Sensitivity analysis—ART dropouts reinitiate ART only at CD4<200 cells/μl.

<p><b>A)</b> The fraction of HIV infections averted and <b>B)</b> The fraction of HIV-related deaths averted over the 10 year period when ART initiation rate is increased or ART dropout rate is decreased to achieve a final ART coverage of 55% or 62%. HIV-attributable mortality and disease progression rates in assumption A reduced by 50% on ART vs. off ART instead of 90%: <b>C)</b> The fraction of HIV infections averted and <b>D)</b> The fraction of HIV-related deaths averted over the 10 year period when ART initiation rate is increased or ART dropout rate is decreased to achieve a final ART coverage of 55% or 90%.</p

Model diagrams.

<p><b>X)</b> General model structure showing only what is consistent across all progression assumptions, A, B, C, and D. The following model diagrams show only the ART compartments (A_i) and ART dropout compartments (D_i) and do not show mortality. Key differences are highlighted in red. <b>A)</b> <i>Progression assumption A</i>: ART reduces disease progression rate (<i>σ</i>_i) by a factor <b><i>τ</i></b> while ART dropouts progress at the same rate as ART-naive individuals (<i>δ</i> = 1). <b>B)</b> <i>Progression assumption B</i>: There is no movement between ART compartments; prognosis depends on CD4 at ART initiation. <b>C)</b> <i>Progression assumption C</i>: ART patients progress to higher CD4 categories over time at a per-capita rate <i>ψ</i>_i and the rest is as in progression assumption A. <b>D)</b> <i>Progression assumption D</i>: As in assumption B, there is no movement between ART compartments. However, upon dropping out of ART, individuals move to a higher CD4 category (reflecting improvement in CD4 count on ART) but then progress at an increased rate compared to ART-naive individuals (<i>δ</i>>1; reflecting the rapid CD4 decline which occurs after dropping out of ART).</p

Assumption-specific parameter symbols, definitions, baseline values, and sources.

<p>Assumption-specific parameter symbols, definitions, baseline values, and sources.</p

General parameter symbols, definitions, baseline values, sensitivity analysis ranges, and sources.

<p>General parameter symbols, definitions, baseline values, sensitivity analysis ranges, and sources.</p

Projections from progression assumptions A-D.

<p><b>A)</b> The fraction of HIV infections averted and <b>B)</b> The fraction of HIV-related deaths averted over the 10 year period when increasing ART uptake rate (<i>ε</i>, solid lines) or decreasing ART dropout rate (<b><i>θ</i></b>, dashed lines) to obtain final ART coverage shown.</p

Model fitting data: Baseline values, sensitivity analysis ranges, and sources.

<p>Model fitting data: Baseline values, sensitivity analysis ranges, and sources.</p

Partial rank correlation coefficients (PRCC) between resistance-related parameters and intervention outcomes, relative 10-year CPF (green) and resistance prevalence after 10 years (blue) based on 10, 000 simulations (10 per preselected epidemic set).

<p>The intervention parameters are fixed on their baseline values from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080927#pone-0080927-t001" target="_blank">Table 1</a>, part C. Relative CPF is calculated as the ratio of the 10-year CPF for scenarios with resistance over baseline scenario (no resistance).</p

Parameters and ranges used in the analysis.

<p>Parameters and ranges used in the analysis.</p

Public-health impact of 10 years of consistent PrEP use by 50% of the population projected by the model parameterized with the assumptions extracted from published papers.

<p>The outcomes presented are A) the cumulative fraction of prevented infections (CPF); B) resistance prevalence due to PrEP (RP); C) cumulative fraction of infections in which resistance is transmitted (TRF) and D) resistance contribution to CPF. The boxplots (median, 2.5th, 25th, 75th, 97.5th percentiles) reflect the variation in impact estimates based on 10,000 simulations (10 per preselected epidemic set). In D, the contribution of resistance to CPF is calculated as the percentage change in CPF from simulations in which the resistance is disregarded. Intervention parameters are fixed on their baseline values from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080927#pone-0080927-t001" target="_blank">Table 1</a>, part C.</p

Comparison of the impact of interventions with 70% efficacious VMB used consistently by 60% of the non-pregnant women under different scenarios of VMB use by pregnant women: A) Cumulative fraction of infections prevented over 10 years in women (red), men (blue) and total (green) assuming no change in HIV risk during pregnancy (RR_HIV/preg = 1); B) Cumulative fraction of infections prevented in women; C) Projected HIV prevalence after 10 years assuming no VMB use and VMB use by non-pregnant women only.

<p>D) Cumulative fraction of infections during pregnancy prevented over 10 years. The scenarios with elevated risk during pregnancy use parameter combinations described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073770#pone-0073770-g002" target="_blank">Fig. 2A</a>. The box plots (median, 5th, 25th, 75th, 95th percentiles) reflect the variation in estimates generated by 1,000 different epidemic sets.</p