Projected health benefits and cost offsets from the United States National Hepatitis C Elimination Initiative

Abstract

Over 2 million Americans were estimated to have chronic hepatitis C virus (HCV) in 2020. The national hepatitis C elimination initiative provides an opportunity to dramatically expand access to HCV treatment nationally. Using a validated microsimulation model, we projected the health benefits and cost savings of the proposed US national hepatitis C elimination initiative compared with the status quo from 2025 to 2044. The model incorporates HCV disease progression, incidence, diagnosis, treatment, and costs across Medicare, Medicaid, privately insured, justice-involved, and uninsured populations. By 2034, the initiative is projected to reduce the number of persons with HCV to approximately 100,000, compared with 1.3 million under the status quo. Over 10 years (2025–2034), the initiative is projected to avert 20,000 cases of hepatocellular carcinoma, 49,000 cases of diabetes, 25,000 cases of chronic kidney disease, and 24,000 deaths, and add 220,000 life years. These reductions in disease would save an estimated $17.7 billion in healthcare spending, of which $12.2 billion would accrue to the federal government. Over 20 years (2025–2044), the health benefits would more than double and cost offsets would triple compared with 10-year outcomes. The national hepatitis C elimination initiative can substantially reduce HCV-related morbidity and mortality while offsetting healthcare spendings.

In this study the authors project the health and cost benefits of the US national hepatitis C elimination initiative aimed at expanding access to hepatitis C virus (HCV) treatment and eliminating HCV as a public health problem in the U.S.

Introduction

A national hepatitis C elimination initiative, initially proposed by the White House and transitioned to the Cure Hepatitis C Act of 2025 (Bill S.1941), aims to dramatically expand access to hepatitis C virus (HCV) treatment and put the US on a path to eliminating HCV as a public health problem^1,2. The U.S. healthcare system is a mixed public–private system in which coverage is fragmented. Because HCV disproportionately affects individuals covered by Medicaid, those who are uninsured, and justice-involved populations, federal leadership and financing play a central role in the proposed elimination strategy. The Administration projects that this national initiative will treat over 1.5 million individuals over the next 5 years and needs a $9.4 billion upfront investment.

This initiative aims to overcome historic barriers to HCV elimination. Despite the availability of highly-effective oral drugs since 2014—with a cure rate of more than 95%³—over 2 million Americans were estimated to have chronic HCV between January 2017 and March 2020⁴, and about 14,000 people died from HCV-related complications in 2020⁵. In 2020, there were 66,700 estimated new HCV infections, a 97% increase from 2015⁵.

There are several reasons for the slow progress in addressing HCV. First, 40% of the infected people have not been tested and so are unaware of their infection status⁶. Second, at the time of their market launch, the high price of HCV medications served as a major barrier to access and hence to HCV cure⁷. Third, Medicaid and other payers imposed treatment restrictions, including requiring evidence of advanced fibrosis and prolonged sobriety. Though the cost of treatment has come down to $20,000 or less, access to curative drugs remains restricted in some settings⁸. Fourth, HCV disproportionately affects certain marginalized and/or minoritized communities who often have less access to medical care, including those who are uninsured, American Indian and Alaska Native persons, non-Hispanic Black persons, incarcerated populations, and people who inject drugs⁹. These populations have, in particular, experienced rising infection rates in recent years⁶.

The national initiative to eliminate hepatitis C (“the Initiative”) will accelerate the development and deployment of point-of-care HCV diagnostic technologies in the US to enable “test and treat” in one visit; improve access to HCV treatment by establishing a novel national “subscription model” to competitively procure drugs for Medicaid, uninsured, Indian Health Service, and justice-involved populations, and by removing out-of-pocket costs for these drugs for certain Medicare beneficiaries; and expand outreach and capacity for screening and treatment^1,10,11. Under the subscription model, the Initiative will contract with manufacturers to provide a full supply for Medicaid, the Indian Health Service, corrections, and the uninsured for a set amount. This approach, which was pioneered in Australia and utilized in Louisiana, makes it possible to reach far more people than current approaches based on per-patient pricing^12,13. As a condition of receiving HCV medication from the federal government at no cost to states, state Medicaid programs will eliminate cost-sharing and prior authorization requirements, improving the patient experience and reducing patients’ barriers to receiving treatment². Additionally, a significant portion of funds will be directed towards efforts to increase treatment rates, including a national training program and technical assistance for clinicians, a public engagement campaign, and initiatives to increase testing and treatment in opioid treatment programs, federal, state, and local jails and prisons, among other intervention components².

