Introduction
Chronic hepatitis B (CHB) is a major global health challenge and a leading cause of liver-related mortality. Despite effective vaccines and therapies, HBV infection causes significant liver cirrhosis and hepatocellular carcinoma (HCC).1–3 In 2022, an estimated 257.5 million people were living with CHB globally. This resulted in approximately 0.5–0.8 million annual deaths.4–6 CHB also imposes a heavy economic burden because of the high treatment costs associated with advanced liver disease and productivity losses from premature mortality.7–9 Reducing this burden is critical for public health and economic development.
The Asia-Pacific region is the global epicenter of the HBV epidemic.10–12 Historically driven by mother-to-child transmission, this region contains the world’s largest reservoir of chronic HBV infections.13,14 Although universal infant vaccination has significantly reduced prevalence among younger generations, a major challenge remains: the large population of adults infected prior to the vaccination era.4,15 As this “aging cohort” advances in age, its risk of developing decompensated cirrhosis and HCC increases.5,16 Consequently, the region continues to face a substantial burden of advanced liver disease that requires sustained healthcare resources.11,12,17
To guide progress toward elimination, the World Health Organization (WHO) Global Health Sector Strategy set 2030 targets for viral hepatitis, including a 90% reduction in new chronic HBV infections and a 65% reduction in HBV-related mortality from the 2015 baseline.18 In 2022, the WHO further clarified its phased goals by aiming to reduce the prevalence of HBsAg in children under five years of age to 0.1% by 2030.19 Although vaccination has successfully curbed incidence, the mortality target remains unattainable because of persistent gaps in the care cascade, particularly suboptimal diagnosis and treatment rates among eligible adults in high-burden countries.20,21 Current surveillance data are also essential for guiding policy, and the Global Burden of Disease (GBD) Study 2023 provides the most rigorous assessment of health trends using updated methodologies and demographic data.3,22 Therefore, using the GBD 2023 framework, this study aimed to quantify the current CHB burden in 2023, assess temporal trends from 1990 to 2023, identify demographic and epidemiological drivers of burden changes, and project the burden through 2030. By comparing global, regional, subregional, and key-country patterns, we sought to clarify the major gaps in achieving the WHO 2030 targets and identify priorities for CHB elimination in the Asia-Pacific region.
Methods
Data sources
Detailed GBD methodology has been described elsewhere.3,22 The GBD 2023 study provides annual estimates of disease burden from 1990 to 2023 by age, sex, location, and year, covering 204 countries and territories, 375 diseases and injuries, and 88 risk factors. It was built on previous iterations by incorporating over 35,000 new data sources, including vital registration, surveillance systems, surveys, disease registries, hospital records, and published literature, and by applying advanced modeling tools, specifically DisMod-AT and refined MR-BRT, to generate point estimates and 95% uncertainty intervals (UIs) and improve the accuracy of CHB estimates. These updates improve the capture of outpatient and readmission-adjusted hospital data. All data utilized in this study were obtained from the Global Health Data Exchange (https://vizhub.healthdata.org/gbd-results/ ).
GBD estimation framework
