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Abstract：
China faces challenges in meeting the World Health Organization (WHO)\'s target of reducing hepatitis B virus (HBV) infections by 95% using 2015 as the baseline. Using Global Burden of Disease (GBD) 2019 data, joinpoint regression models were used to analyse the temporal trends in the crude incidence rates (CIRs) and age-standardized incidence rates (ASIRs) of acute HBV (AHBV) infections in China from 1990 to 2019. The age-period-cohort model was used to estimate the effects of age, period, and birth cohort on AHBV infection risk, while the Bayesian age-period-cohort (BAPC) model was applied to predict the annual number and ASIRs of AHBV infections in China through 2030. The joinpoint regression model revealed that CIRs and ASIRs decreased from 1990 to 2019, with a faster decline occurring among males and females younger than 20 years. According to the age-period-cohort model, age effects showed a steep increase followed by a gradual decline, whereas period effects showed a linear decline, and cohort effects showed a gradual rise followed by a rapid decline. The number of cases of AHBV infections in China was predicted to decline until 2030, but it is unlikely to meet the WHO\'s target. These findings provide scientific support and guidance for hepatitis B prevention and control.
摘要：
中国在实现世界卫生组织（WHO）的目标，以2015年为基线，将乙型肝炎病毒（HBV）感染减少95％的目标方面面临挑战。使用2019年全球疾病负担(GBD)数据，使用联合点回归模型分析1990年至2019年中国急性HBV(AHBV)感染粗发病率(CIR)和年龄标准化发病率(ASIR)的时间趋势.年龄-时期-队列模型用于估计年龄的影响，period,和出生队列对AHBV感染风险，而贝叶斯年龄期队列（BAPC）模型用于预测到2030年中国AHBV感染的年度数量和ASIR。联合点回归模型显示，从1990年到2019年，CIRs和ASIR下降，其中20岁以下的男性和女性下降更快。根据年龄-时期-队列模型，年龄效应显示出急剧增加，然后逐渐下降，而周期效应显示出线性下降，队列效应显示逐渐上升，随后迅速下降。预计到2030年，中国的AHBV感染病例数将下降，但不太可能达到WHO的目标。这些发现为乙型肝炎的预防和控制提供了科学支持和指导。