The FY 2025 President’s budget requests $9.4 billion in mandatory funding for the national hepatitis C elimination initiative over 5 years, with a significant amount of the funding redirected from current hepatitis C expenditures². At a time when macroeconomic concerns are focused on deficit reductions, it is important to evaluate how, if at all, investment in this national hepatitis C initiative is associated with health benefits and cost offsets through a reduction in liver-related complications and the extrahepatic manifestation of HCV^14,15. Therefore, in this study, we estimate the health benefits and healthcare savings to the federal government from the national hepatitis C elimination initiative compared to the status quo.

HCV diagnosis and treatment

In 2022, an estimated 59.7% of all persons with HCV were aware of their infection, and 57.0% had been successfully treated. Because of the implementation of the national hepatitis C elimination initiative, 92.5% of all persons living with HCV are projected to be diagnosed, and 89.6% of all achieve a cure within five years of the initiative. Supplementary Fig. 3 shows the annual number of persons living with HCV projected to receive treatment in the next 5 years under this initiative. Among those, 1.05 million (69%) of the patients treated for HCV would be in Medicare or Medicaid, 195,000 (13%) private insurance, and 103,000 (7%) under corrections; the program would include 171,000 (11%) persons without health insurance.

Reduction in HCV disease burden

In 2020, an estimated 1.76 million people were chronically infected with HCV, which was estimated to have decreased to 1.65 million by 2022. The implementation of the national HCV initiative is projected to decrease the number of persons with HCV in the US to about 100,000 by 2034 (Supplementary Fig. 4). In contrast, in the absence of a program, the number of persons with HCV infection would be 1.3 million in 2034.

In the next 10 years, the national hepatitis elimination initiative would reduce the hepatocellular carcinoma incidence rate by 53% to 1.28 cases per 100,000. In the absence of a program, the hepatocellular carcinoma incidence rate will decrease by 27% to 2.07 cases per 100,000. Cumulatively, the initiative would prevent an additional 20,000 cases of hepatocellular carcinoma over 10 years and 43,000 cases over 20 years (Fig. 1). For liver-related deaths, the annual mortality rate would decrease by 46% from 5.00 to 2.70 per 100,000 in the first 10 years of the initiative. In total, the initiative would prevent over 24,000 additional liver-related deaths within 10 years and 69,000 deaths over 20 years. The initiative is also projected to prevent the need for 2500 liver transplants over 10 years and 9100 transplants over 20 years. With the reductions in HCV-related liver disease, the national initiative is projected to save 217,000 years of life compared to the status quo over the next 10 years. This difference continues to grow substantially, with 3,036,000 life years saved at 20 years.

Fig. 1. Esimated reduction in HCV-related complications because of the national hepatitis C initiative over 10 and 20 years.

A hepatocellular carcinoma , B liver-related deaths , C diabetes, D chronic kidney disease.

In addition to the reductions in liver-related disease, the national hepatitis C elimination initiative is projected to prevent 49,000 cases of diabetes over 10 years and 112,000 cases over 20 years (Fig. 1). The initiative would also prevent 25,000 cases of CKD in 10 years and 66,000 cases over 20 years.

Cost savings

Over 10 years, total cost savings attributable to averted liver-related complications and extrahepatic manifestations amount to $17.7 billion ($13.0 billion, if discounted; Supplementary Table 7) for uninsured, private, Medicare, Medicaid, and justice-involved populations (Fig. 2, Supplementary Table 8). Of this $17.7 billion, the federal government will accrue $12.2 billion (69%) ($9.0 billion, if discounted) of the cost savings. Over 20 years, cost savings will accrue to $55.2 billion in total ($30.0 billion, if discounted), of which $39.3 billion ($21.3 billion, if discounted) will accrue to the federal government. By 10 years, 65% of total savings are attributable to the prevention of liver-related outcomes, and by 20 years, 52% of total savings are attributable to the prevention of liver-related outcomes. If extrahepatic illnesses are not considered, the total cost savings directly attributable to HCV sequelae are slightly reduced to $11.5 B at 10 years and $28.9 B at 20 years (Supplementary Table 19). Of this, $8.3 B and $21.4 B will accrue to the federal government by 10 and 20 years, respectively.

Fig. 2. Projected cumulative cost savings (in billion US Dollar) of the national hepatitis C elimination initiative.

A by subpopulation, (B) by whether they are attributable to the federal government or not, (C) and by liver vs extrahepatic disease prevention.