We defined CHB as chronic HBV infection, including cases with and without cirrhosis, and extracted annual estimates (1990–2023) for prevalence, mortality, and disability-adjusted life years (DALYs) by age (5-year intervals) and geography (67 Asia-Pacific countries; Supplementary Table 1). Historical population data were obtained from the GBD database, and 2024–2030 projections were obtained from the United Nations World Population Prospects.23 Consistent with established epidemiology, prevalence in children under five years served as a proxy for the incidence of new infections.24,25
Table 1Main CHB Burden in Asia-Pacific Region, 2023
| Location | Prevalence, All ages
| Prevalence, Age under 5
| Deaths, All ages
| DALYs, All ages
|
|---|
| Number, thousand (95% UI) | Rate, per 100,000 (95% UI) | Number, thousand (95% UI) | Rate, per 100,000 (95% UI) | Number, thousand (95% UI) | Rate, per 100,000 (95% UI) | Number, thousand (95% UI) | Rate, per 100,000 (95% UI) |
|---|
| Global | 281,929.51 | 3,495.36 | 8,522.35 | 1,325.32 | 394.20 | 4.89 | 13,074.46 | 162.10 |
| (259,575.69–307,130.36) | (3,218.22–3,807.80) | (6,619.27–10,124.71) | (1,029.37–1,574.51) | (324.62–464.54) | (4.02–5.76) | (10,822.92–15,349.73) | (134.18–190.31) |
| Asia-Pacific Region | 177,975.44 | 3,705.32 | 1,964.38 | 590.33 | 259.07 | 5.39 | 8,441.73 | 175.75 |
| (168,260.21–188,809.00) | (3,503.06–3,930.87) | (1,853.91–2,110.86) | (557.14–634.35) | (237.86–286.01) | (4.95–5.95) | (7,750.42–9,391.33) | (161.36–195.52) |
| East Asia | 99,242.62 | 5,978.09 | 475.95 | 677.07 | 104.03 | 6.27 | 2,988.38 | 180.01 |
| (89,681.39–108,380.36) | (5,402.15–6,528.52) | (417.85–537.70) | (594.42–764.92) | (88.65–121.29) | (5.34–7.31) | (2,560.15–3,503.97) | (154.22–211.07) |
| China | 91,190.03 | 6,374.05 | 358.65 | 576.95 | 90.88 | 6.35 | 2,630.08 | 183.84 |
| (81,716.34–100,342.69) | (5,711.85–7,013.81) | (305.07–412.58) | (490.76–663.71) | (76.28–108.63) | (5.33–7.59) | (2,230.14–3,113.54) | (155.88–217.63) |
| Japan | 2,883.35 | 2,312.74 | 1.64 | 39.66 | 4.04 | 3.24 | 88.88 | 71.29 |
| (2,657.31–3,178.76) | (2,131.43–2,549.68) | (1.35–1.99) | (32.77–48.05) | (3.36–4.75) | (2.69–3.81) | (76.23–102.97) | (61.14–82.59) |
| Democratic People’s Republic of Korea | 2,202.65 | 8,340.03 | 107.67 | 7,226.16 | 2.41 | 9.12 | 78.03 | 295.44 |
| (1,898.68–2,497.71) | (7,189.09–9,457.21) | (83.19–132.74) | (5,583.07–8,908.88) | (1.43–3.53) | (5.40–13.35) | (48.31–113.14) | (182.92–428.41) |
| South Asia | 40,460.95 | 2,072.32 | 714.10 | 426.10 | 76.18 | 3.90 | 2,763.57 | 141.54 |
| (37,580.92–43,611.26) | (1,924.82–2,233.68) | (632.86–823.44) | (377.62–491.34) | (62.95–92.95) | (3.22–4.76) | (2,249.75–3,422.93) | (115.23–175.32) |
| India | 30,611.16 | 2,120.79 | 425.71 | 386.89 | 56.95 | 3.95 | 2,035.15 | 141.00 |
| (27,931.04–33,678.65) | (1,935.11–2,333.31) | (338.15–507.38) | (307.31–461.11) | (43.28–71.12) | (3.00–4.93) | (1,521.29–2,533.96) | (105.40–175.56) |
| Pakistan | 5,450.61 | 2,234.31 | 222.73 | 722.49 | 10.65 | 4.37 | 420.13 | 172.22 |
| (4,870.40–6,038.13) | (1,996.47–2,475.14) | (184.72–259.76) | (599.18–842.62) | (5.96–14.53) | (2.44–5.96) | (238.98–579.83) | (97.96–237.68) |
| Bangladesh | 3,184.52 | 1,831.68 | 24.00 | 148.37 | 4.14 | 2.38 | 158.86 | 91.37 |
| (2,823.00–3,603.79) | (1,623.75–2,072.84) | (14.85–33.39) | (91.82–206.41) | (2.58–7.41) | (1.48–4.26) | (99.98–274.47) | (57.51–157.87) |
| Southeast Asia | 27,978.58 | 4,026.67 | 471.99 | 890.08 | 61.19 | 8.81 | 2,169.63 | 312.25 |
| (26,908.14–29,134.87) | (3,872.61–4,193.08) | (435.96–515.75) | (822.15–972.61) | (52.85–72.30) | (7.61–10.41) | (1,867.31–2,573.16) | (268.74–370.33) |
| Indonesia | 10,002.01 | 3,479.36 | 185.27 | 849.67 | 28.40 | 9.88 | 1,014.52 | 352.92 |
| (9,169.43–10,866.33) | (3,189.73–3,780.03) | (155.32–213.85) | (712.34–980.77) | (21.26–36.67) | (7.39–12.76) | (754.59–1,305.99) | (262.50–454.31) |
| Vietnam | 6,786.26 | 6,578.80 | 53.09 | 676.28 | 8.86 | 8.59 | 290.52 | 281.64 |
| (6,380.32–7,215.54) | (6,185.27–6,994.96) | (43.03–64.59) | (548.08–822.70) | (5.99–13.01) | (5.81–12.61) | (189.21–435.81) | (183.43–422.49) |
