Fig 1.
Fit of the logistic proliferation model to the data.
The circles represent viral load data which are filled green when the viral population was dominated by BAM sensitive virus and filled red when dominated by resistant virus. The unfilled circles are data below the limit of quantification (2 log10 RNA copies/mL) or limit of detection (1.4 log10 RNA copies/mL, indicated by horizontal lines). Black curves show the best-fit of the model to the total viral load. When plotting the model fit, V1 (BAM sensitive) is represented by a dashed–green curve and V2 (BAM resistant) by a red curve. The vertical black line indicates the time of treatment initiation. The vertical red line indicates the estimated time, t* when adaptive immunity begins to emerge.
Table 1.
Best fit parameters for the logistic proliferation model.
Fig 2.
Fit of the innate immune response model to the data.
The circles represent viral load data which are filled green when the viral population was dominated by BAM sensitive virus and filled red when dominated by resistant virus. The unfilled circles are data below the limit of quantification or limit of detection (indicated by horizontal lines). Black curves show the best-fit of the model to the total viral load. When plotting the model fit, V1 (BAM sensitive) is represented by a dashed–green curve and V2 (BAM resistant) by a red curve. The vertical black line indicates the time of treatment initiation. The vertical red line indicates the estimated time, t*, when adaptive immunity begins to emerge.
Table 2.
Best fit parameters for the innate immune response model.
Table 3.
Comparison of fitting between the logistic proliferation and innate immune response models.
Bolded text shows the smaller value.
Fig 3.
The rate of target cell replenishment has a crucial role in driving the amplitude of the viral rebound.
Baseline parameters for the simulation are taken from the best fit parameters of B2-8. The first vertical red (dashed dot) line indicates the time of treatment initiation. The second vertical red (dashed) line indicates when adaptive immunity begins to emerge. (A) Viral rebound is more likely to be observable (e.g., sufficiently high VL) with increasing intrinsic growth rate r. (B) Viral rebound is more likely to be observable with increasing rate of refractory cells returning to cells susceptible to infection ρ.
Fig 4.
Target cell replenishment can explain the emergence of resistant virus associated with high transient viral rebound.
(A) Natural course of acute infection as described by a standard viral dynamic model. (B) Without target cell replenishment, the resistant virus becomes the dominant population but does not lead to observable transient viral rebound. (C) Target cell replenishment–either via new production or target cell returning from the refractory state ‐ can drive the resistant viral population to an observable transient viral rebound.