< Back to Article

COVID-19 virtual patient cohort suggests immune mechanisms driving disease outcomes

Fig 8

Algorithm for generating virtual patients.

Parameters in the model were first obtained through fitting to data (S1 Table). 1) Parameters relating to macrophage, IL-6 and IFN production (, p_L,MΦ, p_F,I, p_M,I, η_F,MΦ, ϵ_F,I, and p_F,M) were generated from normal distributions with mean equal to their original fitted values and standard deviation informed by experiment observations (see Section S6.1). 2) The model evaluated is then simulated on this parameter set to obtain y(t, p). 3) A simulated annealing algorithm is then used to determine a parameter set that optimises the objective function J(p) (Eq 17). 4) Optimizing the objective function provides a parameter set for which the patient response to SARS-CoV-2 will be within the physiological ranges. This patient is then assigned to the cohort and this process is continued until 200 patients have been generated. Physiological ranges are noted in the bottom box for viral load [37], IFN [51], IL-6 [53] and G-CSF [30].

doi: https://doi.org/10.1371/journal.ppat.1009753.g008