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Background: Chronic hepatitis B has become a major public health problem in China. An accurate depiction of the disease burden has not yet been thoroughly conducted. We aimed to project the disease burden of chronic hepatitis B virus (HBV) infection and related complications by modeling various scenarios. Method: An individual-based Markov model was used to predict disease burden from 2006 through 2050. We simulated 5 scenarios with different annual incidences, diagnoses and nucleotide analog (NA) treatment rates as well as treatment eligibility, which included a natural history without diagnosis or NA therapy, a base case, a World Health Organization (WHO)-proposed target case and two ideal cases. Result: The natural history scenario is projected to have the fewest HBsAg losses (27.59 million) and highest number of HBV-related deaths (27.19 million). With improved diagnosis and treatment rates of NA therapy, ideal cases have fewer HBV-related deaths (14.46-14.77 million) than do WHO-proposed cases (15.13 million) and base cases (16.89 million), but the proportion of HBsAg loss is similar among them. With a reduction in new infections, the prevalence of chronic HBV in 2050 is expected to be a minimum of 27.03-27.49 million under WHO and ideal cases. Conclusion: Ideal scenarios 1 and 2 contribute to the lowest disease burden of HBV and its complications in the future, in which new infection control is more effective than increasing diagnosis, treatment rate and treatment eligibility. However, considering the large existing chronic HBV infected population and the low HBsAg loss rate of NA therapy, it is still difficult to avert the increasing trend of cumulative cirrhosis, DC, HCC, LT, and HBV-related death in all scenarios. If new high-potency drugs are not developed, the disease burden of chronic HBV will remain high in the future.
Zheng, Y., Wu, J., Ding, C., Xu, K., Yang, S., & Li, L. (2020). Disease burden of chronic hepatitis B and complications in China from 2006 to 2050: An individual-based modeling study. Virology Journal, 17(1). https://doi.org/10.1186/s12985-020-01393-z
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