| Philippines | 6,492.70 | 5,669.91 | 150.78 | 1,497.89 | 5.42 | 4.73 | 188.34 | 164.47 |
| (5,948.52–7,142.47) | (5,194.69–6,237.34) | (127.52–174.11) | (1,266.74–1,729.63) | (4.33–6.75) | (3.78–5.89) | (150.06–231.90) | (131.04–202.51) |
| Western Asia | 6,649.40 | 1,795.44 | 157.73 | 541.55 | 12.05 | 3.25 | 324.87 | 87.72 |
| (6,445.48–6,859.22) | (1,740.38–1,852.09) | (137.71–186.05) | (472.80–638.79) | (10.53–14.29) | (2.84–3.86) | (291.68–378.48) | (78.76–102.19) |
| Turkey | 1,761.91 | 2,051.94 | 25.07 | 462.72 | 4.40 | 5.13 | 102.80 | 119.73 |
| (1,670.34–1,846.78) | (1,945.29–2,150.78) | (19.91–30.44) | (367.38–561.75) | (3.15–5.81) | (3.67–6.77) | (78.02–132.05) | (90.87–153.79) |
| Yemen | 1,635.29 | 4,599.95 | 97.33 | 1,960.25 | 1.37 | 3.86 | 39.91 | 112.25 |
| (1,491.20–1,757.32) | (4,194.63–4,943.21) | (72.89–116.81) | (1,468.00–2,352.43) | (0.81–2.08) | (2.28–5.85) | (23.89–61.34) | (67.21–172.55) |
| Iran | 1,241.67 | 1,412.19 | 5.60 | 100.07 | 2.02 | 2.29 | 55.34 | 62.94 |
| (1,136.22–1,359.22) | (1,292.25–1,545.88) | (4.67–6.59) | (83.45–117.84) | (1.42–2.75) | (1.61–3.13) | (39.25–76.03) | (44.64–86.47) |
| Central Asia | 2,124.40 | 2,679.22 | 24.16 | 270.45 | 4.50 | 5.68 | 157.63 | 198.80 |
| (1,965.42–2,298.72) | (2,478.72–2,899.08) | (19.99–30.54) | (223.69–341.81) | (3.87–5.30) | (4.89–6.68) | (134.01–190.29) | (169.01–239.99) |
| Uzbekistan | 1,218.95 | 3,448.87 | 10.03 | 243.25 | 1.69 | 4.79 | 62.37 | 176.47 |
| (1,072.83–1,368.85) | (3,035.44–3,872.99) | (5.72–14.39) | (138.78–349.17) | (1.26–2.30) | (3.57–6.50) | (44.97–86.45) | (127.24–244.61) |
| Kazakhstan | 466.71 | 2,287.52 | 4.98 | 240.14 | 1.49 | 7.28 | 45.57 | 223.35 |
| (411.03–529.14) | (2,014.60–2,593.54) | (3.51–6.04) | (169.12–291.05) | (1.13–1.98) | (5.53–9.69) | (32.79–62.94) | (160.73–308.48) |
| Tajikistan | 194.83 | 1,823.13 | 4.40 | 326.06 | 0.42 | 3.89 | 14.97 | 140.11 |
| (158.38–234.89) | (1,482.10–2,198.05) | (2.58–6.44) | (191.17–477.25) | (0.27–0.57) | (2.50–5.36) | (9.09–21.45) | (85.07–200.77) |
| Oceania | 1,519.49 | 3,287.99 | 120.45 | 3,183.98 | 1.13 | 2.44 | 37.65 | 81.47 |
| (1,438.72–1,605.08) | (3,113.21–3,473.19) | (98.20–146.96) | (2,595.99–3,884.76) | (0.97–1.33) | (2.11–2.88) | (32.31–45.08) | (69.93–97.54) |
| Papua New Guinea | 810.41 | 7,296.64 | 110.41 | 6,716.28 | 0.24 | 2.14 | 9.76 | 87.90 |
| (738.80–886.50) | (6,651.85–7,981.70) | (86.72–132.70) | (5,274.92–8,072.21) | (0.14–0.34) | (1.28–3.10) | (6.12–13.81) | (55.08–124.31) |
| Australia | 480.49 | 1,782.91 | 2.75 | 182.99 | 0.59 | 2.20 | 17.38 | 64.48 |
| (444.95–525.00) | (1,651.03–1,948.04) | (2.26–3.24) | (150.72–215.33) | (0.47–0.75) | (1.76–2.78) | (13.55–21.73) | (50.29–80.64) |
| New Zealand | 92.85 | 1,813.79 | 2.22 | 746.09 | 0.06 | 1.24 | 1.78 | 34.80 |
| (84.15–102.96) | (1,643.75–2,011.29) | (1.86–2.60) | (623.89–873.55) | (0.06–0.07) | (1.08–1.45) | (1.55–2.06) | (30.31–40.17) |
Statistics
Statistical analysis was stratified by four geographic levels: global, regional (Asia-Pacific), subregional (six custom subregions), and national (Supplementary Table 1). For each geographic level, we systematically assessed all-age CHB prevalence, CHB prevalence among children under five years of age, deaths, and DALYs. At the national level, we identified and focused on 18 key countries, specifically the three countries with the highest numbers of prevalent CHB cases in 2023 within each subregion. These countries were then consistently evaluated across all major outcomes, including pediatric prevalence, mortality, DALYs, temporal trends, decomposition analysis, and projections toward 2030. This approach was used to capture both the major contributors to the regional burden and the heterogeneity of pediatric infection across subregions and countries.
