# Cost-effectiveness of community-based screening and treatment for chronic hepatitis B in The Gambia: an economic modelling analysis

Shevanthi Nayagam, Lesong Conteh, Elisa Sicuri, Yusuke Shimakawa, Penda Suso, Saydiba Tamba, Ramou Njie, Harr Njai, Maud Lemoine, Timothy Hallett, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Shevanthi Nayagam, Lesong Conteh, Elisa Sicuri, Yusuke Shimakawa, Penda Suso, et al.. Cost-effectiveness of community-based screening and treatment for chronic hepatitis B in The Gambia: an economic modelling analysis. The Lancet global health, 2016, 4 (8), pp.e568-e578. 10.1016/S2214-109X(16)30101-2. pasteur-02875275

HAL Id: pasteur-02875275

https://pasteur.hal.science/pasteur-02875275

Submitted on 19 Jun 2020

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>
# Cost-effectiveness of community-based screening and treatment for chronic hepatitis B in The Gambia: an economic modelling analysis

Shevanthi Nayagam, Lesong Conteh, Elisa Sicuri, Yusuke Shimakawa, Penda Suso, Saydiba Tamba, Ramou Njie, Harr Njai*, Maud Lemoine, Timothy B Hallett, Mark Thursz

<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

## Summary

**Background** Despite the high burden of hepatitis B virus (HBV) infection in sub-Saharan Africa, absence of widespread screening and poor access to treatment leads to most people remaining undiagnosed until later stages of disease when prognosis is poor and treatment options are limited. We examined the cost-effectiveness of community-based screening and early treatment with antiviral therapy for HBV in The Gambia.

**Methods** In this economic evaluation, we combined a decision tree with a Markov state transition model to compare a screen and treat intervention consisting of adult community-based screening using a hepatitis B surface antigen (HBsAg) rapid test and subsequent HBV antiviral therapy versus current practice, in which there is an absence of publicly provided screening or treatment for HBV. We used data from the PROLIFICA study to parameterise epidemiological, primary screening, and cost information, and other model parameter inputs were obtained from a literature search. Outcome measures were cost per disability-adjusted life-year (DALY) averted; cost per life-year saved; and cost per quality-adjusted life-year (QALY) gained. We calculated the incremental cost-effectiveness ratios (ICERs) between current practice and the screen and treat intervention. Costs were assessed from a health provider perspective. Costs (expressed in 2013 US$) and health outcomes were discounted at 3% per year.

**Findings** In The Gambia, where the prevalence of HBsAg is 8.8% in people older than 30 years, adult screening and treatment for HBV has an incremental cost-effectiveness ratio (ICER) of $540 per DALY averted, $645 per life-year saved, and $511 per QALY gained, compared with current practice. These ICERs are in line with willingness-to-pay levels of one times the country's gross domestic product per capita ($487) per DALY averted, and remain robust over a wide range of epidemiological and cost parameter inputs.

**Interpretation** Adult community-based screening and treatment for HBV in The Gambia is likely to be a cost-effective intervention. Higher cost-effectiveness might be achievable with targeted facility-based screening, price reductions of drugs and diagnostics, and integration of HBV screening with other public health interventions.

**Funding** European Commission.

**Copyright** © The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license.

## Introduction

An estimated 250 million people worldwide are chronically infected with hepatitis B virus (HBV), which is often asymptomatic during the early stages of disease.¹ If left untreated, about 25% of infected individuals will progress to cirrhosis or hepatocellular carcinoma, for which prognosis is poor. Approximately 1 million people die every year from HBV-related end-stage liver disease; the burden is concentrated in resource-poor settings, including West Africa, where more than 70% of cases of hepatocellular carcinoma in people younger than 50 years are caused by HBV.² Screening, which aims to identify people with asymptomatic infection and offer early intervention with antiviral therapy, could be an important public health measure to prevent HBV-related morbidity and mortality.

International recommendations, including the new WHO guidelines, recommend treatment for chronic HBV infection.³ However, in practice, publicly funded

treatment for HBV mono-infection is not available in sub-Saharan Africa.⁴ Poor infrastructure, high diagnostic and treatment costs, limited community awareness, and absence of trained health-care professionals are just a few of the possible contributing factors that account for this discrepancy. Treatment for chronic HBV infection, without active screening, has been shown to be cost-effective in many settings;⁵,⁶ however, screening studies have focused on high-risk target groups in high-income countries rather than the general population in highly endemic low-income countries.⁷ The advent of potent antiviral drugs such as tenofovir, now available at generic prices for HIV treatment but effective in the treatment of both HIV and HBV, makes screening and treatment for chronic HBV infection potentially feasible in more low-income and middle-income countries.

To our knowledge, this study is the first economic evaluation of a community screening and treatment

Lancet Glob Health 2016; 4: e568-78

See Editorial page e502

See Comment page e507

Division of Digestive Diseases, St Mary's Hospital, (S Nayagam MBBS, M Lemoine PhD, Prof M Thursz MD), Department of Infectious Disease Epidemiology, School of Public Health (S Nayagam, Prof T B Hallett PhD), and Health Economics Group, Department of Infectious Disease Epidemiology, School of Public Health (L Conteh PhD, E Sicuri PhD), Imperial College, London, UK; ISGlobal, Barcelona Centre for International Health Research (CRESIB), Hospital Clinic, Universitat de Barcelona, Barcelona, Spain (E Sicuri); Medical Research Council Laboratories, The Gambia Unit, Fajara, The Gambia

(Y Shimakawa PhD, P Suso BSc, S Tamba, H Njai PhD, M Lemoine); Unité d'Epidémiologie des Maladies Emergentes, Institut Pasteur, Paris, France

(Y Shimakawa PhD); and International Agency for Research on Cancer (IARC), Lyon, France (R Njie PhD)

*Dr Njai died in October, 2014

Correspondence to: Dr Shevanthi Nayagam, Division of Digestive Diseases, St Mary's Hospital, Imperial College, London W2 1NY, UK
s.nayagam01@imperial.ac.uk
## Research in context

### Evidence before this study

We searched PubMed for articles published before September, 2015, with terms incorporating "Hepatitis B", "HBV", or "CHB" and "Cost*" or "Economic" and "Screen*", "Test*", or "Diagnosis". We found no previous studies describing costs or cost-effectiveness of community-based screening for hepatitis B virus (HBV) infection in low-income or middle-income countries. Research in high-income countries included two previous community-based studies of cost-effectiveness of screening, and further studies of screening in groups classified as high risk, including immigrant populations, many of which were based on hypothetical cohorts, rather than real-life screening data.

### Added value of this study

To our knowledge, this study is the first to investigate the cost-effectiveness of adult screening and treatment for HBV at the community level in a low-income or middle-income setting.

Furthermore, the study includes real-life cost and effectiveness parameter data from a large-scale screening and treatment programme in The Gambia. The model incorporates clinically salient features and is unique in presenting results using three different outcome measures.

### Implications of all the available evidence

Ambitious targets for improving testing and treatment for HBV form part of the recent WHO Global Health Sector Strategy for viral hepatitis. Evidence on how to achieve these targets will be needed to help guide national policies. Screening and treatment for hepatitis B has been shown to be a feasible and cost-effective intervention in The Gambia and should be considered as a public health strategy to reduce mortality and morbidity from cirrhosis and liver cancer. Our study helps to inform such decisions, and highlights the need for further similar analyses in other highly endemic countries.

strategy for chronic HBV infection in a low-income or middle-income setting. It aims to inform decisions on health policy and resource allocation by presenting the possible costs and benefits of improving rates of diagnosis and treatment of people with asymptomatic HBV infection in sub-Saharan Africa, a strategy that has so far had a very limited evidence base.

