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

Jennifer M Ross; Roger Ying; Connie L Celum; Jared M Baeten; Katherine K Thomas; Pamela M Murnane; Heidi van Rooyen; James P Hughes; Ruanne V Barnabas

doi:10.1016/j.epidem.2017.12.001

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

Epidemics. 2018 Jun:23:34-41. doi: 10.1016/j.epidem.2017.12.001. Epub 2017 Dec 5.

Authors

Jennifer M Ross¹, Roger Ying², Connie L Celum³, Jared M Baeten⁴, Katherine K Thomas⁵, Pamela M Murnane⁶, Heidi van Rooyen⁷, James P Hughes⁸, Ruanne V Barnabas⁹

Affiliations

¹ Department of Medicine, University of Washington, Seattle, WA, USA; Division of Allergy and Infectious Disease, University of Washington, 1959 NE Pacific St., Box 356423, Seattle, WA 98195, USA. Electronic address: [email protected].
² Weill Cornell Medical College, Cornell University, 420 E 70th St., 12J-3, New York, NY 10021, USA. Electronic address: [email protected].
³ Department of Medicine, University of Washington, Seattle, WA, USA; Department of Global Health, University of Washington, 325 9th Ave., Box 359927, Seattle, WA 98104-2420, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA; Division of Allergy and Infectious Disease, University of Washington, 1959 NE Pacific St., Box 356423, Seattle, WA 98195, USA. Electronic address: [email protected].
⁴ Department of Medicine, University of Washington, Seattle, WA, USA; Department of Global Health, University of Washington, 325 9th Ave., Box 359927, Seattle, WA 98104-2420, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA; Division of Allergy and Infectious Disease, University of Washington, 1959 NE Pacific St., Box 356423, Seattle, WA 98195, USA. Electronic address: [email protected].
⁵ Department of Global Health, University of Washington, 325 9th Ave., Box 359927, Seattle, WA 98104-2420, USA. Electronic address: [email protected].
⁶ Department of Global Health, University of Washington, 325 9th Ave., Box 359927, Seattle, WA 98104-2420, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA; Center for AIDS Prevention Studies, Department of Medicine, University of California San Francisco. Electronic address: [email protected].
⁷ Human Sciences Research Council, Durban, South Africa. Electronic address: [email protected].
⁸ Department of Biostatistics, University of Washington, 1959 NE Pacific St., Box 357232, Seattle, WA 98195, USA; Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. Electronic address: [email protected].
⁹ Department of Medicine, University of Washington, Seattle, WA, USA; Department of Global Health, University of Washington, 325 9th Ave., Box 359927, Seattle, WA 98104-2420, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA; Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Division of Allergy and Infectious Disease, University of Washington, 1959 NE Pacific St., Box 356423, Seattle, WA 98195, USA. Electronic address: [email protected].

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/μL, 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/μL was 2.53 years longer for females than males. Relative to a baseline of ART initiation at CD4≤500cells/μL, 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.

Keywords: ART; HIV; HIV prevention; disease progression; herpes simplex virus; mathematical modeling; valacyclovir.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Adult
Africa South of the Sahara / epidemiology
Antiviral Agents / therapeutic use*
Cost-Benefit Analysis
Disease Progression
Female
Follow-Up Studies
HIV Infections / drug therapy*
HIV Infections / epidemiology*
HIV Infections / transmission
Humans
Male
Markov Chains
Valacyclovir / therapeutic use*
Viral Load / drug effects
Viral Load / statistics & numerical data

Substances

Antiviral Agents
Valacyclovir

Abstract

Publication types

MeSH terms

Substances

Grants and funding