Estimates are reported with 95% UIs. Regional point estimates were derived by summing country-level data. To estimate regional UIs, we used a Monte Carlo simulation (1,000 iterations) to account for nonlinear uncertainty propagation. Assuming a log-normal distribution, standard errors were calculated as (ln(Upper UI) - ln(Lower UI)) / 3.92, and random draws were aggregated to generate regional totals and rates, with the 2.5th and 97.5th percentiles of the simulated distribution defining the final 95% UIs.
Temporal trends were analyzed using Joinpoint regression to calculate the average annual percent change (AAPC), and trends were considered statistically significant if the 95% confidence interval (CI) excluded zero. To determine drivers of burden, we applied the Das Gupta decomposition method, partitioning changes in absolute numbers into three components: population growth, population aging, and epidemiological changes in rates.14,26 In this decomposition framework, the epidemiological change component represents changes in age-specific burden rates after holding population size and age structure constant. It should be interpreted as a composite effect of multiple factors, including prevention, diagnosis, treatment, healthcare access, health education, and other unmeasured changes, rather than the effect of any single intervention. Future burden trends from 2024 to 2030 were projected using a Bayesian age-period-cohort (BAPC) model. Age-specific historical estimates of CHB prevalence, deaths, and DALYs from GBD 2023 for 1990–2023 were used as input time-series data. The BAPC model decomposes temporal trends into age, period, and cohort effects, which are smoothed using second-order random-walk priors to stabilize short-term projections. Projected age-specific rates were then combined with future population denominators from the United Nations World Population Prospects 2024 to estimate the numbers of prevalent cases, deaths, and DALYs through 2030. The model was implemented using the BAPC package in R.23 All statistical analyses were performed using R statistical software (version 4.5.0; R Foundation for Statistical Computing, Vienna, Austria) or the Joinpoint Regression Program (Version 5.1.0.0; Statistical Research and Applications Branch, National Cancer Institute).
