2020-2024年黑龙江省耐药结核病流行病学特征及发病趋势预测

Epidemiological characteristics and incidence prediction of drug-resistant tuberculosis in Heilongjiang, 2020−2024

  • 摘要:
    目的 探讨高纬度寒冷地区黑龙江省耐药结核病流行病学特征,揭示其时空传播规律,并预测其发病趋势,为黑龙江省制定有效的耐药结核病防治策略提供科学依据。
    方法 采用描述性流行病学、全局趋势面分析、空间自相关分析和季节性自回归移动平均(SARIMA)模型,对2020-2024年黑龙江省耐药结核病数据进行统计分析并预测。
    结果 2020-2024年黑龙江省共报告耐药结核病6 489例,年均耐药结核病发病率为4.19/10万,发病率呈先上升后下降趋势。男女性别比为3.08∶1,病例主要集中于中老年群体(68.81%)、家务及待业人群(58.36%)。鹤岗市(7.49/10万)、七台河市(6.26/10万)和鸡西市(6.08/10万)耐药结核病发病率位列前三。黑龙江省耐药结核病发病在空间分布上呈现南高北低、东中部高、西部低的态势,2024年发病率呈现空间聚集分布(全局Morans's I>0,P<0.05),齐齐哈尔市、大庆市和绥化市均呈现出低−低聚集特征,佳木斯市和双鸭山市均呈现高−高聚集特征,牡丹江市呈低-高聚集特征。时间序列分析显示,2020-2024年黑龙江省耐药结核病发病具有明显的季节性特征,存在2个高峰,夏季(6-8月)是发病主高峰,春季(3-4月)是次高峰。基于2020-2023年的训练集数据构建SARIMA(1,1,1)×(1,1,1)12预测模型,模型拟合效果较好。预测结果显示,2025-2026年耐药结核病发病数呈明显的季节性波动,夏季和春季为发病高峰。
    结论 2020-2024年黑龙江省耐药结核病防治具有成效,发病率呈先上升后下降趋势,2020-2022年上升趋势平缓,2023年上升趋势显著,2024年发病率转为下降。需持续监测耐药结核病,加强耐药高危人群筛查和登记管理,以减少耐药结核病的传播和死亡。

     

    Abstract:
    Objective To understand the epidemiological characteristics of drug-resistant tuberculosis (TB) in Heilongjiang province, a high-latitude cold region, reveal its spatiotemporal transmission pattern, and predict its incidence, and provide scientific evidence for the development of effective prevention and control strategies for drug-resistant TB in Heilongjiang.
    Methods Descriptive epidemiology, global trend surface analysis, spatial autocorrelation analysis and seasonal autoregressive moving average (SARIMA) model were used for the statistical analysis and prediction based on the incidence data of drug-resistant TB in Heilongjiang from 2020 to 2024.
    Results A total of 6 489 cases of drug-resistant TB were reported in Heilongjiang from 2020 to 2024, with an average annual incidence rate of 4.19/100 000. The incidence rate showed a increasing trend, then a decreasing trend. The male to female ratio of the cases was 3.08∶1, and the majority of the cases were middle-aged and elderly people (68.81%) and the jobless or the unemployed (58.36%). The top three areas with high incidence rates of drug resistant TB were Hegang (7.49/100 000), Qitaihe (6.26/100000), and Jixi (6.08/100 000). Spatially, the incidence of drug-resistant TB in Heilongjiang exhibited a pattern of higher rate in southern area and lower rate in northern area, higher rate in both eastern and central areas, and lower rate in western area. In 2024, the incidence showed spatial clustering (global Moran's I>0, P<0.05) , with Qiqihar, Daqing and Suihua as low-low clustering area, Jiamusi and Shuangyashan as high-high clustering area, Mudanjiang as low-high clustering area. Time series analysis indicated that the incidence of drug-resistant TB in Heilongjiang from 2020 to 2024 demonstrated clear seasonal patterns, with the primary peak in summer (June–August) and the secondary peak in spring (March–April). SARIMA (1,1,1) × (1,1,1)12, prediction model was constructed based on training data from 2020 to 2023, showing good overall model fit. Predictions for the 2025−2026 incidence of drug-resistant tuberculosis indicated continued seasonal fluctuations, with the main peaks in summer and spring.
    Conclusion The prevention and control of drug-resistant TB was effective in Heilongjiang from 2020 to 2024. The incidence rate of drug resistant TB increased first and then decreased. The upward trend from 2020 to 2022 was mild, and the upward trend in 2023 was significant, and the incidence rate began to decrease in 2024. Continuous surveillance is essential, along with enhanced screening and registration management of populations at high risk, to reduce transmission and mortality of drug resistant TB.

     

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