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

Abstract

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 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 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.

Fundamental principles of epidemic spread highlight the immediate need for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic

“…Model output on cumulative death counts ( ) is fitted to the reported time series of deaths Λ (see Data) using a Bayesian MCMC approach previously implemented in other modelling studies [7][8][9][10] . Model variables are summarized in probability of dying with severe disease θ Gaussian distribution G(M=0.14, SD=0.007) [1,2,11,17] proportion of population at risk of severe disease ρ Gamma distribution G1(S=5, R=5/0.01), G2(S=5, R=5/0.001) --population size N UK 66.87M, Italy 60M ---…”

Determinants of high residual post-PCV13 pneumococcal vaccine type carriage in Blantyre, Malawi: a modelling study

“…A deterministic, ordinary-differential equations (ODE) model ( Figure 1a) was developed to fit VT carriage levels as reported in the cross-sectional observational study in Blantyre (Figure 1d) 22 . Fitting was implemented using a Bayesian Markov chain Monte Carlo (bMCMC) approach developed and used by us in other modelling studies [37][38][39] , including informative priors for duration of carriage ( Figure 1b, Table S1) and uninformative uniform priors for vaccine efficacy (individuallevel protection against carriage) and transmission potential. The methodology is summarised in this section and further details such as equations, literature review on priors and expected parameter values (Tables S1, S2, S5, S6) and complementary results can be found in Supplementary Text S1.…”

Data from an electronic health informatics pipeline to describe clearance dynamics of Hepatitis B surface antigen (HBsAg) and e-Antigen (HBeAg) in chronic HBV infection

“…To our knowledge this is one of the only studies of this kind in such a population. We report ≥2 HBsAg timepoints for each individual, providing long periods of clinical follow-up and the opportunity to track uncommon clearance events over time; Unlike some previous studies of HBsAg clearance that introduce bias through a focus on treatment or based on patient recall for follow-up, the approach we took is agnostic to other parameters, thereby providing a more inclusive picture of all individuals with CHB infection; In addition to reporting longitudinal data for HBsAg loss, we also track HBeAg loss over time. HBeAg loss is an important immunological event (34) signifying control (typically in association with a fall of HBV DNA levels), and may also be an important target for interventions at a population level (35). …”