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Background: This study aims to analyze the trend of Hepatitis B incidence in Xiamen City from 2004 to 2022, and to select the best-performing model for predicting the number of Hepatitis B cases from 2023 to 2027. Methods: Data were obtained from the China Information System for Disease Control and Prevention (CISDCP). The Joinpoint Regression Model analyzed temporal trends, while the Age-Period-Cohort (APC) model assessed the effects of age, period, and cohort on hepatitis B incidence rates. We also compared the predictive performance of the Neural Network Autoregressive (NNAR) Model, Bayesian Structural Time Series (BSTS) Model, Prophet, Exponential Smoothing (ETS) Model, Seasonal Autoregressive Integrated Moving Average (SARIMA) Model, and Hybrid Model, selecting the model with the highest performance to forecast the number of hepatitis B cases for the next five years. Results: Hepatitis B incidence rates in Xiamen from 2004 to 2022 showed an overall declining trend, with rates higher in men than in women. Higher incidence rates were observed in adults, particularly in the 30-39 age group. Moreover, the period and cohort effects on incidence showed a declining trend. Furthermore, in the best-performing NNAR(10, 1, 6)[12] model, the number of new cases is predicted to be 4271 in 2023, increasing to 5314 by 2027. Conclusions: Hepatitis B remains a significant issue in Xiamen, necessitating further optimization of hepatitis B prevention and control measures. Moreover, targeted interventions are essential for adults with higher incidence rates.
RESUMEN
Background: The pivotal phase 3 efficacy clinical trial has demonstrated that a two-dose regimen of dNS1-RBD (Beijing Wantai Biological Pharmacy Enterprise, Beijing, China) is well-tolerated and provides wide protection against SARS-CoV-2 infection. However, the effectiveness of a single-dose regimen is still unknown. We aimed to estimate the effectiveness of one-dose of dNS1-RBD against symptomatic Omicron infections in real-world conditions. Methods: This prospective cohort study was conducted during an Omicron outbreak among healthcare workers in Xiamen, China, from December 22, 2022 to January 16, 2023. Participants chose to receive single-dose of dNS1-RBD or remain unvaccinated based on personal preference. Healthcare workers daily validated their SARS-CoV-2 infection status, using either RT-PCR or rapid antigen test. A survey questionnaire was conducted to gather information on acute symptoms from individuals infected with SARS-CoV-2. The primary outcome was the symptomatic SARS-CoV-2 infections after enrollment in the dNS1-RBD recipients or the control group among all participants and by prior COVID-19 vaccination status. Findings: On December 22, 2022, a total of 1391 eligible participants without a history of prior SARS-CoV-2 infection were enrolled. Among them, 550 received single-dose of dNS1-RBD, while 841 remained unvaccinated. In the total cohort, the range of follow-up time was 1â¼26 days. During the study period, a total of 880 symptomatic SARS-CoV-2 infections were identified in the total cohort. The adjusted vaccine effectiveness against symptomatic SARS-CoV-2 infections and the infections requiring medical attention were 19.0% (95% CI: 6.7, 29.7, P = 0.004) and 59.4% (95% CI: 25.1, 78.0, P = 0.004) in the total cohort, 11.6% (95% CI: -2.4, 23.7, P = 0.100) and 55.3% (95% CI: 15.3, 76.4, P = 0.014) in the participants with inactivated COVID-19 vaccination history, as well as 87.0% (95% CI: 72.6, 93.9, P < 0.001) and 84.2% (95% CI: -41.8, 98.2, P = 0.099) in the naïve participants, respectively. Interpretation: When administered as a booster to individuals with a history of inactivated COVID-19 vaccination, a single-dose of dNS1-RBD provides protection against infections requiring medical attention at least in the short-term after vaccination. The data also showed that a single-dose of dNS1-RBD is protective against symptomatic SARS-CoV-2 infections as a primary immunization for individuals without prior exposure, but due to the limited sample size of naïve participants, further research with a larger sample size is needed to make a solid conclusion. Funding: Xiamen Science and Technology Bureau 2022 General Science and Technology Plan Project and the Bill & Melinda Gates Foundation.