## Methods

### Model structure

We developed a decision tree representing the intervention characteristics of screening and treatment and combined this tree with Markov models representing the untreated and treated natural history of chronic HBV infection (appendix). We identified eight mutually exclusive health domains to represent the clinical states of the natural history of chronic HBV infection, in accordance with internationally accepted definitions.⁶⁰ These stages were based on HBeAg status (a serological marker representing high infectivity), HBV viral load, alanine aminotransferase concentration, and degree of liver fibrosis. Transition parameters between health states were obtained from results of a literature review (table 1). The model was created in Tree Age Pro 2014 and was used to simulate disease progression in the cohorts, in annual cycles for a period of 40 years. We used data from the PROLIFICA study to parameterise epidemiological, screening, and cost information, and other model parameter inputs were obtained from a literature search.

### Study setting

The multicentre PROLIFICA study assessed the feasibility of a screen and treat HBV intervention programme across the western part of The Gambia (NCT02129829). Study methods are described in detail

elsewhere.⁶¹ The study was approved by The Gambia Government/MRC Joint Ethics committee.

### Comparator strategies

In this economic evaluation, we compared the screen and treat intervention versus current practice. Our baseline strategy reflects current practice—specifically, the absence of publicly provided screening or treatment for HBV in The Gambia. Therefore, costs for this strategy reflect those incurred if and when patients present at the later stages of disease because of morbidity from cirrhosis and hepatocellular carcinoma, when patient outcomes are also poorer.

For the screen and treat intervention, community-based screening consisted of initial community sensitisation, door-to-door household registration of eligible participants (aged ≥30 years), and testing for hepatitis B surface antigen (HBsAg; a marker of being infected with HBV), by use of a rapid point-of-care test.⁶¹ This part of the intervention was carried out by field workers. Individuals with a positive test result were offered outpatient review for diagnostic assessment including routine blood tests, HBV viral load, screening for co-infection with HIV, hepatitis C virus (HCV), or hepatitis delta virus (HDV), liver ultrasound scan, and transient elastography (FibroScan) for assessment of liver fibrosis. Patients meeting European Association for the Study of the Liver (EASL) criteria⁶⁰ for treatment were prescribed tenofovir monotherapy. Standard monitoring was done in accordance with international guidelines and we assumed lifelong treatment. We assumed that there was no resistance to tenofovir¹³ and that antiviral treatment would halt disease progression (if patients were completely adherent to treatment). However, for individuals with already established cirrhosis, there

See Online for appendix
<table><thead><tr><th></th><th>Base-case value</th><th>Deterministic range</th><th>PSA distribution</th><th>PSA parameters</th><th>Source*</th><th>Further description</th></tr></thead><tbody><tr><td colspan="7"><strong>Intervention costs</strong></td></tr><tr><td>One-off activity</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Screening cost per person (US$)</td><td>7.43</td><td>3.72-14.9</td><td>Gamma<sup>†</sup></td><td>a=100; λ=13.4</td><td>Primary data, PROLIFICA</td><td>Initial assessment visit includes routine blood tests, virology, ultrasound scan, transient elastography (FibroScan), and staff costs</td></tr><tr><td>Initial assessment visit (US$)</td><td>120</td><td>60-200</td><td>Gamma</td><td>±20% range for each component part</td><td>Primary data, PROLIFICA</td><td>Initial assessment visit includes routine blood tests, virology, ultrasound scan, transient elastography (FibroScan), and staff costs</td></tr><tr><td>Annual management</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Drug treatment (US$)</td><td>48</td><td>24-207</td><td>Point estimate</td><td>±20% range for each component part</td><td>Ref 8</td><td>Treatment consisted of antiviral therapy with daily tenofovir at generic price</td></tr><tr><td>Monitoring on treatment (US$)</td><td>36.88</td><td>30-44</td><td>Gamma</td><td>±20% range for each component part</td><td>Primary data, PROLIFICA</td><td>Monitoring is done every 6 months in the treated stages of chronic HBV infection</td></tr><tr><td>Monitoring not on treatment (US$)</td><td>15.77</td><td>13-32</td><td>Gamma</td><td>±20% range for each component part</td><td>Primary data, PROLIFICA</td><td>Monitoring is done yearly in the untreated stages of chronic HBV infection</td></tr><tr><td colspan="7"><strong>Costs of hospital admission</strong></td></tr><tr><td>Cost per day of hospital stay (US$)</td><td>6.66</td><td>..</td><td>..</td><td>..</td><td>Ref 9</td><td>WHO-CHOICE values are given minus drug and laboratory costs; therefore, we have multiplied by a factor of two to account for these</td></tr><tr><td>Average length of hospital stay (days)</td><td>7.15</td><td>..</td><td>..</td><td>..</td><td>Ref 9</td><td>..</td></tr><tr><td>Cost per hospital admission (US$)</td><td>47.24</td><td>..</td><td>Gamma<sup>†</sup></td><td>a=3.57; λ=0.0756</td><td>Ref 9</td><td>Average cost per hospital admission in stages of compensated cirrhosis, decompensated cirrhosis, and hepatocellular carcinoma is equal to the average length of stay multiplied by the cost per day of hospital stay</td></tr><tr><td>Number of hospital admissions per year for compensated cirrhosis</td><td>2</td><td>..</td><td>Uniform</td><td>low=0; high=4</td><td>Assumption</td><td>Annual cost of hospital admission in each stage is equal to the cost per hospital admission multiplied the number of hospital admissions per year</td></tr><tr><td>Number of hospital admissions per year for decompensated cirrhosis</td><td>3</td><td>..</td><td>Uniform</td><td>low=0; high=6</td><td>Assumption</td><td>Annual cost of hospital admission in each stage is equal to the cost per hospital admission multiplied the number of hospital admissions per year</td></tr><tr><td>Number of hospital admissions per year for hepatocellular carcinoma</td><td>3</td><td>..</td><td>Uniform</td><td>low=0; high=6</td><td>Assumption</td><td>Annual cost of hospital admission in each stage is equal to the cost per hospital admission multiplied the number of hospital admissions per year</td></tr><tr><td>Average annual cost of hospital admission for compensated cirrhosis (US$)</td><td>95.24</td><td>0-190</td><td>..</td><td>..</td><td>Based on above</td><td>Annual cost of hospital admission in each stage is equal to the cost per hospital admission multiplied the number of hospital admissions per year</td></tr><tr><td>Average annual cost of hospital admission for decompensated cirrhosis (US$)</td><td>142.86</td><td>48-286</td><td>..</td><td>..</td><td>Based on above</td><td>Annual cost of hospital admission in each stage is equal to the cost per hospital admission multiplied the number of hospital admissions per year</td></tr><tr><td>Average annual cost of hospital admission for hepatocellular carcinoma (US$)</td><td>142.86</td><td>48-286</td><td>..</td><td>..</td><td>Based on above</td><td>Annual cost of hospital admission in each stage is equal to the cost per hospital admission multiplied the number of hospital admissions per year</td></tr><tr><td colspan="7"><strong>Epidemiological parameters‡</strong></td></tr><tr><td>HBsAg prevalence (%)</td><td>8.8%</td><td>0-15%</td><td>Point estimate</td><td>..</td><td>PROLIFICA</td><td>..</td></tr><tr><td>Screening uptake (%)</td><td>68.9%</td><td>63-97%</td><td>Point estimate</td><td>..</td><td>PROLIFICA (ref 10)‡</td><td>Intervention coverage reported in the PROLIFICA study was used as a proxy for uptake of screening, as we can assume all eligible individuals were offered screening, given the study design</td></tr><tr><td>Linkage to care (%)</td><td>81.3%</td><td>62-95%</td><td>Point estimate</td><td>..</td><td>PROLIFICA (ref 11)‡</td><td>Defined as attendance at the first clinic appointment after being tested HBsAg positive in the community</td></tr><tr><td>Adherence to treatment in year 1 (%)</td><td>80.9%</td><td>77-95%</td><td>Point estimate</td><td>..</td><td>PROLIFICA (ref 12)‡</td><td>Adherence to antiviral therapy in the first year of treatment</td></tr><tr><td>Annual rate of drop-out of treatment after year 1 (%)</td><td>2%</td><td>1-5%</td><td>Point estimate</td><td>..</td><td>Assumption</td><td>Yearly drop-out rate from second year of antiviral treatment onwards</td></tr><tr><td>Annual resistance to treatment (%)</td><td>0%</td><td>0-2% (after year 6)</td><td>Point estimate</td><td>..</td><td>Ref 13</td><td>..</td></tr></tbody></table>