Scenario analyses

The results for all four scenarios and the base case are summarized in Supplementary Table 9. Compared to the base case, under the “half incidence” scenario, there are slightly fewer (less than 1000) cases of hepatocellular carcinoma and liver-related deaths averted within 10 years (Supplementary Fig. 5). At 20 years, the differences are more noticeable, resulting in 5000 and 6000 fewer cases of HCC and deaths averted, respectively (Supplementary Fig. 5). The impact on extrahepatic conditions is larger, with 10,000 fewer diabetes and 5000 fewer CKD cases averted at 10 years, with these numbers reaching 41,000 diabetes and 24,000 CKD cases at 20 years (Supplementary Fig. 5). The “half incidence” scenario correspondingly results in a slight reduction in cost savings of $1.9 billion at 10 years ($15.8 billion; $10.8 billion to the federal government) and $13.6 billion ($41.6 billion; $29.1 billion to the federal government) at 20 years (Supplementary Table 10).

If HCV incidence decreases at the rate of reduction in HCV prevalence, the national initiative would avert an additional 24,000 liver-related deaths and save $39.6 billion in 10 years, with $28.9 billion of savings accrued to the federal government (Supplementary Fig. 6, Supplementary Table 11). The corresponding benefits over 20 years would increase to 69,000 liver-related deaths averted and $217.6 billion saved ($164.3 billion accrue to the federal government).

If the treatment rate in the HCV elimination initiative is reduced to 80%, the number of people treated annually decreases to an average of nearly 300,000 for the five years of the program (Supplementary Fig. 7). This scenario has a similar impact on the disease burden as the base case at both 10 and 20 years, with a difference of less than 1000 fewer cases of HCC and deaths averted and 3000 fewer cases of diabetes and CKD averted (Supplementary Fig. 8). Under this scenario, there is a slight reduction in cost savings of $0.7 billion at 10 years ($17.0 billion; $11.8 billion to the federal government) and $1.3 billion ($53.9 billion; $38.3 billion to the federal government) at 20 years (Supplementary Table 12).

Lastly, the scenario with an elevated status quo treatment cap had a slight reduction in the HCV-related disease burden at both 10 and 20 years (Supplementary Fig. 9). Similarly, this scenario results in a similar reduction in cost savings of $2.2 billion at 10 years ($15.5 billion; $10.7 billion to the federal government) and $9.0 billion ($46.2 billion; $32.6 billion to the federal government) at 20 years (Supplementary Table 13).

One-way sensitivity analysis

Figure 3 shows the ten model parameters that the cost savings and deaths averted outcomes are most sensitive to. The results were most sensitive to parameters related to the likelihood of developing advanced liver disease outcomes (e.g., decompensated cirrhosis, HCC, liver-related death) in cirrhosis patients (both cured and untreated), and incidence of and cost associated with management of CKD and diabetes. Of note, we found that the national initiative remained cost-saving when accounting for uncertainty within each parameter. Additionally, we found that the anticipated impact on the HCV-related disease burden was relatively robust.

Fig. 3. Tornado diagram showing the top 10 most sensitive model parameters associated with outcomes of national hepatitis C elimination initiative. for total 10-year cost savings.

A for total 10-year cost offsets, (B) and liver-related deaths averted.

Discussion

Untreated HCV causes hepatic and extrahepatic complications and leads to substantial morbidity and premature mortality. The national hepatitis C elimination initiative aims to treat over 1.5 million individuals over the next 5 years by overcoming historic barriers to HCV cure. The initiative requires an upfront commitment of resources, and we projected substantial health benefits and cost offsets from those resources. Over 10 years, this analysis finds that the national hepatitis C initiative will avert 20,000 cases of hepatocellular carcinoma, 49,000 cases of diabetes, and 25,000 cases of chronic kidney disease. This reduction in HCV-related disease will prevent 24,000 deaths and add 220,000 life years. These benefits in improved health would reduce $17.7 billion in direct healthcare spending, of which $12.2 billion would accrue to the federal government. Over 20 years, the health benefits of the national initiative would increase by more than two-fold and cost offsets by three-fold.

Achieving the proposed screening rate is ambitious but feasible given the initiative’s investments in point-of-care diagnostics, outreach, and provider training. Nonetheless, barriers such as limited testing capacity, engagement of high-burden populations, and coordination across care settings may affect implementation. While our analysis focuses on the proposed national strategy, targeted approaches—such as prioritizing people who inject drugs, justice-involved populations, or high-burden regions—may offer complementary pathways to elimination and warrant future evaluation.