Discussion
In 2023, the Asia-Pacific region accounted for 63.1% of the global CHB burden (178.0 million cases), with a prevalence rate of 3.7%, which surpassed the global average. The burden was concentrated in East, South, and Southeast Asia, with China (91.2 million), India (30.6 million), and Indonesia (10.0 million) accounting for nearly 75% of regional cases, whereas Western Asia (6.6 million), Central Asia (2.1 million), and Oceania (1.5 million) contributed smaller burdens. Decomposition analysis identified divergent drivers of burden trends (1990–2023). In South Asia, population growth was the dominant driver, overwhelming epidemiological gains and leading to a net rise in absolute cases. In India, although prevalence rates declined, an approximately 1.7-fold increase in the adult population and rapid population growth (contributing a 4,347.1% relative increase) drove absolute numbers higher.23 Furthermore, longitudinal surveillance indicates stagnation in HBsAg prevalence in some cohorts (2.96% in 2013 vs. 2.5% in 2022).27,28 This suggests that low endemicity does not guarantee a decline in transmission without adequate birth-dose coverage and adult test-and-treat strategies. In contrast, East Asia, particularly China, exhibited an inverse dynamic in which epidemiological improvements neutralized demographic pressures. China’s national infant vaccination program (initiated in 1992), for example, reduced HBsAg prevalence from 9.7% in 1992 to 5.6% in 2022.29 This robust epidemiological effect (178.4% reduction contribution) led to a net decline in cases. However, given its massive population and historically high endemicity, China still bears a colossal burden of chronic infections.26,30 Southeast Asia showed an intermediate pattern between South and East Asia. The subregion still carried a large all-age prevalence burden in 2023. Population growth largely offset epidemiological gains, resulting in a persistently high absolute burden. The all-age prevalence rate was low in Western Asia and Central Asia (Western Asia: 1.8%; Central Asia: 2.1%), with the largest declines among the six subregions over time (AAPC: Western Asia: −1.99%; Central Asia: −1.64%), suggesting substantial epidemiological improvement, although demographic expansion partly counterbalanced this progress. Oceania contributed the smallest absolute burden and prevalence rate, with a relatively small decline (AAPC = −1.20%), suggesting limited epidemiological improvement that was offset by population growth. Regarding under-5 control, the region achieved significant progress, with under-5 HBsAg prevalence declining annually by 6.44% (1990–2023), outpacing the global average (3.95%). However, regional differences remain substantial. South Asia had the largest number of under-5 CHB cases (714.1 thousand), followed by East Asia (476.0 thousand) and Southeast Asia (472.0 thousand), whereas Oceania had the highest under-5 prevalence rate (3.2%). Projections to 2030 suggest that all six subregions will remain above the WHO target of 0.1% under-5 HBsAg prevalence, with Oceania and Southeast Asia remaining the highest-rate subregions and Central Asia projected to have the lowest rate. In 2023, 3-dose hepatitis B vaccine coverage was relatively high in East Asia, South Asia, Central Asia, and Western Asia, but lower in Southeast Asia and especially in Oceania excluding Australia and New Zealand (Philippines, birth-dose coverage: 57%, 3-dose coverage: 77%; Papua New Guinea, birth-dose coverage: 26%, 3-dose coverage: 40%; Vietnam, birth-dose coverage: 82%, 3-dose coverage: 65%).24,25
Despite this, the region remains off track for the WHO 2030 target of 0.1% under-5 prevalence. Projections estimate a 0.60% rate by 2030, with the burden concentrated in India, China, and Pakistan. Among the key countries, Japan is the only one projected to meet the under-5 prevalence target (0.04% vs. 0.1%), likely reflecting its long-standing prevention of mother-to-child transmission program and universal infant HBV vaccination.31,32 Unlike many high-burden countries, the decomposition analysis shows that Japan’s CHB prevalence is less affected by the negative pressures of population growth and aging, although mortality remains influenced by the aging of previously infected cohorts. Iran is also close to the under-5 target (0.1% vs. 0.1%), suggesting the benefit of early nationwide infant vaccination and sustained primary prevention.33,34 In China, coverage for the 3-dose HepB series and the timely birth dose (TBD) reached 99.6% and 95.6%, respectively, by 2020.35 Despite these high national averages, however, disparities in TBD coverage persist. A 2019–2021 study in three provinces reported TBD coverage of only 71.41% for preterm infants,36 and rural western China lags behind eastern regions.37 To bridge the gap between 0.30% and the <0.1% target, strategies must shift from general coverage to targeting underserved groups, including preterm infants, migrant populations, and remote rural communities. Elsewhere in South Asia, particularly in India and Pakistan, there is a major gap between routine immunization and birth-dose administration. India achieved approximately 93% third-dose coverage in 2023 following the National Viral Hepatitis Control Program,1,38,39 and Pakistan similarly reduced pediatric HBsAg prevalence to 0.3% in 2019, supported by 74% third-dose coverage. However, TBD coverage remains suboptimal: India reports 63%,38 and Pakistan reports only 3%,40 far below the WHO’s 90% target. Given the significance of perinatal transmission, the discrepancy between high routine coverage and low TBD coverage represents a major missed opportunity. Without scaling up TBD administration, particularly for noninstitutional deliveries, South Asia is unlikely to meet global elimination targets. This highlights that, despite favorable trends, the population scale of high-burden countries sustains a large reservoir of pediatric infections.
