Fig 1.
Participant viral loads following ATI.
(a) Plasma HIV RNA levels following ATI; each corner represents a measurement, with lines used to connect the measurements from the same participant. (b) The times of last undetectable measurement and first detectable measurement shown as line segments spanning the detection window per ATI study participant, with color indicating whether the pre-ATI ART regimen included (red) or excluded (blue) NNRTIs.
Fig 2.
We assume that following ATI, latent cell activations are followed by chains of infection that may die out, i.e., go extinct, with probability q, or successfully re-establish high viral loads associated with chronic infection, with probability 1 − q. In the latter case, we further assume a delay τ between activation and the time when plasma viral load crosses the detection threshold.
Table 1.
Stylized delay distributions, D(t).
Fig 3.
HIV CA-RNA and HIV viral rebound.
(a) Histogram showing pre-ATI log10(HIV CA RNA (per 106 CD4+ cells)) across study participants. (b) Correlation between pre-ATI log10(HIV CA-RNA (per 106 CD4+ cells)) and time to viral rebound in non-NNRTI study participants (p-value 0.0260). Data shown only for study participants who showed viral loads less than 10000 HIV RNA/mL at first detection.
Fig 4.
Time post-ATI of first detectable viral load measurement depending on study participant drug regimen, with or without NNRTIs.
Note the statistically significant delay in viral rebound in participants taking NNRTIs pre-ATI (Wilcoxon rank sum test; p-value<0.01).
Table 2.
Key parameter estimates for model (1), making no distinction between participants based on pre-ATI ART regimen, with the 95% confidence interval indicated in parentheses.
All parameter provided in S1 Table.
Table 3.
Key parameter estimates for model (1) with the 95% confidence interval indicated in parentheses, distinguishing study participants based on pre-ATI ART regimen, specifically inclusion of NNRTIs.
Distribution-specific parameter estimates provided in S2 Table.
Fig 5.
Model predictions on time to viral rebound (VR).
Model predictions on time to VR for each ATI study participant (thin grey line) and the average time to viral rebound (thick, solid line), for (a) parameters estimated across all participants while neglecting pre-ATI ART regimen, and participants whose pre-ATI regimen (b) excluded or (c) included NNRTIs. The black, dashed curves give the empirical distributions of the time of last undetectable viral load test and first detectable viral load test.
Fig 6.
Visualization of model predictions.
Visualization of model predictions (a) neglecting pre-ATI ART regimen, using Eq (1), and (b) accounting for pre-ATI ART regimen, using Eq (2). The normalized times of last undetectable measurement and first detectable measurement are shown as line segments spanning the detection window per ATI study participant. Each detection window’s line segment is normalized by subtracting the associated model-predicted mean and dividing by the model-predicted standard deviation. Red and blue lines indicate detection windows that lie wholly outside one standard deviation, with color indicating whether the pre-ATI ART regimen is included (red) or excluded (blue) NNRTIs, while grey lines indicate detection windows that may be within one standard deviation of the mean.
Fig 7.
Model-predicted mean and standard deviation in time to viral rebound across the study population.
Histograms show the (a) mean and (b) standard deviation in time to viral rebound across ATI study population (see Description of data). Black/yellow indicates absence/presence of NNRTIs in the pre-ATI ART regimen.
Fig 8.
Model-predicted average frequency of recrudescence events.
Histograms of model-predicted average time between successful latent cell activations, across ATI study population (see Description of data) assuming (a) a Weibull-distributed detection delay and (b) a fixed detection delay. The predicted population-average is a successful activation every (a) 2.2 days and (b) 5.2 days.
Table 4.
Model-predicted mean time to successful latent cell activation, depending on detection delay distribution assumption, across study population, with 5th, 50th (median), and 95th percentiles.
Fig 9.
Model-recommended frequency of testing for ATI clinical trials, depending on study objectives, averaged over study population’s HIV CA-RNA levels.
Probability of viral rebound given fixed testing frequencies of every 1, 3, 7, and 14 days, as a function of time since ATI for study participants whose pre-ATI ART regimen (a) excluded and (b) included NNRTIs.
Fig 10.
In silico ATI study survival curves.
Ten sample survival curves for in silico studies with 100 study participants whose pre-ATI ART regimen included NNRTIs. Median (dashed line) and and 99% confidence interval (solid lines) computed from 10000 simulations. Survival curves describe model-predicted time to detectable viral rebound, given a post-ATI viral load testing schedule with (a) twice-weekly, (b) weekly, or (c) every two week testing.