The projected cost offsets reflect reductions in downstream healthcare spending associated with HCV and do not account for the upfront cost of implementing the cost of the elimination initiative itself. The Cure Hepatitis C Act proposes $9.4 billion in federal funding over five years for the initiative, although a portion of this amount represents reallocation of existing HCV treatment expenditures rather than entirely new spending. Our estimates predict that the initiative would save the federal government $12.2 billion within a 10-year time frame, reflecting reduced Medicare and Medicaid spending on complications of untreated infection. In principle, this projected savings represent the potential budgetary offset associated with avoided disease management, under which the initiative could be cost-saving if program expenditures fall within this range. We acknowledge that the total cost of implementing a nationwide elimination initiative may exceed the $9.4 billion once all programmatic elements are fully accounted for. If the full cost of implementation exceeds the projected offsets, the initiative may not be cost-saving in a budgetary sense. Nevertheless, depending on the final program design and cost structure, it could still be cost-effective, especially in the long term.

Of note, the cost offsets from our model provide a conservative estimate of the value of the national initiative. Several government agencies use the “value of a statistical life” concept to convert mortality risk reductions into dollar terms for overall economic and social benefits^16,17. The US Department of Health and Human Services recommends using $11.4 million (in 2020 dollars) as the value of a statistical life¹⁸. Multiplying this estimate of the value of a statistical life by liver-related deaths averted provides an estimate of the health benefits in dollar value of $275.6 billion over 10 years and $784.6 billion over 20 years—far in excess of the cost of the initiative. Additionally, our model focuses on the HCV-related cost reduction of elevated treatment rates; we do not include some other potential external federal expenses, such as increased social security payments or healthcare management costs for competing illnesses.

Though previous US-based studies did not evaluate the health and economic impact of the national hepatitis C initiative, our findings are consistent with other studies showing that HCV interventions are cost-saving and prevent associated mortality. A systematic review identified 24 relevant cost-effectiveness studies and concluded that antiviral treatment both saves lives and reduces costs¹⁴. A 2023 Milliman white paper found savings from HCV elimination ranging from $28–$46 billion over 10 years¹⁹. Over 30 years, the savings were even greater, between $226 and $257 billion. Another study estimated that antiviral use in the US Veterans Affairs health care would result in cost savings between $7 and $9 billion over 50 years²⁰. In addition, cost savings were achieved in their program as early as 5 years after treatment began. In 2016, the Australian government committed A$1.2 billion for five years of unlimited access to direct-acting antivirals (DAAs). A modeling study by Scott et al. estimated that compared with the counterfactual of no treatment, an HCV elimination scenario would avert 9430 deaths and 25,700 new HCV cases and result in A$1.29 billion savings from disease averted²¹. In addition, a modeling study of six WHO world regions estimated that the HCV elimination scenario would prevent 2.1 million liver-related deaths and 10 million new HCV infections globally between 2018 and 2030²².

There are several limitations to this study. First, in the base case, we did not dynamically model a reduction in HCV transmission because of a reduction in HCV prevalence under the elimination scenario; however, we simulated an additional scenario accounting for a reduction in HCV incidence that showed substantially higher cost savings than our base case results. Second, the successful implementation of this hepatitis C elimination initiative requires careful planning to scale up HCV screening and treatment, and our study does not capture those factors. Third, our model does not incorporate fibrosis regression (partial reversal of liver scarring after HCV cure), which has been associated with reduced risks of cirrhosis progression, hepatocellular carcinoma, and liver-related mortality; therefore, our projected long-term health and economic benefits are likely conservative. Fourth, we did not explicitly model HCV re-infection, but this was incorporated via the inclusion of HCV incident cases. In addition, we did not account for the prevention investment needed to reduce HCV re-infection or incidence. Finally, we underestimated the potential cost savings of the national hepatitis C elimination plan by not modeling the association of HCV treatment with other extrahepatic manifestations, including depression, cardiovascular disease, stroke, and lymphoma.

In conclusion, the national hepatitis C elimination initiative is projected to have a large impact on improving health by averting 24,000 liver-related deaths, adding 220,000 life years, and cost offsets of $17.7 billion over the next 10 years. The national program can virtually eliminate HCV as a public health threat in the US while potentially reducing healthcare spending of the federal government at 10 years and beyond.

Methods

Overview

This study complies with all relevant ethical regulations. Ethical approval was waived because no individual-level data were used; all data were derived from publicly available, aggregate sources. For the same reason, informed consent was not required.

