HBV vaccination and PMTCT as elimination tools in the presence of HIV: Insights from a clinical cohort and dynamic model

Background: Sustainable Development Goals set a challenge for the elimination of hepatitis B virus (HBV) infection as a public health concern by the year 2030. Deployment of a robust prophylactic vaccine and enhanced interventions for prevention of mother to child transmission (PMTCT) are cornerstones of elimination strategy. However, in light of the estimated global burden of 290 million cases, enhanced efforts are required to underpin optimisation of public health strategy. Robust analysis of population epidemiology is particularly crucial for populations in Africa made vulnerable by HIV co-infection, poverty, stigma and poor access to prevention, diagnosis and treatment. Methods: We here set out to evaluate the current and future role of HBV vaccination and PMTCT as tools for elimination. We first investigated the current impact of paediatric vaccination in a cohort of children with and without HIV infection in Kimberley, South Africa. Second, we used these data to inform a new parsimonious model to simulate the ongoing impact of preventive interventions. By applying these two approaches in parallel, we are able to determine both the current impact of interventions, and the future projected outcome of ongoing preventive strategies over time. Results: Existing efforts have been successful in reducing paediatric prevalence of HBV infection in this setting to < 1%, demonstrating the success of the existing vaccine campaign. Our model predicts that, if consistently deployed, combination efforts of vaccination and PMTCT can significantly reduce population prevalence (HBsAg) by 2030, such that a major public health impact is possible even without achieving elimination. However, the prevalence of HBV e-antigen (HBeAg)-positive carriers will decline more slowly, representing a persistent population reservoir. We show that HIV co-infection significantly reduces titres of vaccine-mediated antibody, but has a relatively minor role in influencing the projected time to elimination. Our model can also be applied to other settings in order to predict impact and time to elimination based on specific interventions. Conclusions: Through extensive deployment of preventive strategies for HBV, significant positive public health impact is possible, although time to HBV elimination as a public health concern is likely to be substantially longer than that proposed by current goals. Ethics approval was obtained from the Ethics Committee of the Faculty of Health Science, University of the Free State, Bloemfontein, South Africa (HIV Study Ref: ETOVS Nr 08/09 and COSAC Study Ref: ECUFS NR 80/2014), and from the Oxfordshire Research Ethics Committee A, ref 06/Q1604/12. Written consent for enrollment into the study was obtained from the child’s parent/guardian. Recruitment was undertaken in Kimberley, South Africa. In this setting, a standard three-dose HBV immunisation schedule is deployed in infants, with the first dose at 6 weeks. A previous study of HBV serology in adults in the same setting found HBsAg prevalence of 9.5% (55/579) [6]. Children were recruited as part of the Co-infection in South-African Children (‘COSAC’) study as previously described [20, 21]. The lower age limit of recruitment was 6 months in order to limit the detection of maternal anti-HBs. Children were recruited as follows: At the time of undertaking this study, children were immunised with three doses of a monovalent HBV vaccine (Biovac Paed). Where possible, we recorded the number of HBV vaccine doses received based on the Road to Health Book (RTHB). The characteristics of the cohorts are summarised in Table 1 and all metadata can be found in Additional file 1. Characteristics of three paediatric study cohorts, comprising 402 children, recruited from Kimberley Hospital, South Africa KReC Kimberley Respiratory Cohort, IQR interquartile range Testing for hepatitis B serum markers and DNA was performed as previously described, and in keeping with recent implementation of HBV screening in Kimberley [21]. Briefly, HBsAg testing was carried out in Kimberley Hospital, South Africa, using the magnetic parcel chemiluminometric immunoassay (MPCI; Advia Centaur platform). Confirmatory HBsAg testing was carried out by the clinical microbiology laboratory at Oxford University Hospitals (OUH) NHS Foundation Trust, Oxford, UK (Architect i2000). For all samples, anti-HBs and anti-HBc testing were carried out by the OUH laboratory (Architect i2000). Limit of detection of the anti-HBs assay was 10 mIU/ml. Studies variably quote anti-HBs titres of ≥ 10 mIU/ml or ≥ 100 mIU/ml as a correlate of protection; UK recommendations for testing HBV immunity advocate the more stringent criterion of an anti-HBs titre of ≥ 100 mIU/ml [12], while early vaccine studies suggest a titre of ≥ 10 mIU/ml as a clinically relevant threshold for protection [13, 22]. We have presented our results pertaining to both thresholds. Data from the cohort was analysed using GraphPad Prism v.7.0. We determined significant differences between sub-sets within the cohort using Mann-Whitney U tests for non-parametric data, Fisher’s