(Table 1 continues on next page)
<table><thead><tr><th></th><th>Base-case value</th><th>Deterministic range</th><th>PSA distribution</th><th>PSA parameters</th><th>Source*</th><th>Further description</th></tr></thead><tbody><tr><td colspan="7">(Continued from previous page)</td></tr><tr><td>Annual risk of developing hepatocellular carcinoma in individuals with compensated cirrhosis on antiviral therapy (%)</td><td>0.5%</td><td>0-1%</td><td>Beta</td><td>a=0.747; b=149</td><td>Refs 14, 15</td><td>..</td></tr><tr><td>Annual risk of developing hepatocellular carcinoma in individuals with decompensated cirrhosis on antiviral therapy (%)</td><td>1%</td><td>0-4.4%</td><td>Beta</td><td>a=0.808; b=80.0</td><td>Refs 14, 15</td><td>..</td></tr><tr><td>Sensitivity of HBsAg POC test (%)</td><td>88.5%</td><td>85.1-98.2%</td><td>Point estimate</td><td>..</td><td>PROLIFICA (refs 16,17)‡</td><td>Patients with false-positive results on screening are seen in clinic and have full diagnostic assessment including confirmatory HBsAg serology; they are then discharged from care and do not receive unnecessary treatment. Patients with false-negative results are those who tested HBsAg negative at screening, and are therefore not followed up in clinic and do not receive treatment; they progress in the model as per the untreated natural history of HBV</td></tr><tr><td>Specificity of HBsAg POC test (%)</td><td>100%</td><td>99.03-100%</td><td>Point estimate</td><td>..</td><td>PROLIFICA (refs 16,17)‡</td><td>See previous row for description of false-positive and false-negative cases</td></tr><tr><td>Start age of cohort (years)</td><td>38</td><td>15-50</td><td>Point estimate</td><td>..</td><td>PROLIFICA</td><td>Screening was offered to all individuals older than 30 years; however, the start age of our modelled cohort was 38 years to correspond with the median age of HBV-positive patients screened in the community</td></tr><tr><td>Discount rate: costs (%)</td><td>3%</td><td>0-6%</td><td>Point estimate</td><td>..</td><td>Refs 18, 19</td><td>..</td></tr><tr><td>Discount rate: health outcomes (%)</td><td>3%</td><td>0-6%</td><td>Point estimate</td><td>..</td><td>Refs 18, 19</td><td>..</td></tr><tr><td colspan="7">Annual disease transition rates§</td></tr><tr><td colspan="7">From immune tolerant to:</td></tr><tr><td>Immune reactive</td><td>0.1</td><td>0.03-0.2</td><td>Beta</td><td>a=5.063; b=45.57</td><td>Refs 20-22</td><td>..</td></tr><tr><td>Hepatocellular carcinoma</td><td>0.003</td><td>0-0.006</td><td>Beta</td><td>a=3.985; b=1324.35</td><td>Assumption</td><td>..</td></tr><tr><td colspan="7">From immune reactive to:</td></tr><tr><td>Inactive carrier</td><td>0.05735</td><td>0.0458-0.06882</td><td>Beta</td><td>a=11.971; b=196.76</td><td>Refs 23,24</td><td>..</td></tr><tr><td>HBeAg-negative chronic HBV</td><td>0.005</td><td>0-0.05</td><td>Beta</td><td>a=0.154; b=30.69</td><td>Assumption</td><td>..</td></tr><tr><td>Compensated cirrhosis</td><td>0.0277</td><td>0.01-0.054</td><td>Beta</td><td>a=6.138; b=215.45</td><td>Refs 25-31</td><td>..</td></tr><tr><td>Hepatocellular carcinoma</td><td>0.0065</td><td>0.0027-0.01</td><td>Beta</td><td>a=12.596; b=1925.30</td><td>Refs 26-28, 32-35</td><td>..</td></tr><tr><td colspan="7">From inactive carrier to:</td></tr><tr><td>HBeAg-negative chronic HBV</td><td>0.0268</td><td>0.0155-0.0471</td><td>Beta</td><td>a=11.173; b=405.74</td><td>Refs 24, 36-41</td><td>..</td></tr><tr><td>Hepatocellular carcinoma</td><td>0.00065</td><td>0-0.001</td><td>Beta</td><td>a=0.057; b=94.89</td><td>Ref 42</td><td>..</td></tr><tr><td>HBsAg negative</td><td>0.01</td><td>0.0097-0.0226</td><td>Beta</td><td>a=17.146; b=1257.65</td><td>Refs 23, 38, 39, 43</td><td>..</td></tr><tr><td colspan="7">From HBeAg-negative chronic HBV to:</td></tr><tr><td>Compensated cirrhosis</td><td>0.04</td><td>0.01-0.052</td><td>Beta</td><td>a=11.173; b=300.92</td><td>Refs 25-31, 37, 43, 44</td><td>..</td></tr><tr><td>Hepatocellular carcinoma</td><td>0.00616</td><td>0.0027-0.01</td><td>Beta</td><td>a=11.300; b=1824.50</td><td>Refs 43</td><td>..</td></tr><tr><td colspan="7">From compensated cirrhosis to:</td></tr><tr><td>Decompensated cirrhosis</td><td>0.039</td><td>0.032-0.046</td><td>Beta</td><td>a=2.848; b=70.18</td><td>Refs 35, 45-47</td><td>..</td></tr><tr><td>Hepatocellular carcinoma</td><td>0.0366</td><td>0.008-0.08</td><td>Beta</td><td>a=3.947; b=103.88</td><td>Refs 20, 28, 32, 35, 46, 48-56</td><td>..</td></tr><tr><td>Death</td><td>0.039</td><td>0.039-0.507</td><td>Beta</td><td>a=0.270; b=6.66</td><td>Ref 57</td><td>..</td></tr><tr><td colspan="7">From decompensated cirrhosis to:</td></tr><tr><td>Hepatocellular carcinoma</td><td>0.0376</td><td>0.023-0.071</td><td>Beta</td><td>a=9.411; b=240.88</td><td>Refs 45, 48-52, 58</td><td>..</td></tr></tbody></table>