A previously developed mathematical model, Hepatitis C Simulation Model (HEP-SIM), was used to simulate temporal trends in HCV disease burden and cost of care in the US for the next 20 years under the status quo and the national hepatitis C elimination initiative. The HEP-SIM synthesizes information on patient demographics, HCV disease progression, screening and treatment for HCV, access to healthcare (including insurance status), and the cost of care and treatment. The model has been used to project the changing prevalence and outcomes of HCV in the US since 2001 and has been validated with published data and national surveys^23–26. The model was developed in the C++ programming language, and analysis was performed using R, version 4.4.2²⁷.

HEP-SIM is a microsimulation model that tracks individual HCV-infected persons on a yearly (discrete-time) basis. Each individual follows an individual-level state-transition (Markov) process, moving annually between mutually exclusive health states that represent the natural history of HCV infection (Fig. 4). All transitions occur once per year according to published annual transition probabilities (Table 1).

Fig. 4. Schematic of the HCV Natural History Simulation Model.

Each square represents a health state that a patient can exist in. The arrows between states represent annual transition probabilities that can occur. In each state, competing-cause mortality, the background risk of dying from other causes, exists. F0, F1, and F2 represent no fibrosis, portal fibrosis without septa and portal fibrosis with few septa, respectively. F3 indicates severe septal fibrosis, and F4 represents compensated fibrosis. Abbreviations: LT: liver transplant; DCC: decompensated cirrhosis; HCC: hepatocellular carcinoma; LRD: liver-related death.

Table 1.

Annual transition probabilities, disease management costs, and initialization parameters for the hepatitis C virus natural history model

Input	Parameter	Range for Sensitivity Analysis	Reference
HCV Transition Probabilities (Annual)
F0 to F1	0.117	0.104–0.130	52
F1 to F2	0.085	0.07–0.096	52
F2 to F3	0.120	0.109–0.133	52
F3 to F4	0.116	0.104–0.129	52
F4 to DCC	0.039	0.010–0.079	53
F4 to HCC	0.014	0.010–0.079	53
F4-cure to DCC	0.008	0.002–0.036	54
F4-cure to HCC	0.005	0.002–0.013	54
DCC to HCC before DAA	0.068	0.030–0.083	55
DCC to LT	0.023	0.010–0.062	56,57
DCC to HCC Adjustment****	0.700	0.600–0.800	Calibrated
DCC to LRD Adjustment****	0.700	0.600–0.800	Calibrated
DCC (first year) to LRD before DAA	0.182	0.065–0.190	55
DCC (subsequent years) to LRD before DAA	0.112	0.065–0.190	55
HCC to Liver transplant	0.040	0.000–0.140	25,58
HCC to death	0.427	0.330–0.860	53
Liver transplant (first year) to death	0.116	0.060–0.420	59
Liver transplant to death	0.044	0.024–0.110	59
Extrahepatic Disease Probabilities
Diabetes
Prevalence (HCV infected)	0.179	0.112–0.275	35
Prevalence (not HCV infected)	0.138	0.128–0.149	36*
Incidence (untreated)	0.037	0.0366–0.0379	15
Incidence (DAA treated)	0.030	0.0289–0.0315	15
Chronic Kidney Disease (CKD)
Prevalence (HCV infected)	0.201	0.150–0.250	37
Prevalence (not HCV infected)	0.131	0.121–0.144	38*
Incidence (untreated)	0.034	0.0335–0.0347	15
Incidence (DAA treated)	0.031	0.0299–0.0322	15
Disease Management Costs (Annual)
F0–F2	$976	$732–$1220	60–62
F3	$2,005	$1504–$2506	60–62
Compensated cirrhosis	$2,492	$1869–$3115	60–62
Decompensated cirrhosis	$26,014	$19,511–$32,518	60–62
Hepatocellular carcinoma	$47,794	$35,846 - $59,743	60–62
Liver transplant (Year 1)	$138,205	$103,654– $172,756	60–62
Liver transplant (Year 2 + )	$38,635	$28,976–$48,294	60–62
Diabetes	$11,826	$8,870–$14,783	63
Chronic Kidney Disease	$26,980	$22,808–$38,013	64**
Initialization Parameters
HCV Prevalence	See Supplementary Table 2 for calibrated values	--	28***
Prevalence by Subpopulation
Justice-Involved	See Supplementary Table 2	--	29
Medicare, Medicaid, Private, Uninsured	See Supplementary Table 2	--	CDC analysis*
HCV genotype (national estimates)	G1: 75.7%, G2: 10.7%, G3: 11.9%, G4-6: 1.7%	--	65
HCV fibrosis stages (national estimates)	Calibration Parameter	--	Calibrated
HCV incidence	See Supplementary Table 3	--	32
HCV awareness rates	See Supplementary Table 15 for insurance status and age-specific values	--	66
Age Distribution by Subpopulation	See Supplementary Table 16	--	10,11*

Abbreviations. F0 to F4: Metavir liver fibrosis stage; DAA: direct-acting antiviral; LT: liver transplant; DCC: decompensated cirrhosis; HCC: hepatocellular carcinoma; LRD: liver-related death

^*These parameters were estimated through a linear extrapolation through 2023 that used the midpoint year of each NHANES cycle and the prevalence estimate.

