1.南京医科大学康达学院医学信息工程学部，江苏 连云港 222000 ;2.连云港市第一人民医院信息部，江苏 连云港 222000
R512.6；R181.3
南京医科大学康达学院第二期品牌专业建设工程资助项目（JX206000302）；南京医科大学康达学院医学信息模拟及预测科研团队资助项目（KD2022KYCXTD003）
1.Department of Medical Information Engineering，Kangda College，Nanjing Medical University，Lianyungang 222000 ;2.Information Department of the First People’s Hospital of Lianyungang City，Lianyungang 222000 ，China
目的：探讨2019—2023年新型冠状病毒肺炎（coronavirus disease-2019，COVID-19）疫情前后我国4种肝炎（甲肝、乙肝、丙肝和戊肝）发病趋势的变化规律性，为疫情后肝炎防治提供参考依据。方法：通过我国2012—2023年4种肝炎时间序列的描述统计和季节性分解，对2019—2023年COVID-19疫情前后肝炎月发病数以及时间序列的长期趋势、季节因子和方差贡献率的动态变化进行比较和分析。结果：COVID-19疫情期间的2020—2022年，4种肝炎的平均月发病数低于疫情前的2019年，每种肝炎都出现2012年以来的历史最低值，疫情后的2023年月发病数都出现上升趋势。时间序列的分解表明，甲肝、乙肝、丙肝和戊肝，2012—2019 年与 2012—2023 年的季节因子高度相关，相关系数分别为 0.964、0.964、0.947 和 0.977（P 均< 0.001）。 2012—2019年、2012—2020年、2012—2021年、2012—2022年及2012—2023年4种肝炎的时间序列的方差呈上升趋势，长期趋势的方差贡献率呈上升趋势，与方差的相关系数分别为0.979、0.981、0.890和0.938（P均 < 0.05），季节因子的方差贡献率呈下降趋势，与方差的相关系数分别为 -0.978、-0.986、-0.954和 -0.936（P均 < 0.05）。结论：时间序列分解有助于研究肝炎长期趋势变化和周期性波动的规律性。甲肝和乙肝时间序列图的长期趋势变化特征明显，丙肝、戊肝时间序列图的周期性波动特征明显。疫情防控减少了4种肝炎的月发病数，对月发病数的长期趋势有较大影响，未改变发病低谷期和高峰期的周期性特征。面临疫情后肝炎发病数上升的挑战，要加强疫情后肝炎的监测工作，研究肝炎发病规律性，做好防控和治疗工作。
Objective：To explore the changing regularity of the incidence trend of four types of hepatitis（hepatitis A，hepatitis B， hepatitis C and hepatitis E）in China before and after the coronavirus disease-2019（COVID-19）pandemic between 2019 and 2023， and provide a reference for the prevention and treatment of hepatitis after the epidemic. Methods：Based on the descriptive statistics and seasonal decomposition of the four hepatitis time series between 2012 and 2023 in China，the monthly cases before and after the COVID-19 pandemic in 2019 and 2023 were compared and analyzed，as well as the long-term trend，seasonal factors and the dynamic change of variance contribution rate of the time series. Results：During the COVID-19 epidemic between 2020 and 2022，the average monthly cases of four types of hepatitis were lower than that in 2019 before the epidemic，each type of hepatitis had reached its lowest historical value since 2012，and the monthly cases of 2023 after the epidemic appeared an upward trend. The decomposition of time series showed that the seasonal factors of hepatitis A，B，C，and E in 2012- 2019 and 2012- 2023 were highly correlated，with correlation coefficients of 0.964，0.964，0.947，and 0.977，respectively（all P < 0.001）. The variance of the time series of the four types of hepatitis of 2012-2019，2012-2020，2012-2021，2012-2022，2012-2023 showed an upward trend，the long-term trend variance contribution rates showed an upward trend，with correlation coefficients of 0.979，0.981，0.890，and 0.938 with variance，respectively （all P < 0.05），but the seasonal factor variance contribution rates showed a downward trend，with correlation coefficients of -0.978， -0.986，-0.954，and -0.936 with variance，respectively（all P < 0.05）. Conclusion：The decomposition of the time series is helpful to study the regularity of the long -term trend changes and periodic fluctuation of hepatitis. The long -term trend is obvious for the time series diagram of hepatitis A or B，and the periodic fluctuation is obvious for the time series diagram of hepatitis C or E. The epidemic prevention and control have reduced the monthly cases of four types of hepatitis，which has a significant impact on the long-term trend of monthly cases but has not changed the cyclical characteristics of the low and peak periods of incidence. Faced with the challenge of an increase in the cases of hepatitis after the epidemic，it is necessary to strengthen the monitoring of hepatitis，explore the regularity of hepatitis incidence，and do a good job in prevention，control and treatment of hepatitis.
陈静,瞿怀荣,赵巍,冯永华,丁勇.新型冠状病毒肺炎疫情前后我国4种肝炎发病趋势的时间序列分析[J].南京医科大学学报（自然科学版）,2025,(3):334-345
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