(Table 1 continues on next page)
<table><thead><tr><th></th><th>Base-case value</th><th>Deterministic range</th><th>PSA distribution</th><th>PSA parameters</th><th>Source*</th><th>Further description</th></tr></thead><tbody><tr><td>(Continued from previous page)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Death</td><td>0.314</td><td>0.043-0.57</td><td>Beta</td><td>a=3.583; b=7.83</td><td>Ref 57</td><td>..</td></tr><tr><td>From hepatocellular carcinoma to:</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Death</td><td>0.5</td><td>0.4-1</td><td>Beta</td><td>a=5.056; b=5.06</td><td>Ref 57</td><td>..</td></tr><tr><td>Disability weights¶</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Immune tolerant</td><td>0.053</td><td>..</td><td>Beta</td><td>a=20.13; b=359.73</td><td>GBD 2010<sup>59</sup></td><td>Disability weight for "HIV receiving ARV" was used as proxy</td></tr><tr><td>Immune reactive</td><td>0.053</td><td>..</td><td>Beta</td><td>a=20.13; b=359.73</td><td>GBD 2010<sup>59</sup></td><td>Disability weight for "HIV receiving ARV" was used as proxy</td></tr><tr><td>Inactive carrier</td><td>0.053</td><td>..</td><td>Beta</td><td>a=20.13; b=359.73</td><td>GBD 2010<sup>59</sup></td><td>Disability weight for "HIV receiving ARV" was used as proxy</td></tr><tr><td>HBeAg-negative chronic HBV</td><td>0.053</td><td>..</td><td>Beta</td><td>a=20.13; b=359.73</td><td>GBD 2010<sup>59</sup></td><td>Disability weight for "HIV receiving ARV" was used as proxy</td></tr><tr><td>Compensated cirrhosis</td><td>0.127</td><td>..</td><td>Beta</td><td>a=10.02; b=68.90</td><td>GBD 2010<sup>59</sup></td><td>Disability weight for "Decompensated cirrhosis of the liver" was used as proxy (lower CI used)</td></tr><tr><td>Decompensated cirrhosis</td><td>0.194</td><td>..</td><td>Beta</td><td>a=21.67; b=90.05</td><td>GBD 2010<sup>59</sup></td><td>Disability weight for "Decompensated cirrhosis of the liver" was used</td></tr><tr><td>Hepatocellular carcinoma</td><td>0.519</td><td>..</td><td>Beta</td><td>a=18.10; b=16.77</td><td>GBD 2010<sup>59</sup></td><td>Disability weight for "Terminal phase: without medication (for cancers, end-stage kidney or liver disease)" was used</td></tr><tr><td>Treated immune reactive</td><td>0.053</td><td>..</td><td>Beta</td><td>a=20.13; b=359.73</td><td>GBD 2010<sup>59</sup></td><td>Disability weight for "HIV receiving ARV" was used as proxy</td></tr><tr><td>Treated HBeAg-negative chronic HBV</td><td>0.053</td><td>..</td><td>Beta</td><td>a=20.13; b=359.73</td><td>GBD 2010<sup>59</sup></td><td>Disability weight for "HIV receiving ARV" was used as proxy</td></tr><tr><td>Treated compensated cirrhosis</td><td>0.053</td><td>..</td><td>Beta</td><td>a=20.13; b=359.73</td><td>GBD 2010<sup>59</sup></td><td>Assumed returns to same disability weight as untreated chronic HBV stages</td></tr><tr><td>Treated decompensated cirrhosis</td><td>0.127</td><td>..</td><td>Beta</td><td>a=10.02; b=68.90</td><td>GBD 2010<sup>59</sup></td><td>Assumed returns to same disability weight as untreated chronic HBV stages</td></tr></tbody></table>

See appendix for starting state distributions of chronic HBV infection and for health utilities used for quality-adjusted life-year calculations. ARV=antiretroviral. HBeAg=hepatitis B envelope antigen. HBsAg=hepatitis B surface antigen. HBV=hepatitis B virus. POC=point-of-care. PSA=probabilistic sensitivity analysis. PROLIFICA=Prevention of Liver Fibrosis and Cancer in Africa. Ref=reference number. *If more than one reference is given, the final value represents a summary value. †In the gamma distributions, the λ parameter is equal to mean/SD. ‡The references provided represent the sources of the parameter ranges used in the sensitivity analyses. §For transition rates used from the review by Lin and colleagues,⁵⁷ the original articles are individually referenced. ¶The equivalent category in the Global Burden of Disease Study 2010,¹⁰ which was used for the disability weight of each of these health states, is described.

<caption>**Table 1: Main model parameters**</caption>

remained an ongoing risk of developing hepatocellular carcinoma despite antiviral therapy.¹⁴,¹⁵

## Cohort characteristics

Although screening was offered to all individuals living in study areas who were aged 30 years or older, the start age of our modelled cohort was 38 years, corresponding with the median age of HBV-positive patients screened in the community, in an attempt to avoid overestimation of health benefits. We assumed that all individuals offered screening had not been vaccinated against HBV, because the universal infant vaccination programme only began in 1990 in The Gambia.² The starting distribution of the infected cohort across different clinical states was based on PROLIFICA data (appendix). We assumed that natural history and cost parameters were independent of age and sex, but applied an age-structured Gambia-specific mortality rate.⁶²

## Costs

Costs were assessed from a health provider perspective, and were based on the PROLIFICA study budget, public health facility activity data, and interviews with key health personnel regarding time and resource use. Costs consisted of personnel, equipment, materials, and

maintenance. The cost components of the screen and treat intervention included one-off costs for screening of US$7.43 per person offered screening and initial diagnostic assessment cost of $120 per patient. Annual costs were $48 for drugs, $36.88 for monitoring on antiviral therapy, and $15.77 for monitoring if not on antiviral therapy (table 1).

We used data from WHO-CHOICE to estimate costs of hospital admission in The Gambia.⁹ All costs are expressed in 2013 US$. Future costs and health outcomes were discounted at 3% per year, as per WHO guidelines and Gates Reference Case.¹⁸,¹⁹

## Outcome measures

We present three outcome measures to allow for greater comparability with existing literature and to acknowledge that each one has limitations: cost per disability-adjusted life-year (DALY) averted; cost per life-year saved; and cost per quality-adjusted life-year (QALY) gained. When available, we used disability weights from the Global Burden of Disease Study 2010,⁵⁹ and approximated from other diseases if liver-specific weights were not available. Health utilities are not well defined for HBV in low-income and middle-income countries, but we used mean cross-country utilities from a multi-country study by Levy
and colleagues⁶³ for our base-case QALY. Life-years represent an objective measure, but do not take into account morbidity.

## Measurement of cost-effectiveness

We calculated an incremental cost-effectiveness ratio (ICER) between current practice and the screen and treat intervention, which was defined as (cost<sub>screen and treat intervention</sub> - cost<sub>current practice</sub>)/(effectiveness<sub>screen and treat intervention</sub> - effectiveness<sub>current practice</sub>). A new intervention is often deemed cost-effective if the ICER is below a willingness-to-pay (WTP) threshold. However, these thresholds and their use are contested, especially in low-income and middle-income countries where various thresholds have been suggested, including multiples of a country's gross domestic product (GDP) per capita⁶⁴ and a World Bank threshold of $240 per DALY averted.⁶⁵,⁶⁶ We therefore present a range of WTP thresholds to allow the decision maker to put the results of our study into the context of these various thresholds—namely, one times GDP per capita ($487),⁶⁷ three times GDP per capita ($1460), and a more stringent World Bank threshold of $240 per DALY averted.

## Sensitivity analysis

We performed a series of one-way deterministic sensitivity analyses that varied the parameters individually over plausible ranges to test the robustness of our findings and to identify key uncertainties and data collection priorities (table 1). Multiple combinations of health utility values were also explored in the sensitivity analysis (appendix). We did a multivariate probabilistic sensitivity analysis to characterise the overall combined uncertainty of all the model parameters using second order Monte Carlo simulations. Distributions for parameter values were specified by a gamma distribution for costs (range of ±20%) and beta distribution for probabilities (range taken from published literature, or if unavailable ±0·2, constrained between 0 and 1). Uncertainty in the model is presented in a cost-effectiveness acceptability curve.

## Role of the funding source

The funder of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to the data in the study and had final responsibility for the decision to submit for publication.

## Results

The projected total health benefit that a round of screening will impart on this cohort of 8170 people compared with no screening is an additional 498 DALYs averted, 417 life-years gained, or 526 QALYs saved.

The screen and treat intervention has ICERs of $540 per DALY averted, $645 per life-year saved, and $511 per QALY gained, compared with current practice (table 2). The cost per DALY averted compares favourably to a three times GDP per capita threshold in The Gambia.

<table><thead><tr><th rowspan="2"></th><th colspan="4">Average per person</th><th colspan="3">ICER</th></tr><tr><th>Cost (US$)</th><th>Life-years saved</th><th>QALY</th><th>DALY</th><th>US$ per DALY averted</th><th>US$ per QALY gained</th><th>US$ per life-year saved</th></tr></thead><tbody><tr><td>Current practice</td><td>11·15</td><td>19·84</td><td>16·98</td><td>4·28</td><td>..</td><td>..</td><td>..</td></tr><tr><td>Screen and treat intervention</td><td>44·08</td><td>19·89</td><td>17·04</td><td>4·22</td><td>540</td><td>511</td><td>645</td></tr></tbody><tfoot><tr><td colspan="8">DALY=disability-adjusted life-year. ICER=incremental cost-effectiveness ratio. QALY=quality-adjusted life-year.</td></tr></tfoot></table>

<figure><img src="image_5.png" /><figcaption>**Figure 1:** Tornado diagram showing one-way sensitivity analyses of parameters that affect the ICER</figcaption></figure>

The first nine parameters affect the ICER by greater than US$100 over the ranges specified. The bottom three parameters affect the ICER to a lesser extent, but are included because they are important for programmatic implementation. Parameter categories are grouped by colour: purple represents costs, green represents transition rates, and red represents patient behaviours. The values representing the lower and higher ranges over which the parameter was varied are shown in parentheses. The dashed vertical black line represents the base case value. DALY=disability-adjusted life-year. ICER=incremental cost-effectiveness ratio.