^**The annual cost of managing CKD was calculated as a weighted average combined the frequency and cost of managing each CKD stage.

^***Based on unpublished recent CDC analysis that used multiple state- and national-level datasets^67–71.

^****Values listed as ‘adjustments’ are multiplicative calibration factors applied to published pre-DAA transition probabilities to reflect lower progression rates following introduction of direct-acting antivirals.

HCV prevalence and incidence

National data were included to align the model to the US-specific HCV epidemic from 2015 onward, including the HCV prevalence and distribution by subpopulation, HCV genotype, fibrosis stage, incident cases, infection awareness rates, and age distribution by subpopulation.

The model was initialized with HCV prevalence in 2015 using multiple data sources and a national survey (Supplementary Table 1)²⁸. Our model incorporates HCV prevalence estimates derived from the National Health and Nutrition Examination Survey (NHANES) (representing the civilian, non‑institutionalized US population) and also includes populations not captured by NHANES, such as people who are incarcerated, homeless, or living in other institutional settings²⁸. We further incorporated updated data on the justice-involved population size from HepCorrections (Supplementary Table 2)^29–31.

In addition to the prevalent cases, the model accounts for incident HCV cases using the estimated annual cases in the CDC’s Viral Hepatitis Surveillance Report from 2011–020, which were calculated by multiplying the reported incident case counts by 13.9, which was derived by the CDC to account for under-reporting and under-ascertainment of incident HCV cases (Supplementary Table 3)^32–34. From 2021 to 2050, the number of incident HCV cases is extrapolated based on a linear trend between 2011 to 2020. These cases are then distributed between the high- and low-risk subpopulations in a 2.55 to 1 ratio by subpopulation (Supplementary Table 4)³². Reinfection following cure was not explicitly modeled because reliable, nationally representative reinfection rates—particularly for high-risk subpopulations—are unavailable. Instead, reinfection and new infections are jointly reflected through the annual incident case estimates.

To confirm the validity of our outcomes, the simulation results were compared with published studies and national data, including the chronic HCV prevalence in 2015 (Supplementary Fig. 1A) and liver-related deaths from 2015–2019 (Supplementary Fig. 1B)^28,32.

The natural history of HCV

The natural history of HCV is simulated as an individual-level state-transition model (Fig. 4), where at any given time, an HCV-infected person exists in one of the following states: acute HCV infection; spontaneously resolved acute infection; chronic HCV defined by one of the five METAVIR liver fibrosis states ranging from F0 (no fibrosis) to F4 (compensated cirrhosis); sustained virologic response, which is indicative of cure of HCV infection; decompensated cirrhosis; hepatocellular carcinoma; liver-transplant recipient; and liver-related death. HCV-infected persons can progress to the next state or stay in their current state, according to the transition probabilities in Table 1. Patients in the F0 to F3 stages who are successfully treated with antivirals transition to the ‘cure’ state. Patients with F4 state who are successfully treated with antivirals move to the ‘F4-cure’ state, with the likelihood of further progression to an advanced liver disease state (decompensated cirrhosis or hepatocellular carcinoma) greatly diminished but still possible. Persons in the decompensated cirrhosis, hepatocellular carcinoma, or liver transplant states have a heightened risk of liver-related mortality. We also applied background mortality by age and sex to each health state.

HCV diagnosis and treatment

After being infected with HCV, an individual may progress through the unaware (not yet diagnosed), aware (diagnosed), and eventually the treated stages. An individual’s likelihood of progressing through these states is dynamic and based on a variety of factors, including age, calendar year, insurance type, and the presence of a national elimination initiative. A complete description of these rates and probabilities is included in the accompanying online supplement.

