Hepatitis C elimination in Myanmar: Modelling the impact, cost, cost-effectiveness and economic benefits

Abstract

Background: Myanmar has set national hepatitis C (HCV) targets to achieve 50% of people diagnosed and 50% treated by 2030. The WHO has additional targets of reducing incidence by 80% and mortality by 65% by 2030. We aimed to estimate the impact, cost, cost-effectiveness and net economic benefit of achieving these targets.

Methods: Mathematical models of HCV transmission, disease progression and the care cascade were calibrated to 15 administrative regions of Myanmar. Cost data were collected from a community testing and treatment program in Yangon. Three scenarios were projected for 2020-2030: (1) baseline (current levels of testing/treatment); and testing/treatment scaled up sufficiently to reach (2) the national strategy targets; and (3) the WHO targets.

Findings: Without treatment scale-up, 333,000 new HCV infections and 97,000 HCV-related deaths were estimated to occur in Myanmar 2020-2030, with HCV costing a total $100 million in direct costs (testing, treatment, disease management) and $10.4 billion in lost productivity. In the model, treating 55,000 people each year was sufficient to reach the national strategy targets and prevented a cumulative 40,000 new infections (12%) and 25,000 HCV-related deaths (25%) 2020-2030. This was estimated to cost a total $189 million in direct costs ($243 per DALY averted compared to no treatment scale-up), but only $9.8 billion in lost productivity, making it cost-saving from a societal perspective by 2024 with an estimated net economic benefit of $553 million by 2030. Reaching the WHO targets required further treatment scale-up and additional direct costs but resulted in greater longer-term benefits.

Interpretation: Current levels of HCV testing and treatment in Myanmar are insufficient to reach the national strategy targets. Scaling up HCV testing and treatment in Myanmar to reach the national strategy targets is estimated to generate significant health and economic benefits.

Funding: Gilead Sciences.

Keywords: Elimination; Hepatitis C; Low and middle income country; Mathematical model; Myanmar.

Fig. 1

Hepatitis C transmission, disease progression and care cascade model schematic. Not shown for brevity: liver fibrosis stages F0, F1 and F2 were all explicitly modelled; acute stage of infection and spontaneous clearance was possible after re-infection as well as primary infection.

Fig. 2

Projected epidemiological outputs at a national level, aggregated over the 15 regional models. Projections for (A) people living with HCV (PLHCV); (B) HCV incidence; (C) HCV-related deaths; (D) prevalence of HCV in the general population; and (E) prevalence of HCV among people who inject drugs (PWID). Black dots = data estimates; black line = baseline, orange and blue lines = testing and treatment scaled up to reach the national strategy and WHO strategy targets respectively. Uncertainty bands may decrease over time where scenarios are constrained to reach the same endpoints in 2030.

Fig. 3

Projected cost outputs at a national level, aggregated over the 15 regional models, from a health systems perspective. (A) Total direct annual costs of HCV (testing, treatment and disease management) in the baseline (black), national strategy (orange) and WHO strategy (blue) scenarios; (B) Cost per disability-adjusted life year averted over time, for the national strategy (orange) and WHO strategy (blue) scenarios relative to the baseline. Uncertainty bands may decrease over time where scenarios are constrained to reach the same endpoints in 2030. Costs and DALYs are discounted at 3% per annum.

Fig. 4

Net economic benefit of scaling up testing/treatment to reach the national and WHO targets (at a national level, aggregated over the 15 regional models) from a societal perspective. Difference in cumulative testing, treatment, disease management and productivity costs compared to the baseline.

Fig. 5

Decomposition of the investment requirements across the 15 regional models. Projected testing (green), treatment (yellow) and disease management (red) costs 2020–2030 for the baseline, national strategy and WHO strategy scenarios.