Despite effective vaccines and therapies, the Asia-Pacific region accounts for nearly two-thirds of global CHB-related deaths. Decomposition analysis shows that distinct demographic forces drive this mortality burden within high-burden nations. In China and East Asia, population aging is the dominant factor increasing deaths, neutralizing healthcare gains; in India and South Asia, population growth primarily drives the rising death toll; and Indonesia and Southeast Asia face a “double burden” of aging and population growth. Western Asia had the steepest decline in all-age prevalence among the six subregions (AAPC = −1.99%, 95% CI: −2.10% to −1.88%), and epidemiological improvements substantially reduced prevalent cases. However, population expansion and aging still contributed to a modest increase in absolute deaths. Central Asia showed a more concerning pattern: although all-age and under-5 prevalence declined, mortality (AAPC = 0.77%, 95% CI: 0.37% to 1.17%) and DALY rates (AAPC = 0.78%, 95% CI: 0.43% to 1.14%) increased. Decomposition analysis suggested that this increase was mainly driven by population growth and aging, whereas the protective contribution of epidemiological change was limited. Kazakhstan was especially notable, with the steepest increases in mortality and DALY rates among the key countries, and epidemiological change itself contributed positively to the increase in deaths. Projections further showed that India and Bangladesh are the only key countries expected to achieve reductions in all-age deaths, but neither is projected to meet the 65% mortality-reduction target (Bangladesh: 15.5%; India: 0.2%). This should not be interpreted as evidence of sufficient diagnosis or treatment coverage, because both countries still have substantial gaps in the HBV care cascade.21 Rather, the decomposition analysis suggests that the decline in Bangladesh was mainly driven by a favorable epidemiological change component that outweighed demographic pressure, whereas in India, epidemiological gains were largely offset by population growth, aging, and a large reservoir of chronic infections, resulting in a near-stable trend in mortality rates.38 Taken together, these findings indicate that declining prevalence alone is insufficient to achieve mortality reduction. Without expanded adult screening, diagnosis, antiviral treatment, and long-term surveillance, population aging and growth will continue to sustain CHB-related deaths and keep the region off track for the WHO 2030 mortality target.
Timely diagnosis and antiviral treatment are crucial for preventing progression to cirrhosis and HCC. Long-term nucleos(t)ide analogue therapy can suppress HBV replication and reduce the risks of cirrhosis, hepatic decompensation, HCC, and liver-related death.41 Yet coverage in major burden countries remains far below WHO targets (90% diagnosis, 80% treatment). In many high-burden Asia-Pacific countries, diagnosis rates remain low, treatment initiation among eligible patients is inadequate, and long-term retention in care and surveillance for cirrhosis and HCC are insufficient.4 In China, for example, although diagnostic capacity has improved, a substantial treatment gap persists: in 2022, only 24% of approximately 79.7 million infections were diagnosed, and only 15% of eligible patients received treatment.4 In South and Southeast Asia, screening gaps are major obstacles. India reports negligible diagnosis and treatment rates (2.4% and nearly 0%, respectively),38 with similarly low figures in Indonesia.26 Therefore, the projected failure to achieve the mortality target does not primarily reflect a lack of effective treatment, but rather insufficient coverage across the HBV care cascade.21,42 Modeling further indicates that maintaining the status quo will increase mortality, whereas scaling up test-and-treat strategies is cost-effective and lifesaving.43 To reduce the projected mortality rebound, a multidimensional approach is imperative: (1) high-level advocacy to demonstrate the cost-effectiveness of antiviral therapy44; (2) simplifying treatment algorithms and expanding indications according to updated guidelines45; (3) capacity building to decentralize care to local practitioners; (4) strengthening surveillance with HBV-specific notification mechanisms; and (5) piloting micro-elimination programs to test task-shifting and digital linkage-to-care models.
This study has several strengths. First, it uses GBD 2023 data, which incorporate >35,000 new sources and methodological upgrades to increase accuracy. Second, the standardized methodology enables robust comparisons, distinguishing regions that need intensified prevention from those facing rising mortality. Third, decomposition and Bayesian analyses provide insights into demographic drivers and future trends relative to the WHO 2030 targets. However, two limitations should be noted. First, estimates depend on the availability of primary data; in resource-limited settings, reliance on modeling may introduce uncertainty, although consistent frameworks ensure trend validity. Second, this study could not explicitly quantify the effects of specific programmatic or health-system interventions on CHB burden. In the decomposition analysis, the epidemiological change component reflects changes in age-specific burden rates after accounting for population growth and aging, but it could not be further separated into specific drivers such as vaccination, timely birth-dose administration, maternal screening, antiviral treatment coverage, healthcare access, or long-term retention in care. Similarly, the BAPC projections were based on historical GBD estimates and future population projections and did not explicitly incorporate future country-specific policy changes. Because these indicators were not consistently available across all included countries and years, our projections should be interpreted as baseline estimates under current trends rather than scenario-based predictions. Future studies integrating GBD data with country-level programmatic indicators and intervention scenarios are needed to estimate how intensified vaccination, diagnosis, treatment, and surveillance may alter the future CHB burden.
