Dynamic heterogeneity in COVID-19: Insights from a mathematical model.

ABSTRACT: Critical illness, such as severe COVID-19, is heterogenous in presentation and treatment response. However, it remains possible that clinical course may be influenced by dynamic and/or random events such that similar patients subject to similar injuries may yet follow different trajectories. We deployed a mechanistic mathematical model of COVID-19 to determine the range of possible clinical courses after SARS-CoV-2 infection, which may follow from specific changes in viral properties, immune properties, treatment modality and random external factors such as initial viral load. We find that treatment efficacy and baseline patient or viral features are not the sole determinant of outcome. We found patients with enhanced innate or adaptive immune responses can experience poor viral control, r

SUBMITTER: Voutouri C 

PROVIDER: S-EPMC11142552 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature