Data will be analyzed using Stata software (Stata Corp V.13, Texas, USA). Unadjusted prevalence and standard errors will be recalculated based on the information of crude numerators and denominators provided by individual studies. To keep the effect of studies with extremely small or extremely large prevalence estimates on the overall estimate to a minimum, the variance of the study-specific prevalence will be stabilized with the Freeman-Tukey single arc-sine transformation before pooling the data with the random-effects meta-analysis model [
10]. Heterogeneity will be evaluated by the chi-squared test on Cochrane’s Q statistic [
11], which will be quantified by
I-squared values, assuming that
I-squared values of 25%, 50%, and 75% being representative of low, medium and high heterogeneity respectively [
12]. When substantial heterogeneity will be detected, subgroup analysis and meta-regression will be performed to investigate the possible sources of heterogeneity using the following variables: age, sex, study design, sampling method, data collection period, timing of data collection, diagnostic method for HBV, study setting, WHO region, level of income, ART regimens, and study methodological quality. Symmetry of funnel plots and Egger’s test will be done to assess the presence of publication and selective reporting bias [
13]. A
p value < 0.10 will be considered indicative of statistically significant publication bias. In the case of publication bias, we will report estimates after adjustment on publication bias using the trim-and-fill method [
14]. We will assess inter-rater agreement between investigators for study inclusion, data extraction, and methodological quality assessment using Kappa Cohen’s coefficient [
15].