exact test for categorical variables and Spearman’s correlation coefficient for correlation between data points. Here, we summarise the modelling framework, but include a detailed description of the ODE system, model parameters, and Bayesian data fitting approach in Additional file 2. We developed a dynamic model based on ordinary differential equations (ODE), for which parameterisation of HBV transmission and prevention was based both on our Kimberley paediatric cohort and current literature estimates. In summary, the model takes into consideration the proportion of the population susceptible to HBV infection (S), those with chronic infection (C) and acute infection (I), those who are immune as a result of recovery from prior infection (R) and those who are immune as a result of vaccination (V) (Fig. 1). For simplicity, and assuming vaccination takes place early in life, all individuals are assumed to be born either susceptible (Z) or vaccinated (Z’). Chronic carriers (C) are divided into HBeAg-positive (C+) and HBeAg-negative (C−) to further allow for different parameterisation (e.g. transmission potential) between these two epidemiologically distinct states. To be able to parameterise epidemiological traits by age, (e.g. probability of chronicity, or decay of vaccine-induced protection) susceptible (S) and vaccinated (V) individuals are divided into three subgroups representing infants (i, < 1 years of age), children (c, 1–6 years of age) and older individuals (whom we abbreviate to ‘adults’, a, but comprise children age > 6 years, adolescents and adults). The probability of developing chronicity decreases with age, with (1 − ψ) for infants, (1 − ε) for children and (1 − γ) for older individuals. Vertical transmission takes place from mothers with chronic infection and is dependent on their HBeAg serostatus (not shown on diagram). HBeAg-positive chronic carriers (C+) may become HBeAg-negative at a rate θ. HBeAg-negative chronic carriers (C−) can clear infection spontaneously at a rate ρ, entering the anti-HBc-positive, HBsAg-negative state (R). Acute infections (I) are cleared at a rate σ, also entering the recovered class (R). Diagram of HBV dynamic model. To allow for specific parameterisation of important epidemiological states, the population was divided into susceptible (Sx) and vaccinated (Vx) classified into three age-groups representing infants (x = i, < 1 years of age), children (x = c, 1–6 years of age) and older (x = a, > 6 years of age). Individuals acquire infection at any age, moving with different probabilities (Ψ, ε, γ, with Ψ < ε < γ) into acute (I) or chronic (C) infection. When chronically infected, individuals transit between HBeAg-positive (C+) and HBeAg-negative (C−) with rate θ and may clear infection (R) with a small rate ρ. Vaccine-induced protection is age dependent (Δi) and assumed to lower susceptibility to infection (λ). Interventions (in blue) include routine vaccination at birth (Z’) and other ages (ωa, ωc), as well as PMTCT at birth (influencing Z, Z’) and catch-up events (not shown). Model is used to fit prevalence rates as observed: HBV prevalence (I + C− + C+), anti-HBc+ (R) and relative prevalence of HBeAg+ (C+) and HBeAg-negative (C−) individuals. For a complete description on state transitions, vaccination, force of infection, parameters and model equations, please refer to Additional file 2; Bayesian parameter estimations obtained when fitting the model are presented in Additional file 2: Figure S1 Vaccinated individuals (Vi, Vc, Va) are under the same HBV acute and chronic infection rules as susceptible individuals (Si, Sc, Sa), but are further assumed to have vaccine-induced age-dependent protection against infection (Δi, Δc, Δa). For simplicity, we assume that vaccine-induced protection was equivalent to reducing susceptibility to infection potential (λ), e.g. Δi = 1 would be 100% reduction in susceptibility, or 100% vaccine efficacy against infection. Interventions include routine vaccination at birth (affecting Z’) and other ages (affecting ωa, ωc), as well as PMTCT at birth (affecting Z, Z’) and catch-up events (not shown in diagram). We used a Bayesian Markov-chain Monte Carlo (bMCMC) approach to fit the dynamic model to the local demographic and epidemiological setting of Kimberley before projecting the impact of interventions (Additional file 2: Figure S1). The bMCMC used informative priors for ODE model parameters for which robust literature support exists. Two parameters (ρ, θ) were left with uninformed priors (uniform, from 0 to 1), for which we later checked if the fitted bMCMC solution recovered posteriors of these parameters compatible with current literature knowledge (as partial validation of the fitted solution). Informed by the clinical cohort data described above, natural decay (age-effects) and the effects of HIV sero-status on vaccine-induced protection (Δi, Δc, Δa) are taken into account (Additional file 2: Figure S2). SDGs for the year 2030 have been set out in the WHO Global Health Sector Strategy on Viral Hepatitis (GHSSVH) [2]. Given the public health relevance of chronic infections, in particular of HBeAg-positive infections, we measured impact of interventions based on two targets: