METHODS: An age-structured multi-state Markov model was developed to simulate the natural history of HCV infection. We tested three historical incidence scenarios that would give rise to the estimated prevalence in 2009, and calculated the incidence of cirrhosis, end-stage liver disease, and death, and disability-adjusted life-years (DALYs) under each scenario, to the year 2039. In the baseline scenario, current antiviral treatment levels were extended from 2014 to the end of the simulation period. To estimate the disease burden averted under current sustained virological response rates and treatment levels, the baseline scenario was compared to a counterfactual scenario in which no past or future treatment is assumed.
RESULTS: In the baseline scenario, the projected disease burden for the year 2039 is 94,900 DALYs/year (95% credible interval (CrI): 77,100 to 124,500), with 2,002 (95% CrI: 1340 to 3040) and 540 (95% CrI: 251 to 1,030) individuals predicted to develop decompensated cirrhosis and hepatocellular carcinoma, respectively, in that year. Although current treatment practice is estimated to avert a cumulative total of 2,200 deaths from DC or HCC, a cumulative total of 63,900 HCV-related deaths is projected by 2039.
CONCLUSIONS: The HCV-related disease burden is already high and is forecast to rise steeply over the coming decades under current levels of antiviral treatment. Increased governmental resources to improve HCV screening and treatment rates and to reduce transmission are essential to address the high projected HCV disease burden in Malaysia.
OBJECTIVE: To assist with achieving these goals and to inform the development of a national strategic plan for Malaysia, we estimated the long-term burden incurred by the care and management of patients with chronic hepatitis C virus (HCV) infection. We compared cumulative healthcare costs and disease burden under different treatment cascade scenarios.
METHODS: We attached direct costs for the management/care of chronically HCV-infected patients to a previously developed clinical disease progression model. Under assumptions regarding disease stage-specific proportions of model-predicted HCV patients within care, annual numbers of patients initiated on antiviral treatment and distribution of treatments over stage, we projected the healthcare costs and disease burden [in disability-adjusted life-years (DALY)] in 2018-2040 under four treatment scenarios: (A) no treatment/baseline; (B) pre-2018 standard of care (pegylated interferon/ribavirin); (C) gradual scale-up in direct-acting antiviral (DAA) treatment uptake that does not meet the WHO 2030 treatment uptake target; (D) scale-up in DAA treatment uptake that meets the WHO 2030 target.
RESULTS: Scenario D, while achieving the WHO 2030 target and averting 253,500 DALYs compared with the pre-2018 standard of care B, incurred the highest direct patient costs over the period 2018-2030: US$890 million (95% uncertainty interval 653-1271). When including screening programme costs, the total cost was estimated at US$952 million, which was 12% higher than the estimated total cost of scenario C.
CONCLUSIONS: The scale-up to meet the WHO 2030 target may be achievable with appropriately high governmental commitment to the expansion of HCV screening to bring sufficient undiagnosed chronically infected patients into the treatment pathway.
METHODS: Five graph models were fit using data from 1574 people who inject drugs in Hartford, CT, USA. We used a degree-corrected stochastic block model, based on goodness-of-fit, to model networks of injection drug users. We simulated transmission of HCV and HIV through this network with varying levels of HCV treatment coverage (0%, 3%, 6%, 12%, or 24%) and varying baseline HCV prevalence in people who inject drugs (30%, 60%, 75%, or 85%). We compared the effectiveness of seven treatment-as-prevention strategies on reducing HCV prevalence over 10 years and 20 years versus no treatment. The strategies consisted of treatment assigned to either a randomly chosen individual who injects drugs or to an individual with the highest number of injection partners. Additional strategies explored the effects of treating either none, half, or all of the injection partners of the selected individual, as well as a strategy based on respondent-driven recruitment into treatment.
FINDINGS: Our model estimates show that at the highest baseline HCV prevalence in people who inject drugs (85%), expansion of treatment coverage does not substantially reduce HCV prevalence for any treatment-as-prevention strategy. However, when baseline HCV prevalence is 60% or lower, treating more than 120 (12%) individuals per 1000 people who inject drugs per year would probably eliminate HCV within 10 years. On average, assigning treatment randomly to individuals who inject drugs is better than targeting individuals with the most injection partners. Treatment-as-prevention strategies that treat additional network members are among the best performing strategies and can enhance less effective strategies that target the degree (ie, the highest number of injection partners) within the network.
INTERPRETATION: Successful HCV treatment as prevention should incorporate the baseline HCV prevalence and will achieve the greatest benefit when coverage is sufficiently expanded.
FUNDING: National Institute on Drug Abuse.