5. Clinical medicine

Regarding the association between viral load and clinical outcomes such as mortality and clinical scores, a number of studies suggested that a high viral load at diagnosis is associated with more severe clinical outcomes and increased mortality. Such differences in viral load may reflect differences in the immunological response. For example, some studies suggest that severity is associated with the production of autoantibodies, which impairs innate and intrinsic antiviral immunological responses. Autoantibodies perturb immune function by neutralizing the cytokines/chemokines, thus could be associated with disease severity. Autoantibodies may also be associated with persistent viral load for a longer time. Thus to associate viral load and clinical outcomes, temporal viral load pattern should be considered, rather than single time pint viral loads.

Here, we propose a classification model to predict future severity/mortality risk using longitudinal viral load data collected during the early phase of the infection. Patients will be categorized into several groups using the estimated viral load data with a weight function. The weight function will be optimized to realize the best predictive and discriminative ability of mortality (and other clinical outcomes such as critical disease). This project will identify the critical patterns of viral dynamics and the critical timing of viral load collection to identify vulnerable patients.