Effects and cost of different strategies to eliminate hepatitis C virus transmission in Pakistan: a modelling analysis

Abstract

Background: The WHO elimination strategy for hepatitis C virus advocates scaling up screening and treatment to reduce global hepatitis C incidence by 80% by 2030, but little is known about how this reduction could be achieved and the costs of doing so. We aimed to evaluate the effects and cost of different strategies to scale up screening and treatment of hepatitis C in Pakistan and determine what is required to meet WHO elimination targets for incidence.

Methods: We adapted a previous model of hepatitis C virus transmission, treatment, and disease progression for Pakistan, calibrating using available data to incorporate a detailed cascade of care for hepatitis C with cost data on diagnostics and hepatitis C treatment. We modelled the effect on various outcomes and costs of alternative scenarios for scaling up screening and hepatitis C treatment in 2018-30. We calibrated the model to country-level demographic data for 1960-2015 (including population growth) and to hepatitis C seroprevalence data from a national survey in 2007-08, surveys among people who inject drugs (PWID), and hepatitis C seroprevalence trends among blood donors. The cascade of care in our model begins with diagnosis of hepatitis C infection through antibody screening and RNA confirmation. Diagnosed individuals are then referred to care and started on treatment, which can result in a sustained virological response (effective cure). We report the median and 95% uncertainty interval (UI) from 1151 modelled runs.

Findings: One-time screening of 90% of the 2018 population by 2030, with 80% referral to treatment, was projected to lead to 13·8 million (95% UI 13·4-14·1) individuals being screened and 350 000 (315 000-385 000) treatments started annually, decreasing hepatitis C incidence by 26·5% (22·5-30·7) over 2018-30. Prioritised screening of high prevalence groups (PWID and adults aged ≥30 years) and rescreening (annually for PWID, otherwise every 10 years) are likely to increase the number screened and treated by 46·8% and decrease incidence by 50·8% (95% UI 46·1-55·0). Decreasing hepatitis C incidence by 80% is estimated to require a doubling of the primary screening rate, increasing referral to 90%, rescreening the general population every 5 years, and re-engaging those lost to follow-up every 5 years. This approach could cost US$8·1 billion, reducing to $3·9 billion with lowest costs for diagnostic tests and drugs, including health-care savings, and implementing a simplified treatment algorithm.

Interpretation: Pakistan will need to invest about 9·0% of its yearly health expenditure to enable sufficient scale up in screening and treatment to achieve the WHO hepatitis C elimination target of an 80% reduction in incidence by 2030.

Funding: UNITAID.

Conflict of interest statement

Declaration of Interests: NKM has received unrestricted research grants and honoraria from Gilead and Merck unrelated to this work. PV has received unrestricted research grants and honoraria from Gilead, and honoraria from Abbvie.

Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Figures

Figure 1.

Simplified HCV screening model schematic illustrating the key aspects of the screening and treatment intervention pathway. Broadly, the population is split into three categories: (i) those who have never been screened (and eligible for primary Ab screening), (ii) those who have been previously screened Ab- (and eligible for Ab re-screening), and (iii) those who have been previously screened Ab+ (i.e. known Ab+ status). The lattermost category of individuals with known Ab+ status is divided into two sub-categories to indicate whether they have ever been diagnosed or not. The full HCV screening model schematic, including demographic and behavioural compartments, disease progression stages, HCV transmission dynamics, and the screening and treatment intervention cascade of care can be found in Supplementary Figure S1.

Figure 2.

Relative change in incidence and mortality achieved by 2030 compared to 2015 levels for each screening intervention scenario. Intervention scenarios are as follows. Scenario S0: No screening or treatment from 2018 onwards. Scenario SQ: Maintaining status quo treatment of ~150,000 annual treatments from 2018. Scenario S1: One-time screening 90% of the general population by 2030 with 80% referral to care. Scenario S2: One-time screening as in Scenario S1, with prioritisation for PWID and adults (30+ years). Scenario S3: One-time prioritised screening as in Scenario S2, along with re-screening cured and previously Ab-negative/RNA-negative individuals from 2020 (every ten years for non-PWID and annually for PWID). Scenario S4: Scenario S3 with incremental improvements as described in the text. The height of each bar represents the median of 1,151 final model runs, with whiskers indicating 95% uncertainty intervals of runs.

Figure 3.

The cascade of care for Scenarios S1–S4. The heights of each bar show the proportions (numbers above each bar) that are diagnosed, referred, initiated treatment, and achieved SVR relative to the chronic HCV burden in 2018 in the first bar corresponding to 100% (shaded in grey). The full height of the first bar signifies the full burden of HCV infections over 2018–2030 for each scenario which is, specifically, the sum of the chronic HCV burden in 2018 with all new chronic infections that occur from 2018 until 2030 in that scenario. The transitions between each bar indicate the percentage of the previous step in the cascade of care that moves onto the following step. The height of each bar represents the median of 1,151 final model runs, with whiskers indicating 95% uncertainty intervals of runs.

Figure 4.

Estimated (A) total screening and treatment costs, and (B) average costs per cure, for each intervention scenario over 2018–2030. Costs and outcomes are discounted at a standard rate of 3.5% per year. The percentages above each bar in (A) indicate the proportion of total costs that are due to screening.

Figure 5.

Univariate sensitivity analysis on total costs for Scenario S4. Implementing a simplified treatment pathway as in X5 includes fewer visits and laboratory investigations. Details are in Supplementary Materials. DAA: direct-acting antiviral; Ab: antibody; PCR: polymerase chain reaction; CC: compensated cirrhosis; DC: decompensated cirrhosis; HCC: hepatocellular carcinoma; LTFU: lost-to-follow-up; Tx: treatment.