<footnote>*Treatment adherence refers to adherence in the first year, when the subsequent yearly drop-out rate was kept constant at 2% per year.</footnote>
and is in line with a one times GDP per capita threshold, implying that the screening and treatment strategy is likely to be cost-effective. However, if the highly conservative World Bank threshold of $240 per DALY averted is used, this strategy is not cost-effective.

One way-sensitivity analyses showed that the ICER remained below three times GDP per capita per DALY averted, irrespective of outcome measure, for most plausible ranges of parameters (figure 1). Here, we discuss the parameters that had most effect on the ICERs, were most uncertain, or are important for programmatic implementation.

Varying HBsAg prevalence to 10%, 5%, 2%, and 1% increased the ICER to $526, $633, $955, and $1492 per DALY averted, respectively, with a sharp increase in the ICER at a prevalence lower than 2% (figure 2). When the age of the cohort screened was increased from 15 to 50 years, the ICER increased from $443 to $824 per DALY averted.

A two-fold or three-fold increase in the cost of community screening per person from the baseline of $7.43 increased the ICER to $662 or $784 per DALY averted, respectively. The generic price of tenofovir available for HIV programmes in The Gambia of $48 per year⁸ was used for the base case, but increasing the drug price to $207, which represents the current pharmaceutical price of tenofovir offered to countries in sub-Saharan Africa,⁶⁸ increased the ICER to $1064 per DALY averted. A reduction in drug cost by half would reduce the ICER to $461 per DALY averted.

Our baseline rate of treatment adherence in the first year was 80.9% (recorded in the PROLIFICA study) and varying this between 77% to 95% (while maintaining a subsequent treatment drop-out rate of 2% per year) changed the ICER by $32, from $515 to $547 per DALY averted. Similarly, when screening uptake was varied over a wide range between 63% and 97%, which is in broad agreement with the ranges seen in the Demographic and Health Surveys of HIV screening in sub-Saharan Africa,¹⁰ the effect on the ICER was only $46. Varying linkage to care (defined here as attendance to first outpatient consultation) between 62% and 95% also had only a small effect on the ICER ($13).

The natural history transition parameter with the greatest effect on the ICER was the rate of progression from HBeAg-negative chronic HBV infection to compensated cirrhosis. Changing this from 0.01 to 0.052 moved the ICER from $458 to $824 per DALY averted. The next most influential transition rates were from inactive carrier to HBeAg-negative chronic HBV infection, compensated cirrhosis to death, and compensated cirrhosis to hepatocellular carcinoma, which affected the ICERs by $183, $130, and $102 per DALY averted, respectively.

The use of different health utilities for QALY calculations gave a range of ICERs from $307 to $627 per QALY gained, the lowest ICER when utilities specific to

China (with a standard gamble technique)⁶³ were used and the highest ICER when utilities from Singapore (with EuroQol-5D technique)⁶⁹ were used (appendix). Sensitivity analysis on the discount rate for costs and health benefits showed an ICER as low as $221 per DALY averted when costs were discounted at 6% and health benefits undiscounted (appendix, Table S4).

The following parameters representing effectiveness of treatment had minimal effect (<$20) on the ICER: varying resistance to treatment between 0.5% to 2% per year after 6 years of treatment initiation, varying failure of reduction in disease progression on antiviral treatment between 0 to 2% per year, and varying the continued annual risk of development of hepatocellular carcinoma for individuals with cirrhosis on antiviral therapy, between 0 to 2% per year for compensated cirrhosis and 0 to 4% per year for decompensated cirrhosis.

For 2000 Monte-Carlo simulations, mean cost was $44.70 (95% CI 44.39–45.00) for the screen and treat intervention and $12.45 (95% CI 12.00–12.91) for current practice. Mean DALYs were 4.215 (95% CI 4.213–4.217) for the screen and treat intervention and 4.27 (95% CI 4.268–4.272) for current practice. Mean ICER was $621 (95% CI 612.8–629.6) per DALY averted (see appendix for ICER scatter plot).

The cost-effectiveness acceptability curve in figure 3 represents the probability that the new intervention will be cost-effective over a range of decision makers' WTP thresholds per additional DALY averted. At a WTP threshold of $1460, there is a 99.7% probability that the screening and treatment strategy will be cost-effective; this probability reduces to 95%, 20%, and <1% if the WTP threshold is $974, $487, or $240, respectively.

<figure><img src="image_6.png" /><figcaption>**Figure 2:** Effect of varying HBsAg prevalence on incremental cost-effectiveness ratio</figcaption></figure>

The boundaries of hepatitis B virus endemicity categories are marked by dashed green lines: low (HBsAg prevalence <2%), low-intermediate (2–5%), high-intermediate (5–8%), and high (>8%). The baseline HBsAg prevalence in The Gambia is represented by a solid grey line. HBsAg=hepatitis B surface antigen. DALY=disability-adjusted life-year.
<figure><img src="image_7.png" /><figcaption>**Figure 3: Cost-effectiveness acceptability curve**</figcaption></figure>

This figure represents the probability that the screen-and-treat intervention will be cost-effective over a range of willingness-to-pay (WTP) thresholds per disability-adjusted life-year (DALY) averted. The dashed lines represent different WTP thresholds that can be applied to The Gambia: US$1460 (represents three times the gross domestic product [GDP] per capita of The Gambia), $974 (represents two times the GDP per capita of The Gambia), $487 (represents one times the GDP per capita of The Gambia), and $240 (World Bank threshold).

The modelled HBV-negative, untreated HBV-positive, and treated HBV-positive cohorts had median survival ages of 70 years, 62 years, and 69 years, respectively. This finding is consistent with the average life expectancy at age 30 years in The Gambia of 68 years,⁶² and the assumption that treatment for chronic HBV infection restores a near normal life expectancy. This concordance adds strength to the validity of the model.

## Discussion

Screening and treatment for HBV in The Gambia, where the adult HBsAg prevalence is 8.8%, has ICERs of $540 per DALY averted, $645 per life-year saved, and $511 per QALY gained, compared with current practice. Whether this intervention represents a cost-effective strategy must be judged in light of the WTP threshold adopted. The screen and treat intervention remains well below the commonly used benchmark WTP threshold of less than three times the country's GDP per capita. However, because the use of this high threshold is increasingly questioned, we are also able to show that the ICERs remain in line with a much more stringent criteria of one times GDP per capita. Uncertainty exists around the chance that such an intervention will be cost-effective at lower WTP thresholds. Low screening costs, highly effective and relatively low cost antiviral therapy at generic price, and only a small proportion of people requiring antiviral therapy help drive the cost-effectiveness of the screening and treatment strategy. However, these factors have to be balanced against lifelong treatment and the

fact that a high proportion of individuals with chronic HBV infection will survive without treatment. Recent trials are showing promising results with finite treatment courses in some patient groups,⁷⁰ and this could help increase cost-effectiveness further.

Existing economic evaluations of HBV interventions in low-income and middle-income countries focus on prevention of HBV infection through vaccination. To our knowledge, our study is the first to assess the cost-effectiveness of active population-level screening and treatment for HBV in a low-income or middle-income setting, using primary data from a large community-based implementation study in The Gambia. Furthermore, our model is unique in incorporating all stages of chronic HBV, thereby taking into account the dynamic natural history of chronic HBV infection and allowing separation into treated and monitored categories, which have differing associated costs and outcomes. Although the paucity of data in sub-Saharan Africa can make accurate cost-effectiveness analyses challenging, sensitivity analyses have shown that the intervention remains cost-effective across a wide range of parameter inputs and WTP thresholds.

