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Modelling upper respiratory viral load dynamics of SARS-CoV-2.
Challenger, Joseph D; Foo, Cher Y; Wu, Yue; Yan, Ada W C; Marjaneh, Mahdi Moradi; Liew, Felicity; Thwaites, Ryan S; Okell, Lucy C; Cunnington, Aubrey J.
  • Challenger JD; Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK. j.challenger@imperial.ac.uk.
  • Foo CY; School of Medicine, Imperial College London, London, UK.
  • Wu Y; School of Clinical Medicine, University of Cambridge, Cambridge, UK.
  • Yan AWC; Department of Infectious Disease, Imperial College London, London, UK.
  • Marjaneh MM; Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, UK.
  • Liew F; National Heart and Lung Institute, Imperial College London, London, UK.
  • Thwaites RS; National Heart and Lung Institute, Imperial College London, London, UK.
  • Okell LC; Medical Research Council Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
  • Cunnington AJ; Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, UK.
BMC Med ; 20(1): 25, 2022 01 13.
Article in English | MEDLINE | ID: covidwho-1690915
ABSTRACT
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Prognostic study Topics: Long Covid Limits: Humans Language: English Journal: BMC Med Journal subject: Medicine Year: 2022 Document Type: Article Affiliation country: S12916-021-02220-0

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Prognostic study Topics: Long Covid Limits: Humans Language: English Journal: BMC Med Journal subject: Medicine Year: 2022 Document Type: Article Affiliation country: S12916-021-02220-0