Supporting information
Supplementary Table 1
Countries Included in Each Sub-region of the Asia-Pacific Region.
(PDF)
Supplementary Table 2
Decomposition of Changes in CHB Burden, 1990–2023.
(PDF)
Supplementary Fig. 1
Age-specific Burden of CHB in Key Countries, 2023.
(A) Prevalent Rate in China, DPRK and Japan, (B) Prevalent Rate in Bangladesh, India and Pakistan, (C) Prevalent Rate in Indonesia, Philippines and Viet Nam, D) Prevalent Rate in Iran, Türkiye and Yemen, (E) Prevalent Rate in Kazakhstan, Tajikistan and Uzbekistan, (F) Prevalent Rate in Australia, New Zealand and Papua New Guinea, (G) Death Rate in China, DPRK and Japan, (H) Death Rate in Bangladesh, India and Pakistan, (I) Death Rate in Indonesia, Philippines and Viet Nam, (J) Death Rate in Iran, Türkiye and Yemen, (K) Death Rate in Kazakhstan, Tajikistan and Uzbekistan, (L) Death Rate in Australia, New Zealand and Papua New Guinea, (M) DALYs Rate in China, DPRK and Japan, (N) DALYs Rate in Bangladesh, India and Pakistan, (O) DALYs Rate in Indonesia, Philippines and Viet Nam, (P) DALYs Rate in Iran, Türkiye and Yemen, (Q) DALYs Rate in Kazakhstan, Tajikistan and Uzbekistan, (R) DALYs Rate in Australia, New Zealand and Papua New Guinea. CHB: Chronic Hepatitis B; DALYs: Disability-adjusted life years.
(PDF)
Supplementary Fig. 2
Historical Trends of CHB Burden in Key Countries, 1990–2023.
(B) (A) Prevalent Rate, All Ages, China, DPRK and Japan, (B) Prevalent Rate, All Ages, Bangladesh, India and Pakistan, (C) Prevalent Rate, All Ages, Indonesia, Philippines and Viet Nam, (D) Prevalent Rate, All Ages, Iran, Türkiye and Yemen, (E) Prevalent Rate, All Ages, Kazakhstan, Tajikistan and Uzbekistan, (F) Prevalent Rate, All Ages, Australia, New Zealand and Papua New Guinea, (G) Prevalent Rate, Age Under 5, China, DPRK and Japan, (H) Prevalent Rate, Age Under 5, Bangladesh, India and Pakistan, (I) Prevalent Rate, Age Under 5, Indonesia, Philippines and Viet Nam, (J) Prevalent Rate, Age Under 5, Iran, Türkiye and Yemen,(K) Prevalent Rate, Age Under 5, Kazakhstan, Tajikistan and Uzbekistan, (L) Prevalent Rate, Age Under 5, Australia, New Zealand and Papua New Guinea, (M) Death Rate, All Ages, China, DPRK and Japan, (N) Death Rate, All Ages, Bangladesh, India and Pakistan, (O) Death Rate, All Ages, Indonesia, Philippines and Viet Nam, (P) Death Rate, All Ages, Iran, Türkiye and Yemen, (Q) Death Rate, All Ages, Kazakhstan, Tajikistan and Uzbekistan, (R) Death Rate, All Ages, Australia, New Zealand and Papua New Guinea, (S) DALYs Rate, All Ages, China, DPRK and Japan, (T) DALYs Rate, All Ages, Bangladesh, India and Pakistan, (U) DALYs Rate, All Ages, Indonesia, Philippines and Viet Nam, (V) DALYs Rate, All Ages, Iran, Türkiye and Yemen, (W) DALYs Rate, All Ages, Kazakhstan, Tajikistan and Uzbekistan, (X) DALYs Rate, All Ages, Australia, New Zealand and Papua New Guinea. CHB: Chronic Hepatitis B; DALYs: Disability-adjusted life years.
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Supplementary Fig. 3
Decomposition of Changes in CHB Burden in main countries, 1990–2023.