The cost of community-based HBV screening falls at the lower end of the broad range of community-based HIV screening costs in sub-Saharan Africa presented in a systematic review by Suthar and colleagues (cost per person tested $2·45–33·54).⁷¹ Despite being perceived as a resource-intensive and labour-intensive strategy, in our study screening costs represented only 3–5% of the overall costs of HBV assessment and annual treatment and monitoring costs. Furthermore, costs are likely to be overestimated in our study because of field teams dedicated entirely to HBV screening as it formed part of a research programme. Integration of HBV screening with testing for other diseases such as hepatitis C virus or HIV could potentially reduce these costs further. Understanding how the quality of the intervention outside trial settings will impact costs and effects will be essential.

Downstream costs of diagnosis, antiviral therapy, and monitoring represent a larger proportion of the total costs than the screening part of the intervention. Generic-price tenofovir ($48) was used for our analysis, but a recent study has shown that entecavir, which is due to come off patent in 2017, can be manufactured for a lower cost of $36,⁷² and could be an alternative cost-effective therapy to tenofovir. If The Gambia had to purchase tenofovir at the current pharmaceutical price of $207 offered to countries in sub-Saharan Africa, this would substantially decrease cost-effectiveness.⁶⁸

Prevalence of chronic HBV infection can be divided into regions of low (<2%), low-intermediate (2–5%), high-intermediate (5–8%), and high (>8%) endemicity.¹ Although The Gambia is classified as a highly endemic country, our analysis shows that community screening and treatment remains below three times GDP per capita per DALY averted, even at an HBV prevalence as low as 1·5%.
This finding has implications for the decision of whether to offer widescale screening in the post-vaccination era, in which the overall prevalence of chronic HBV carriage has begun to decrease,⁷³ and for policy makers considering the potential cost-effectiveness of similar interventions in neighbouring countries with different HBV prevalence patterns.

Although increased uptake of interventions and patient engagement are needed to maximise health gains, in our study, uptake of screening, linkage to care, and adherence to therapy were not big drivers of cost-effectiveness. Our baseline adherence of 80·9%, although higher than the reported adherence of 77% to HIV treatment in sub-Saharan Africa,¹² is lower than the reported adherence of 87·8% to HBV treatment in North America.⁷⁴ Our base-case estimate of 81·3% potentially overestimates linkage to care in routine practice, because it was measured within a research study that provided reimbursement of transportation fees, clinics held in rural sites to facilitate access to treatment, active reminders about appointments, and good sensitisation and counselling of screened participants. However, variations in these parameters had little effect on cost-effectiveness because low rates reduce both the impact, as well as the costs, which scale together. These losses and frailties are similar to what is seen in the HIV care cascade.

Our model is of a static cohort and assumes homogeneity of the population with respect to age and sex, rather than a dynamic transmission model. The model therefore potentially underestimates the impact and cost-effectiveness of treatment, to the extent that treatment can reduce transmission in the population, especially through prevention of mother-to-child transmission by antiviral therapy. However, because only a small proportion of adults in The Gambia are HBeAg-positive, suggesting lower infectivity risk (which is consistent with data from other regions in sub-Saharan Africa), this extra benefit might be limited.⁷⁵

A health provider perspective was used in this study, hence household costs of accessing screening and treatment were excluded. In a setting in which most people die at home, and end-of-life costs are borne by family members acting as caregivers, a societal perspective analysis would likely show a higher cost-effectiveness of the intervention. Furthermore, in The Gambia, where the median age of patients diagnosed with hepatocellular carcinoma is 40 years,⁷⁶ people of working age are often affected; thus, the economic impact is potentially greater to the household and society.

Although care must be taken before generalising the results of this study to other regions in sub-Saharan Africa, the fact that our model results were robust over a wide range of HBV prevalence, transition probabilities, and cost parameters suggests that screening and treatment strategies should be considered in other countries. Direct economic comparison between countries and across disease areas can help put our

results into context, but should be interpreted with caution. Our findings suggest that the cost-effectiveness of a screening and treatment strategy for HBV is comparable to other interventions in The Gambia—for example, the introduction of the pneumococcal vaccine.⁷⁷ A unique feature of HBV screening is that, when combined with vaccination, it only requires once-a-lifetime testing, which contrasts with HIV, where a negative individual still remains at risk of reinfection.

Finally, although the screen and treat intervention was found to lie within cost-effective thresholds, it must be recognised that the WTP threshold is a theoretical one, especially in low-income and middle-income countries, to indicate whether an intervention should be entitled to be set as a priority in the health-care agenda. However, affordability and how the intervention will be funded (whether by governments, out-of-pocket, insurance systems, or external donor funding), in addition to cost-effectiveness, need to be considered before an intervention is adopted on a national level.

Poor access to testing and antiviral treatment remains a major barrier to reducing morbidity and mortality from HBV-related disease in sub-Saharan Africa. Our analysis has shown that community-based screening and treatment for chronic HBV infection is likely to be cost-effective if generic-priced tenofovir is used, which is currently only available for HIV treatment programmes in sub-Saharan Africa. Furthermore, integration of HBV screening with screening for other diseases, using the already established infrastructure for addressing HIV in sub-Saharan Africa, as well as simplifying diagnostic assessment and monitoring, might make this an even more cost-effective intervention. The combination of vaccination, screening, and treatment raises the possibility of advancing the date of elimination of HBV-related morbidity and mortality as a public health threat.⁷⁸

**Contributors**

SN, LC, TBH, and MT designed the study. SN collected the costing data, developed the model, carried out the analysis, and wrote the report. ES and LC assisted with the economic analyses. ML, YS, and RN were responsible for the PROLIFICA clinical trial. HN, PS, and ST helped with collecting costing data. All authors read and approved the final manuscript.

**Declaration of interests**

MT has accepted fees for advisory boards and lectures from AbbVie, BMS, Gilead, Janssen, and Merck. All other authors declare no competing interests.

**Acknowledgments**

We thank the European Commission (FP7) for funding the programme; the Medical Research Council Laboratories, The Gambia Unit, the local ministry of health and social welfare, and the national public health laboratories for supporting the project; the PROLIFICA team; all the study participants; and Debbie Garside, the project manager of PROLIFICA. We acknowledge the support of the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) who jointly fund (under the MRC/DFID Concordat agreement) the clinical research fellowship that supports SN. All authors acknowledge the support of the UK National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at Imperial College London for infrastructure support. We also thank the French Research Agency on HIV/AIDS and viral hepatitis (ANRS) for supporting ML's work within the PROLIFICA project.
References

1 Schweitzer A, Horn J, Mikolajczyk RT, Krause G, Ott JJ. Estimations of worldwide prevalence of chronic hepatitis B virus infection: a systematic review of data published between 1965 and 2013. *Lancet* 2015; **386**: 1546–55.

2 Viviani S, Carrieri P, Bah E, et al. 20 years into the Gambia Hepatitis Intervention Study: assessment of initial hypotheses and prospects for evaluation of protective effectiveness against liver cancer. *Cancer Epidemiol Biomarkers Prev* 2008; **17**: 3216–23.

3 WHO. Guidelines for the prevention, care and treatment of persons with chronic hepatitis B infection. 2015. http://www.who.int/hiv/pub/hepatitis/hepatitis-b-guidelines/en/ (accessed May 23, 2016).

4 WHO. Global policy report on the prevention and control of viral hepatitis in WHO Member States. 2013. http://www.who.int/csr/disease/hepatitis/global_report/en/ (accessed May 23, 2016).

5 Dan YY, Wong JB, Hamid SS, et al. Consensus cost-effectiveness model for treatment of chronic hepatitis B in Asia Pacific countries. *Hepatol Int* 2014; **8**: 382–94.

