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Modeling HIV disease progression and transmission at population-level: The potential impact of modifying disease progression in HIV treatment programs.

ABSTRACT: INTRODUCTION:Mathematical models that incorporate HIV disease progression dynamics can estimate the potential impact of strategies that delay HIV disease progression and reduce infectiousness for persons not on antiretroviral therapy (ART). Suppressive treatment of HIV-positive persons co-infected with herpes simplex virus-2 (HSV-2) with valacyclovir, an HSV-2 antiviral, can lower HIV viral load, but the impact of partially-suppressive valacyclovir relative to fully-suppressive ART on population HIV transmission has not been estimated. METHODS:We modeled HIV disease progression as a function of changes in viral load and CD4 count over time among ART naïve persons. The disease progression Markov model was nested within a dynamic model of HIV transmission at population level. We assumed that valacyclovir reduced HIV viral load by 1.23 log copies/?L, and that persons treated with valacyclovir initiated ART more rapidly when their CD4 fell below 500 due to retention in HIV care. We estimated the potential impact of valacyclovir on onward transmission of HIV in three scenarios of different ART and valacyclovir population coverage. RESULTS:The average duration of HIV infection was 9.5 years. The duration of disease before reaching CD4 200cells/?L was 2.53 years longer for females than males. Relative to a baseline of ART initiation at CD4?500cells/?L, the valacyclovir scenario resulted in 167,000 fewer HIV infections over ten years, with an incremental cost-effectiveness ratio (ICER) of $5276 per HIV infection averted. A Test and Treat scenario with 70% ART coverage and no valacyclovir resulted in 350,000 fewer HIV infections at an ICER of $2822 and $812 per HIV infection averted and QALY gained, respectively. CONCLUSION:Even when compared with valacyclovir suppression, a drug that reduces HIV viral load, universal treatment for HIV is the optimal strategy for averting new infections and increasing public health benefit. Universal HIV treatment would most effectively and efficiently reduce the HIV burden.

SUBMITTER: Ross JM

PROVIDER: S-EPMC5975109 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Modeling HIV disease progression and transmission at population-level: The potential impact of modifying disease progression in HIV treatment programs.

Ross Jennifer M JM Ying Roger R Celum Connie L CL Baeten Jared M JM Thomas Katherine K KK Murnane Pamela M PM van Rooyen Heidi H Hughes James P JP Barnabas Ruanne V RV

Epidemics 20171205

<h4>Introduction</h4>Mathematical models that incorporate HIV disease progression dynamics can estimate the potential impact of strategies that delay HIV disease progression and reduce infectiousness for persons not on antiretroviral therapy (ART). Suppressive treatment of HIV-positive persons co-infected with herpes simplex virus-2 (HSV-2) with valacyclovir, an HSV-2 antiviral, can lower HIV viral load, but the impact of partially-suppressive valacyclovir relative to fully-suppressive ART on po ...[more]

PMID: 29223580

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Project description:We present the Progression and Transmission of HIV (PATH 4.0), a simulation tool for analyses of cluster detection and intervention strategies. Molecular clusters are groups of HIV infections that are genetically similar, indicating rapid HIV transmission where HIV prevention resources are needed to improve health outcomes and prevent new infections. PATH 4.0 was constructed using a newly developed agent-based evolving network modeling (ABENM) technique and evolving contact network algorithm (ECNA) for generating scale-free networks. ABENM and ECNA were developed to facilitate simulation of transmission networks for low-prevalence diseases, such as HIV, which creates computational challenges for current network simulation techniques. Simulating transmission networks is essential for studying network dynamics, including clusters. We validated PATH 4.0 by comparing simulated projections of HIV diagnoses with estimates from the National HIV Surveillance System (NHSS) for 2010-2017. We also applied a cluster generation algorithm to PATH 4.0 to estimate cluster features, including the distribution of persons with diagnosed HIV infection by cluster status and size and the size distribution of clusters. Simulated features matched well with NHSS estimates, which used molecular methods to detect clusters among HIV nucleotide sequences of persons with HIV diagnosed during 2015-2017. Cluster detection and response is a component of the U.S. Ending the HIV Epidemic strategy. While surveillance is critical for detecting clusters, a model in conjunction with surveillance can allow us to refine cluster detection methods, understand factors associated with cluster growth, and assess interventions to inform effective response strategies. As surveillance data are only available for cases that are diagnosed and reported, a model is a critical tool to understand the true size of clusters and assess key questions, such as the relative contributions of clusters to onward transmissions. We believe PATH 4.0 is the first modeling tool available to assess cluster detection and response at the national-level and could help inform the national strategic plan.

Project description:BackgroundThe potential impact of pre-exposure chemoprophylaxis (PrEP) on heterosexual transmission of HIV-1 infection in resource-limited settings is uncertain.Methodology/principle findingsA deterministic mathematical model was used to simulate the effects of antiretroviral PrEP on an HIV-1 epidemic in sub-Saharan Africa under different scenarios (optimistic, neutral and pessimistic) both with and without sexual disinhibition. Sensitivity analyses were used to evaluate the effect of uncertainty in input parameters on model output and included calculation of partial rank correlations and standardized rank regressions. In the scenario without sexual disinhibition after PrEP initiation, key parameters influencing infections prevented were effectiveness of PrEP (partial rank correlation coefficient (PRCC) = 0.94), PrEP discontinuation rate (PRCC = -0.94), level of coverage (PRCC = 0.92), and time to achieve target coverage (PRCC = -0.82). In the scenario with sexual disinhibition, PrEP effectiveness and the extent of sexual disinhibition had the greatest impact on prevention. An optimistic scenario of PrEP with 90% effectiveness and 75% coverage of the general population predicted a 74% decline in cumulative HIV-1 infections after 10 years, and a 28.8% decline with PrEP targeted to the highest risk groups (16% of the population). Even with a 100% increase in at-risk behavior from sexual disinhibition, a beneficial effect (23.4%-62.7% decrease in infections) was seen with 90% effective PrEP across a broad range of coverage (25%-75%). Similar disinhibition led to a rise in infections with lower effectiveness of PrEP (< or = 50%).Conclusions/significanceMathematical modeling supports the potential public health benefit of PrEP. Approximately 2.7 to 3.2 million new HIV-1 infections could be averted in southern sub-Saharan Africa over 10 years by targeting PrEP (having 90% effectiveness) to those at highest behavioral risk and by preventing sexual disinhibition. This benefit could be lost, however, by sexual disinhibition and by high PrEP discontinuation, especially with lower PrEP effectiveness (< or = 50%).

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Modeling HIV disease progression and transmission at population-level: The potential impact of modifying disease progression in HIV treatment programs.

Publications

Modeling HIV disease progression and transmission at population-level: The potential impact of modifying disease progression in HIV treatment programs.

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