Modeling HIV-HCV coinfection epidemiology in the direct-acting antiviral era: the road to elimination

Abstract

Background: HCV treatment uptake has drastically increased in HIV-HCV coinfected patients in France since direct-acting antiviral (DAA) treatment approval, resulting in HCV cure in 63% of all HIV-HCV patients by the end of 2015. We investigated the impact of scaling-up DAA on HCV prevalence in the whole HIV population and in various risk groups over the next 10 years in France using a transmission dynamic compartmental model.

Methods: The model was based on epidemiological data from the French Dat'AIDS cohort. Eight risk groups were considered, including high-risk (HR) and low-risk (LR) men who have sex with men (MSM) and male/female heterosexuals, intra-venous drug users, or patients from other risk groups. The model was calibrated on prevalence and incidence data observed in the cohort between 2012 and 2015.

Results: On January 1, 2016, 156,811 patients were registered as infected with HIV in France (24,900 undiagnosed patients) of whom 7938 (5.1%) had detectable HCV-RNA (722 undiagnosed patients). Assuming a treatment coverage (TC) rate of 30%/year (i.e., the observed rate in 2015), model projections showed that HCV prevalence among HIV patients is expected to drop to 0.81% in 2026. Sub-analyses showed a similar decrease of HIV-HCV prevalence in most risk groups, including LR MSM. Due to higher infection and reinfection rates, predicted prevalence in HR MSM remained stable from 6.96% in 2016 to 6.34% in 2026. Increasing annual TC rate in HR MSM to 50/70% would decrease HCV prevalence in this group to 2.35/1.25% in 2026. With a 30% TC rate, undiagnosed patients would account for 34% of HCV infections in 2026.

Conclusions: Our model suggests that DAA could nearly eliminate coinfection in France within 10 years for most risk groups, including LR MSM. Elimination in HR MSM will require increased TC.

Trial registration: ClinicalTrials.gov NCT02898987.

Keywords: Coinfection; Compartmental model; Direct-acting antiviral agent; HCV; HCV elimination; HIV; Mathematical modeling; Treatment uptake.

Conflict of interest statement

Ethics approval and consent to participate

All patients included in the Dat’AIDS cohort signed a written informed consent for the use of their personal data. The Dat’AIDS cohort is registered on ClinicalTrials.gov under reference number NCT02898987.

Consent for publication

Not applicable.

Competing interests

Mr. Victor Virlogeux reports consulting/speaker fees from Sanofi and AbbVie, outside the submitted work. Pr. Fabien Zoulim reports consulting/speaker fees from Gilead Science, Bristol Myers Squibb, and Roche. Dr. Poizot-Martin reports personal fees from Gilead Sciences and MSD, and non-financial support from BMS, outside the submitted work. Dr. Valantin reports personal fees from BMS, Gilead Sciences, Janssen, MSD and ViiV Healthcare, outside the submitted work. Dr. Cuzin reports personal fees from BMS and ViiV Health Care and non-financial support from Janssen and MSD, outside the submitted work. Dr. Reynes reports personal fees from Gilead Sciences, Janssen, Pfizer, MSD and ViiV Heathcare, outside the submitted work. Dr. Billaud reports personal fees from BMS, Gilead, Janssen and ViiV Healthcare, outside the submitted work. Dr. Huleux reports non-financial support from Janssen and ViiV Healthcare, outside the submitted work. Dr. Rey reports personal fees from BMS, Gilead Sciences, MSD, and ViiV Healthcare, outside the submitted work. Dr. Jacomet reports personal fees from Convergence Edition, Gilead Sciences, Janssen, MSD and ViiV Healthcare and non-financial support from Abbvie, Gilead Sciences, Janssen and MSD, outside the submitted work. Dr. Cabié reports non-financial support from BMS, Gilead Sciences and Janssen, outside the submitted work. Dr. Cotte reports grants from ViiV Healthcare and MSD, personal fees from Abbvie, BMS, Gilead Sciences, Janssen, MSD, ViiV Healthcare and non-financial support from Abbvie, BMS, Gilead Sciences, Janssen, MSD and ViiV Healthcare, outside the submitted work. Dr. Pugliese, Dr. Bani-Sadr, Dr. Fresard, Dr Duvivier, Dr. Cheret, Dr. Hustache-Mathieu, and Dr. Hoen have no conflicts of interest to disclose.

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Figures

Fig. 1

Schematic diagram of HCV transmission compartmental model. Individuals are distributed in eight different risk groups (j): males and females for heterosexuals, for intravenous drug users, and for other groups, and low- and high-risk subgroups for men who have sex with men. New individuals enter the susceptible monoinfected categories (X) at a rate θ [20]. Susceptible individuals may be acutely infected (A) at an infection rate βj (estimated during the calibration process for each subgroup). Individuals acutely infected may progress to HCV chronic infection (C) at a rate (1–γ) or spontaneously clear their infection at a rate γ (S). Acute infection lasts an average 1/ψ. Chronically infected individuals start an HCV treatment at an annual rate τ. Treatment lasts an average 1/ω and results in SVR12 in a proportion α of all treated patients. Successfully treated patients or patients with spontaneous clearance may be reinfected with an external force of infection δj

Fig. 2

Goodness-of-fit of the compartmental model to the prevalence data between 2012 and 2016 (a) and projected HCV prevalence over the next 10 years in the overall HIV population (b). To numerically estimate the goodness-of-fit of our model, we calculated a root mean square error (RMSE) of 459 individuals between 2012 and 2016. Vertical lines indicate the RMSE for each year between 2012 and 2016. Different annual treatment coverage rates were considered for the 10-year projection (panel B): 30%, 50%, 70%, and 90%. The number of HIV-HCV coinfected patients in the undiagnosed population is represented with a dashed horizontal line. This population was not considered eligible for direct-acting antiviral treatment

Fig. 3

Projected prevalence (raw numbers) of HIV-HCV coinfection over the next 10 years within each risk group