Extrahepatic manifestations of HCV

The prevalence and incidence of diabetes and chronic kidney disease (CKD) are higher among those with an HCV infection than those without^35–38. Evidence suggests a causal association between chronic HCV infection and these conditions through inflammatory, metabolic, and immune-mediated pathways^39–41. Longitudinal data demonstrate reduced incidence of diabetes and CKD following direct-acting antiviral therapy compared with those having active HCV^15,42,43. To capture these dynamics in our model, individuals are initialized with diabetes and CKD according to published prevalence estimates that differ for persons with chronic HCV versus those without infection, and yearly transitions to incident diabetes and CKD are simulated separately for HCV-infected and cured persons. Because of this strong association between HCV treatment and diabetes and CKD, the model simulates the incidence of diabetes and CKD separately for HCV-infected and cured persons (Table 1).

Cost of illnesses averted

To evaluate the economic impact of potential interventions, the model incorporates the cost of managing liver-related complications, diabetes and CKD. The annual cost of managing each complication is based on previously published analyses (Table 1). Disease management costs include expenses for routine monitoring, diagnostic tests, imaging, follow-up consultations, inpatient hospitalization, and state-specific treatments associated with distinct stages of liver disease, including cirrhosis, hepatocellular carcinoma, and liver transplant. We also accounted for costs associated with the management of diabetes and CKD. All disease management costs were converted into 2023 USD.

Simulated strategies and outcomes

We simulated two strategies: “status quo” and “national hepatitis C elimination initiative.” We assume the universal screening rate will be 5% per year from 2024 onwards under the status quo and 18% annually under the national hepatitis C elimination scenario. This screening rate was selected to align with the proposed national initiative under which at least 300,000 persons become aware of their HCV status (and thus are eligible for HCV treatment) each year.

Under the status quo, the annual treatment rate is capped at the 2020 treatment volume of 83,740 patients (Supplementary Table 5)⁴⁴. In the national elimination scenario, it is assumed that 90% of all diagnosed patients in that year will receive treatment in the same year, and the remaining 10% will be eligible to receive treatment next year. Every year, under both strategies, the number of treated patients is distributed across the different subpopulations according to the probability of being eligible for treatment (Supplementary Table 6). These screening and treatment uptake assumptions reflect the operational goals of the national initiative and are informed by evaluations of large-scale HCV elimination programs in Egypt, Rwanda, and the Veterans Health Administration^45–47. The 18% annual screening rate matches the program’s target of diagnosing 300,000 individuals per year, while the 90% treatment assumption serves as a modeling device to achieve the legislatively articulated treatment scale and should not be interpreted as a prediction of treatment uptake in all settings or populations.

For each strategy, the status quo and national hepatitis C elimination initiative, the model simulated the number of people getting diagnosed and receiving HCV treatment, the incidence of hepatocellular carcinoma and extrahepatic manifestations, liver-related deaths, and years of life saved for 10- and 20-year post-implementation.

For each strategy, we also evaluated the total cost of illness averted. We further estimated the cost of illness averted to the federal government. We assume that 85% of Medicare savings accrue to the federal government⁴⁸. Similarly, 80% of Medicaid savings in the model are attributable to the federal government because many persons living with HCV will be in an eligibility category that the federal government pays a 90% match⁴⁹. Because many persons who are uninsured, in corrections, or privately insured today may require Medicaid for care of complications of HCV, we assume that 70% of the savings in care for the uninsured, 20% of privately insured, and 50% of those in corrections will accrue to Medicaid. We also evaluated outcomes by discounting future cost savings at 3% per year (Supplementary Table 7).

Uncertainty and sensitivity analyses

Uncertainty in parameter values was evaluated through one-way sensitivity analyses, using lower and upper bounds specified in Table 1. To address first-order stochastic uncertainty inherent in microsimulation, we executed the model ten times with different random seed values and averaged the results. Because of the very large, simulated population, the Monte Carlo error in aggregated outcomes is negligible, and repeated runs were used primarily to ensure output stability.

Scenario analyses: changes to HCV incidence or treatment

To ascertain the sensitivity of the primary model results, four distinct scenarios were included to evaluate the impact of changes in HCV incidence and scenario treatment rates. These include 1) a “half-incidence” scenario, 2) a “decreasing incidence” scenario, 3) a reduced 80% treatment rate for the national initiative, and 4) an elevated treatment rate for the status quo.