6 Toy M, Onder FO, Idilman R, et al. The cost-effectiveness of treating chronic hepatitis B patients in a median endemic and middle income country. *Eur J Health Econ* 2012; **13**: 663–76.

7 Hahne S, Veldhuijzen I, Wiessing L, Lim T-A, Salminen M, Laar Mv. Infection with hepatitis B and C virus in Europe: a systematic review of prevalence and cost-effectiveness of screening. *BMC Infect Dis* 2013; **13**: 181.

8 WHO. HIV/AIDS: global price reporting mechanism. http://apps.who.int/hiv/amds/price/hdd/ (accessed Sept 7, 2015).

9 WHO. WHO-CHOICE unit cost estimates for service delivery. 2011. http://www.who.int/choice/cost-effectiveness/inputs/health_service/en/ (accessed April 5, 2015).

10 Cremin I, Cauchemez S, Garnett GP, Gregson S. Patterns of uptake of HIV testing in sub-Saharan Africa in the pre-treatment era. *Trop Med Int Health* 2012; **17**: e26–37.

11 Rosen S, Fox MP, Gill CJ. Patient retention in antiretroviral therapy programs in sub-Saharan Africa: a systematic review. *PLoS Med* 2007; **4**: e298.

12 Mills EJ, Nachega JB, Buchan I, et al. Adherence to antiretroviral therapy in sub-Saharan Africa and North America: a meta-analysis. *JAMA* 2006; **296**: 679–90.

13 Kitrinos KM, Corsa A, Liu Y, et al. No detectable resistance to tenofovir disoproxil fumarate after 6 years of therapy in patients with chronic hepatitis B. *Hepatology* 2014; **59**: 434–42.

14 Rapatodoridis GV, Manolakopoulos S, Touloumi G, et al. Hepatocellular carcinoma risk in HBeAg-negative chronic hepatitis B patients with or without cirrhosis treated with entecavir: HepNet. Greece cohort. *J Viral Hepat* 2015; **22**: 120–27.

15 Wong GL, Chan HL, Mak CW, et al. Entecavir treatment reduces hepatic events and deaths in chronic hepatitis B patients with liver cirrhosis. *Hepatology* 2013; **58**: 1537–47.

16 Njai HF, Shimakawa Y, Sanneh B, et al. Validation of rapid point-of-care (POC) tests for detection of hepatitis B surface antigen in field and laboratory settings in the Gambia, Western Africa. *J Clin Microbiol* 2015; **53**: 1156–63.

17 Shivkumar S, Peeling R, Jafari Y, Joseph L, Pai NP. Rapid point-of-care first-line screening tests for hepatitis B infection: a meta-analysis of diagnostic accuracy (1980–2010). *Am J Gastroenterol* 2012; **107**: 1306–13.

18 WHO. WHO guide to cost-effectiveness analysis. Geneva: World Health Organization, 2003.

19 Bill & Melinda Gates Foundation. Methods for economic evaluation project (MEEP): the Gates reference case. Seattle, WA: Bill & Melinda Gates Foundation, 2014.

20 Fattovich G, Bortolotti F, Donato F. Natural history of chronic hepatitis B: special emphasis on disease progression and prognostic factors. *J Hepatol* 2008; **48**: 335–52.

21 Chang M-H. Natural history of hepatitis B virus infection in children. *J Gastroenterol Hepatol* 2000; **15**: E16–19.

22 Fattovich G BL, Giustina G, Noventa F, et al. Natural history and prognostic factors for chronic hepatitis type B. *Gut* 1991; **32**: 294–98.

23 Chen CJ, Yang HI. Natural history of chronic hepatitis B REVEALED. *J Gastroenterol Hepatol* 2011; **26**: 628–38.

24 Tseng TC, Liu CJ, Chen CL, et al. Serum hepatitis B virus-DNA levels correlate with long-term adverse outcomes in spontaneous hepatitis B e antigen seroconverters. *J Infect Dis* 2012; **205**: 54–63.

25 Liaw YF, Tai DI, Chu CM, Chen TJ. The development of cirrhosis in patients with chronic type B hepatitis: a prospective study. *Hepatology* 1988; **8**: 493–96.

26 Ikeda K, Saitoh S, Suzuki Y, et al. Disease progression and hepatocellular carcinogenesis in patients with chronic viral hepatitis: a prospective observation of 2215 patients. *J Hepatol* 1998; **28**: 930–38.

27 Wu G, Zhou W, Zhao Y, et al. Study on the natural history of chronic hepatitis B. *Zhonghua Gan Zang Bing Za Zhi* 2002; **10**: 46–48 (in Chinese).

28 Lo KJ, Tong MJ, Chien MC, et al. The natural course of hepatitis B surface antigen-positive chronic active hepatitis in Taiwan. *J Infect Dis* 1982; **146**: 205–10.

29 Lin HH, Liaw YF, Chen TJ, Chu CM, Huang MJ. Natural course of patients with chronic type B hepatitis following acute hepatitis delta virus superinfection. *Liver* 1989; **9**: 129–34.

30 Huo T, Wu JC, Hwang SJ, et al. Factors predictive of liver cirrhosis in patients with chronic hepatitis B: a multivariate analysis in a longitudinal study. *Eur J Gastroenterol Hepatol* 2000; **12**: 687–93.

31 Chen TJ, Liaw YF. The prognostic significance of bridging hepatic necrosis in chronic type B hepatitis: a histopathologic study. *Liver* 1988; **8**: 10–16.

32 Beasley RP, Hwang LY, Lin CC, Chien CS. Hepatocellular carcinoma and hepatitis B virus. A prospective study of 22707 men in Taiwan. *Lancet* 1981; **318**: 1129–33.

33 Beasley RP. Hepatitis B virus. The major etiology of hepatocellular carcinoma. *Cancer* 1988; **61**: 1942–56.

34 Liaw YF, Tai DI, Chu CM, et al. Early detection of hepatocellular carcinoma in patients with chronic type B hepatitis. A prospective study. *Gastroenterology* 1986; **90**: 263–67.

35 Xu B, Hu D-C, Rosenberg DM, et al. Chronic hepatitis B: a long-term retrospective cohort study of disease progression in Shanghai, China. *J Gastroenterol Hepatol* 2003; **18**: 1345–52.

36 Chu CM, Liaw YF. Incidence and risk factors of progression to cirrhosis in inactive carriers of hepatitis B virus. *Am J Gastroenterol* 2009; **104**: 1693–99.

37 Chu CM, Hung SJ, Lin J, Tai DI, Liaw YF. Natural history of hepatitis B e antigen to antibody seroconversion in patients with normal serum aminotransferase levels. *Am J Med* 2004; **116**: 829–34.

38 Chu CM, Liaw YF. HBsAg seroclearance in asymptomatic carriers of high endemic areas: appreciably high rates during a long-term follow-up. *Hepatology* 2007; **45**: 1187–92.

39 Gigi E, Lalla T, Orphanou E, Sinakos E, Vrettou E, Raptopoulou-Gigi M. Long term follow-up of a large cohort of inactive HBsAg (+)/ HBeAg (-)/ anti-HBe (+) carriers in Greece. *J Gastrointestin Liver Dis* 2007; **16**: 19–22.

40 Chu CM, Liaw YF. Genotype C hepatitis B virus infection is associated with a higher risk of reactivation of hepatitis B and progression to cirrhosis than genotype B: a longitudinal study of hepatitis B e antigen-positive patients with normal aminotransferase levels at baseline. *J Hepatol* 2005; **43**: 411–17.

41 Papatodoridis GV, Chrysanthos N, Hadziyannis E, Cholongitas E, Manesis EK. Longitudinal changes in serum HBV DNA levels and predictors of progression during the natural course of HBeAg-negative chronic hepatitis B virus infection. *J Viral Hepat* 2008; **15**: 434–41.

42 Chen JD, Yang HI, Iloeje UH, et al. Carriers of inactive hepatitis B virus are still at risk for hepatocellular carcinoma and liver-related death. *Gastroenterology* 2010; **138**: 1747–54.