(C) (A-1) China, Prevalent Cases, (B-1) Japan, Prevalent Cases, (C-1) DPRK, Prevalent Cases, (D-1) India, Prevalent Cases, (E-1) Pakistan, Prevalent Cases, (F-1) Bangladesh, Prevalent Cases, (G-1) Indonesia, Prevalent Cases, (H-1) Viet Nam, Prevalent Cases, (I-1) Philippines, Prevalent Cases, (J-1) Türkiye, Prevalent Cases, (K-1) Yemen, Prevalent Cases, (L-1) Iran, Prevalent Cases, (M-1) Uzbekistan, Prevalent Cases, (N-1) Kazakhstan, Prevalent Cases, (O-1) Tajikistan, Prevalent Cases, (P-1) Papua New Guinea, Prevalent Cases, (Q-1) Australia, Prevalent Cases, (R-1) New Zealand, Prevalent Cases, (A-2) China, Death Cases, (B-2) Japan, Death Cases, (C-2) DPRK, Death Cases, (D-2) India, Death Cases, (E-2) Pakistan, Death Cases, (F-2) Bangladesh, Death Cases, (G-2) Indonesia, Death Cases, (H-2) Viet Nam, Death Cases, (I-2) Philippines, Death Cases, (J-2) Türkiye, Death Cases, (K-2) Yemen, Death Cases, (L-2) Iran, Death Cases, (M-2) Uzbekistan, Death Cases, (N-2) Kazakhstan, Death Cases, (O-2) Tajikistan, Death Cases, (P-2) Papua New Guinea, Death Cases, (Q-2) Australia, Death Cases, (R-2) New Zealand, Death Cases, (A-3) China, DALYs, (B-3) Japan, DALYs, (C-3) DPRK, DALYs, (D-3) India, DALYs, (E-3) Pakistan, DALYs, (F-3) Bangladesh, DALYs, (G-3) Indonesia, DALYs, (H-3) Viet Nam, DALYs, (I-3) Philippines, DALYs, (J-3) Türkiye, DALYs, (K-3) Yemen, DALYs, (L-3) Iran, DALYs, (M-3) Uzbekistan, DALYs, (N-3) Kazakhstan, DALYs, (O-3) Tajikistan, DALYs, (P-3) Papua New Guinea, DALYs, (Q-3) Australia, DALYs, (R-3) New Zealand, DALYs. CHB: Chronic Hepatitis B; DALYs: Disability-adjusted life years.
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Supplementary Fig. 4
Projections of CHB Burden in Key Countries, 2024–2030.
(D) (A) Prevalent Rate, All Ages, China, DPRK and Japan, (B) Prevalent Rate, All Ages, Bangladesh, India and Pakistan, (C) Prevalent Rate, All Ages, Indonesia, Philippines and Viet Nam, (D) Prevalent Rate, All Ages, Iran, Türkiye and Yemen, (E) Prevalent Rate, All Ages, Kazakhstan, Tajikistan and Uzbekistan, (F) Prevalent Rate, All Ages, Australia, New Zealand and Papua New Guinea, (G) Prevalent Rate, Age Under 5, China, DPRK and Japan, (H) Prevalent Rate, Age Under 5, Bangladesh, India and Pakistan, (I) Prevalent Rate, Age Under 5, Indonesia, Philippines and Viet Nam, (J) Prevalent Rate, Age Under 5, Iran, Türkiye and Yemen, (K) Prevalent Rate, Age Under 5, Kazakhstan, Tajikistan and Uzbekistan, (L) Prevalent Rate, Age Under 5, Australia, New Zealand and Papua New Guinea, (M) Death Rate, All Ages, China, DPRK and Japan, (N) Death Rate, All Ages, Bangladesh, India and Pakistan, (O) Death Rate, All Ages, Indonesia, Philippines and Viet Nam, (P) Death Rate, All Ages, Iran, Türkiye and Yemen, (Q) Death Rate, All Ages, Kazakhstan, Tajikistan and Uzbekistan, (R) Death Rate, All Ages, Australia, New Zealand and Papua New Guinea, (S) DALYs Rate, All Ages, China, DPRK and Japan, (T) DALYs Rate, All Ages, Bangladesh, India and Pakistan, (U) DALYs Rate, All Ages, Indonesia, Philippines and Viet Nam, (V) DALYs Rate, All Ages, Iran, Türkiye and Yemen, (W) DALYs Rate, All Ages, Kazakhstan, Tajikistan and Uzbekistan, (X) DALYs Rate, All Ages, Australia, New Zealand and Papua New Guinea. CHB: Chronic Hepatitis B; DALYs: Disability-adjusted life years.
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