In the base case, HCV incident cases are assumed to increase annually from 2021–2050 based on an extrapolation of the CDC’s estimated incident case counts from 2011–2020, which accounted for underreporting of HCV incidence using the multiplier of 13.9 based on peer-reviewed data (Supplementary Table 3)^32–34. However, to account for the possibility that underreporting is no longer as severe as it was when the data underlying this multiplier were collected, notably before the widespread availability of effective DAAs, the “half incidence” scenario was modeled. This scenario relies on the CDC’s reported HCV incidence estimates through 2020, then reduces the multiplier to 6.95 for subsequent years for both the status quo and national hepatitis C elimination initiative to simulate a possible lower-bound for cost savings and illnesses averted.

Additionally, a ‘decreasing incidence’ scenario was modeled as a theoretical best-case condition in which the number of new infections in the lower-risk population declines in proportion to the reduction in the chronic HCV reservoir achieved by the initiative, while high-risk incidence among persons who inject drugs is assumed to follow current CDC trends. This scenario illustrates the maximum potential impact on downstream disease and costs if transmission falls in parallel with reductions in prevalent infection.

In terms of treatment rates, a new scenario was modeled to evaluate the impact of the HCV treatment rate under the national elimination initiative on the disease burden and cost offsets. In this scenario, the model assumes a reduced annual treatment rate of 80% during the program. Lastly, to consider the potential that 2020 had a uniquely low treatment rate due to the COVID-19 pandemic, a fourth scenario that utilized the median of 2019 and 2020 treatment amounts (99,362 people) as the treatment cap for the status quo scenario was created⁴⁴. This scenario can discern the impact on model results if the background treatment rate were moderately higher than assumed in the base case.

Model coding, verification, and validation

The HEP-SIM model adheres to good modeling and coding practices consistent with the ISPOR-SMDM Modeling Task Force recommendations⁵⁰. Validation and verification followed a multi-step process that included: establishing face validity to ensure that model structure and outputs aligned with the natural history of HCV and expert expectations; conducting external validation by comparing simulated prevalence, liver-related mortality, and treatment trends with national surveillance data and published real-world studies; and performing internal verification through multiple extreme-case and stress-test scenarios guided by the TECH-VER checklist to identify and correct logical or coding errors during model development⁵¹.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Author contributions

J.C., A.A, H.Z, and J.M.S. conceived and designed the study. J.C., A.A. and H.Z. developed the HEP-SIM model. A.A. and H.Z. performed the data analyses. N.S., R.I., H.J.A., Y.Z., J.M.S., and J.W.W. provided critical input on model parameters, policy context, and interpretation of results. J.C., A.A., and H.Z. drafted the manuscript. All authors reviewed, edited, and approved the final manuscript.

Peer review

Peer review information

Nature Communications thanks Sophy Shih, David Tordrup, who co-reviewed with Hannah Schirrmacher, and the other anonymous reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Funding

This study was supported in part by the National Science Foundation (Award number 1722665); the Centers for Disease Control and Prevention (Cooperative Agreement Number NU38OT000141); Arnold Ventures through a grant to Johns Hopkins; and the Coalition for Global Hepatitis Elimination, a program of the Task Force for Global Health. The content is solely the responsibility of the authors and does not represent the views of the funding agencies.

Data availability

The simulation model input parameters used in this study are provided in Table 1 and Supplementary Tables (Supplementary Tables 1–16) of the Supplementary Information. The publicly available datasets used to parameterize and validate the model include the National Health and Nutrition Examination Survey (NHANES; https://www.cdc.gov/nchs/nhanes/), CDC Viral Hepatitis Surveillance Reports (https://www.cdc.gov/hepatitis/statistics/), HepCorrections (http://www.hepcorrections.org/), and the Healthcare Cost and Utilization Project (HCUP; https://hcup-us.ahrq.gov/). Model-generated output data supporting the findings of this study are provided in the Supplementary Information.

Code availability

The custom code for the HEP-SIM microsimulation model used in this study has been deposited on CodeOcean (DOI: 10.24433/CO.0468984.v1 and 10.24433/CO.5385661.v1). The model was developed in C++, and analysis was performed using R, version 4.4.2.

Competing interests

J.M.S. and R.I. work part-time on a federal detail at the National Institutes of Health (NIH) and advise on the national hepatitis C initiative. J.W.W. works for the Task Force for Global Health, which receives funding for the general support of the Coalition for Global Hepatitis Elimination from Abbott, AbbVie, Cepheid, Gilead, Merck, Pharco, Roche, Siemens, VBI Vaccines, Zydus-Cadila, US governmental agencies, and philanthropic organizations. J.C. owns a partnership in Value Analytics Labs. A.A., H.Z., N.S., H.J.A., and Y.Z. report no competing interests.

Supplementary information

The online version contains supplementary material available at 10.1038/s41467-026-74734-1.