43 Zacharakis GH, Koskinas J, Kotsiou S, et al. Natural history of chronic HBV infection: a cohort study with up to 12 years follow-up in North Greece (part of the Interreg I-II/EC-project). *J Med Virol* 2005; **77**: 173–79.

44 Hsu YS, Chien RN, Yeh CT, et al. Long-term outcome after spontaneous HBeAg seroconversion in patients with chronic hepatitis B. *Hepatology* 2002; **35**: 1522–27.

45 Fattovich G, Pantalena M, Zagni I, Realdi G, Schalm SW, Christensen E. Effect of hepatitis B and C virus infections on the natural history of compensated cirrhosis: a cohort study of 297 patients. *Am J Gastroenterol* 2002; **97**: 2886–95.

46 Liaw YF, Lin DY, Chen TJ, Chu CM. Natural course after the development of cirrhosis in patients with chronic type B hepatitis: a prospective study. *Liver* 1989; **9**: 235–41.

47 Liaw Y-F, Sung J, Chow W, et al. Lamivudine for patients with chronic hepatitis B and advanced liver disease. *N Engl J Med* 2004; **351**: 1521–31.
48 Tong MJ, Hsien C, Song JJ, et al. Factors associated with progression to hepatocellular carcinoma and to death from liver complications in patients with HBsAg-positive cirrhosis. *Dig Dis Sci* 2009; **54**: 1337-46.

49 Tong MJ, Hsien C, Hsu L, Sun HE, Blatt LM. Treatment recommendations for chronic hepatitis B: an evaluation of current guidelines based on a natural history study in the United States. *Hepatology* 2008; **48**: 1070-78.

50 Chen YC, Chu CM, Yeh CT, Liaw YF. Natural course following the onset of cirrhosis in patients with chronic hepatitis B: a long-term follow-up study. *Hepatol Int* 2007; **1**: 267-73.

51 Kobayashi M, Ikeda K, Hosaka T, et al. Natural history of compensated cirrhosis in the Child-Pugh class A compared between 490 patients with hepatitis C and 167 with B virus infections. *J Med Virol* 2006; **78**: 459-65.

52 Mahmood S, Niiyama G, Kamei A, et al. Influence of viral load and genotype in the progression of hepatitis B-associated liver cirrhosis to hepatocellular carcinoma. *Liver Int* 2005; **25**: 220-25.

53 Tsai JF, Jeng JE, Ho MS, et al. Effect of hepatitis C and B virus infection on risk of hepatocellular carcinoma: a prospective study. *Br J Cancer* 1997; **76**: 968-74.

54 Chen D-S. Hepatitis B and C virus infections in hepatocellular carcinoma and their prevention. In: Nishioka K, Suzuki H, Mishiro S, Oda T, eds. Viral hepatitis and liver disease: Springer Japan, 1994: 685-89.

55 Ikeda K, Saitoh S, Koida I, et al. A multivariate analysis of risk factors for hepatocellular carcinogenesis: a prospective observation of 795 patients with viral and alcoholic cirrhosis. *Hepatology* 1993; **18**: 47-53.

56 Obata H, Hayashi N, Motoike Y, et al. A prospective study on the development of hepatocellular carcinoma from liver cirrhosis with persistent hepatitis B virus infection. *Int J Cancer* 1980; **25**: 741-47.

57 Lin X, Robinson NJ, Thursz M, et al. Chronic hepatitis B virus infection in the Asia-Pacific region and Africa: review of disease progression. *J Gastroenterol Hepatol* 2005; **20**: 833-43.

58 Hui AY. Survival and prognostic indicators in patients with hepatitis B virus-related cirrhosis after onset of hepatic decompensation. *J Clin Gastroenterol* 2002; **34**: 569-72.

59 Salomon JA, Vos T, Hogan DR, et al. Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010. *Lancet* 2012; **380**: 2129-43.

60 European Association For The Study Of The Liver. EASL Clinical Practice Guidelines: management of chronic hepatitis B. *J Hepatol* 2009; **50**: 227-42.

61 Lemoine M, Shimakawa Y, Njie R, et al. Screen and treat as an intervention programme for 1 hepatitis B virus infection in sub-Saharan Africa: the PROLIFICA experience in The Gambia. *Lancet Glob Health* 2016; **4**: e559-67.

62 United Nations, Department of Economic and Social Affairs, Population Division. World population prospects: the 2012 Revision, DVD Edition. http://esa.un.org/unpd/wpp/ (accessed Dec 5, 2014).

63 Levy AR, Kowdley KV, Iloeje U, et al. The impact of chronic hepatitis B on quality of life: a multinational study of utilities from infected and uninfected persons. *Value Health* 2008; **11**: 527-38.

64 WHO. Cost effectiveness and strategic planning: choosing interventions that are cost-effective. 2014. http://www.who.int/choice/en/ (accessed May 23, 2016).

65 Shillcutt SD, Walker DG, Goodman CA, Mills AJ. Cost effectiveness in low- and middle-income countries: a review of the debates surrounding decision rules. *Pharmacoeconomics* 2009; **27**: 903-17.

66 Marseille E, Larson B, Kazi DS, Kahn JG, Rosen S. Thresholds for the cost-effectiveness of interventions: alternative approaches. *Bull World Health Organ* 2015; **93**: 118-24.

67 UN data USD. Gambia: country profile. 2014. http://data.un.org/CountryProfile.aspx?crName=gambia (accessed Oct 8, 2014).

68 MSF Access Campaign. Untangling the web of antiretroviral price reductions: 17th Edition. 2014. http://www.msfaccess.org/content/untangling-web-antiretroviral-price-reductions-17th-edition-%E2%80%963-july-2014 (accessed May 23, 2016).

69 Ong SC, Mak B, Aung MO, Li SC, Lim SG. Health-related quality of life in chronic hepatitis B patients. *Hepatology* 2008; **47**: 1108-17.

70 Berg T, Simon KG, Mauss S, et al. O119: Stopping tenofovir disoproxil fumarate (TDF) treatment after long term virologic suppression in HBeAg-negative CHB: week 48 interim results from an ongoing randomized, controlled trial ("finite CHB"). *J Hepatol* 2015; **62** (suppl 2): S253.

71 Suthar AB, Ford N, Bachanas PJ, et al. Towards universal voluntary HIV testing and counselling: a systematic review and meta-analysis of community-based approaches. *PLoS Med* 2013; **10**: e1001496.

72 Hill A, Gotham D, Cooke G, et al. Analysis of minimum target prices for production of entecavir to treat hepatitis B in high- and low-income countries. *J Virus Erad* 2015; **1**: 103-10.

73 Whittle H, Jaffar S, Wansbrough M, et al. Observational study of vaccine efficacy 14 years after trial of hepatitis B vaccination in Gambian children. *BMJ* 2002; **325**: 569.

74 Chotiyaputta W, Hongthanakorn C, Oberhelman K, Fontana RJ, Licari T, Lok AS. Adherence to nucleos(t)ide analogues for chronic hepatitis B in clinical practice and correlation with virological breakthroughs. *J Viral Hepat* 2012; **19**: 205-12.

75 Shimakawa Y, Lemoine M, Njai HF, et al. Natural history of chronic HBV infection in West Africa: a longitudinal population-based study from The Gambia. *Gut* 2015; published online July 16. DOI:10.1136/gutjnl-2015-309892.

76 Shimakawa Y, Lemoine M, Bottomley C, et al. Birth order and risk of hepatocellular carcinoma in chronic carriers of hepatitis B virus: a case-control study in The Gambia. *Liver Int* 2015; **35**: 2318-26.

77 Kim S-Y, Lee G, Goldie S. Economic evaluation of pneumococcal conjugate vaccination in The Gambia. *BMC Infect Dis* 2010; **10**: 260.

78 Nayagam S, Thursz M, Sicuri E, et al. Requirements for the global elimination of hepatitis B: a modelling study. *Lancet Infect Dis* (in press).