severity of illness, and transmissibility of virus are fundamental to understanding pathogenesis and devising better therapeutic and prevention strategies for COVID-19. Here we present within-host modelling of viral load dynamics observed in the upper respiratory tract (URT), drawing upon 2172 serial measurements from 605 subjects, collected from 17 different studies. We developed a mechanistic model to describe viral load dynamics and host response and contrast this with simpler mixed-effects regression analysis of peak viral load and its subsequent decline. We observed wide variation in URT viral load between individuals, over 5 orders of magnitude, at any given point in time since symptom onset This variation was not explained by age, sex, or severity of illness, and these variables were not associated with the modelled early or late phases of immune-mediated control of viral load. We explored the application of the mechanistic model to identify measured immune responses associated with the control of the viral load. Neutralising antibodies correlated strongly with modelled immune-mediated control of viral load amongst subjects who produced neutralising antibodies. Our models can be used to identify host and viral factors which control URT viral load dynamics, informing future treatment and transmission blocking interventions.

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