Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Renmin South Road 16, Chengdu, Sichuan Province, 610041, PR China.
BMC Public Health. 2020 Dec 14;20(1):1906. doi: 10.1186/s12889-020-09977-8.
To investigate the regional and age-specific distribution of AIDS/HIV in China from 2004 to 2017 and to conduct time series analysis of the epidemiological trends.
Using official surveillance data from publicly accessible database of the national infectious disease reporting system, we described long-term patterns of incidence and death in AIDS/HIV, analyzed age group and regional epidemic characteristics, and established Autoregressive Integrated Moving Average (ARIMA) models for time series analysis.
The incidence and death of AIDS/HIV have increased rapidly from 2004 to 2017, with significant difference regarding age groups and provincial regions (a few provinces appear as hot spots). With goodness-of-fit criteria and using data from 2004 to 2015, ARIMA (0,1,3) × (2,0,0), ARIMA (3,1,0) × (1,0,1), and ARIMA (0,1,2) × (2,0,0) were chosen as the optimal model for the incidence of AIDS, HIV, and combined; ARIMA (0,1,3) × (1,0,0) was chosen as the optimal model for the death of AIDS, HIV, and combined. ARIMA models robustly predicted the incidence and death of AIDS/HIV in 2016 and 2017.
A focused intervention strategy targeting specific regions and age groups is essential for the prevention and control of AIDS/HIV. ARIMA models function as data-driven and evidence-based methods to forecast the trends of infectious diseases and formulate public health policies.
本研究旨在分析 2004 年至 2017 年中国艾滋病/艾滋病病毒（HIV）的地区和年龄分布特征，并进行时间序列分析。
本研究利用国家传染病报告系统公开可获取的监测数据，描述艾滋病/艾滋病病毒的发病和死亡的长期变化趋势，分析年龄组和地区流行特征，并建立自回归求和移动平均（ARIMA）模型进行时间序列分析。
艾滋病/艾滋病病毒的发病率和死亡率从 2004 年至 2017 年迅速上升，不同年龄组和省级地区之间存在显著差异（少数省份呈热点分布）。拟合优度标准显示，使用 2004 年至 2015 年的数据，ARIMA（0，1，3）×（2，0，0）、ARIMA（3，1，0）×（1，0，1）和 ARIMA（0，1，2）×（2，0，0）分别是艾滋病、HIV 和合并发病的最佳模型；ARIMA（0，1，3）×（1，0，0）是艾滋病、HIV 和合并死亡的最佳模型。ARIMA 模型能够稳健地预测 2016 年和 2017 年艾滋病/艾滋病病毒的发病和死亡情况。
针对特定地区和年龄组的重点干预策略对于艾滋病/艾滋病病毒的防控至关重要。ARIMA 模型是一种基于数据和证据的传染病趋势预测方法，可为公共卫生政策的制定提供依据。
