国际生殖健康/计划生育杂志

国际生殖健康/计划生育杂志 ›› 2026, Vol. 45 ›› Issue (2): 104-111.doi: 10.12280/gjszjk.20250635

• 论著 • 上一篇    下一篇

2020—2024年广州市免费避孕药具在线领取的时空特征与SARIMA预测模型研究

张玉仙, 邹美华, 李优云, 古冬玲()   

  1. 510405 广州市白云区妇幼保健院计划生育技术部（张玉仙，李优云，古冬玲）; 广州市疾病预防控制中心（广州市卫生监督所） 艾滋病预防控制部（邹美华）
  • 收稿日期:2025-12-24 出版日期:2026-03-15 发布日期:2026-04-07
  • 通讯作者: 古冬玲 E-mail:1045758154@qq.com
  • 基金资助:
    白云区2025年度医疗卫生科技计划项目(2025-YL-019)

Spatiotemporal Characteristics and SARIMA Prediction Model of Online Contraceptive Claims in Guangzhou from 2020 to 2024

ZHANG Yu-xian, ZOU Mei-hua, LI You-yun, GU Dong-ling()   

  1. Department of Family Planning Technical Services, Guangzhou Baiyun District Maternal and Child Health Hospital, Guangzhou 510405, China (ZHANG Yu-xian, LI You-yun, GU Dong-ling); Department of HIV/AIDS Prevention and Control, Guangzhou Center for Disease Control and Prevention (Guangzhou Health Supervision Institute), Guangzhou 510405, China (ZOU Mei-hua)
  • Received:2025-12-24 Published:2026-03-15 Online:2026-04-07
  • Contact: GU Dong-ling E-mail:1045758154@qq.com

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摘要：

目的：分析广州市免费避孕药具在线领取的时空演变特征，并构建时间序列预测模型，为免费避孕药具“互联网+服务”的资源优化与政策调整提供量化依据。方法：基于2020—2024年广东省免费提供基本避孕药具服务管理系统308 419人次在线领取记录，结合常住育龄妇女数据，运用多时间维度趋势分析、空间自相关季节性自回归积分滑动平均模型（seasonal autoregressive integrated moving average model，SARIMA）、自回归积分滑动平均模型（autoregressive integrated moving average model，ARIMA）、指数平滑状态空间模型（exponential smoothing state space model，ETS）、三角季节性Box-Cox变换ARMA误差趋势季节性分量模型（trigonometric, box-cox transformation, ARMA errors, trend and seasonal components model，TBATS）、神经网络自回归模型（neural network autoregression model，NNAR）以及Prophet模型等6种时间序列模型，对广州市11个行政区域的免费避孕药具在线领取进行时空特征分析，并预测2025—2026年月度需求。结果：①时序特征：2020—2024年年领取量由40.9万只增至370.2万只（年度复合增长率达65.2%），呈阶梯式攀升；月度分布呈“3 月主峰、9月和12月次峰”的季节性；周一因在线领取平台的公众号推文触发，形成周内高峰。②空间特征：2020—2024年各区人均领取量均上升，白云区、天河区最高；全局Moran's I持续为负（-0.416~-0.360，P>0.05），无显著聚集，提示药具在线发放能打破地域限制，促进服务均等化。③预测模型中SARIMA(1,1,1)(1,1,1)[12]在6种模型中精度最高（MAPE=10.85%）；广州市的免费避孕药具在线月度申领数量预计从2025年1月的31.68万只逐渐增加到2026年12月的47.69万只，2025年和2026年的预测同比增速分别为20.14%和19.01%，各区均呈稳健增长。结论：广州市在线药具需求呈一定的季节性与持续上升态势，呈现显著的空间分散特征；SARIMA 模型适配性强，研究揭示的时空规律为避孕药具精准供应、数字化服务优化提供科学支撑。

关键词: 卫生保健提供, 互联网+服务, 时空分析, SARIMA模型, 预测

Abstract:

Objective: To analyze the spatiotemporal evolution characteristics of online claims for free contraceptive supplies in Guangzhou and to construct a time series prediction model, thereby providing a quantitative basis for resource optimization and policy adjustment of "Internet-based services" for free contraceptives. Methods: Based on 308 419 online claim records from the Guangdong Province Free Essential Contraceptive Service Management System (2020—2024) and data of the permanent resident women of reproductive age, we conducted multi-time-scale trend analysis and spatial autocorrelation analysis. For the demand forecasting, six time-series models—seasonal autoregressive integrated moving average model (SARIMA), autoregressive integrated moving average model (ARIMA), exponential smoothing state space model (ETS), trigonometric, box-cox transformation, ARMA errors, trend and seasonal components model (TBATS), neural network autoregression model (NNAR), and Prophet model—were compared. These approaches were used to characterize the spatiotemporal patterns of online contraceptive requisitions across the 11 districts of Guangzhou and to project monthly demand for 2025—2026. Results: ①Temporal characteristics. From 2020 to 2024, the annual volume of claims was increased from 0.409 million to 3.702 million units (CAGR=65.2%), showing a step-like climb. The monthly distribution was exhibited seasonality with a "primary peak in March, and secondary peaks in September and December". The claims peaked on Mondays within the week, triggered by official account push notifications from the online platform. ② Spatial characteristics. The per capita claim volume was increased across all districts, during 2020—2024, with Baiyun and Tianhe districts having the highest volumes. The global Moran's I was consistently negative (-0.416- -0.360, P>0.05), indicating no significant spatial clustering, which suggests that the online distribution can break geographical barriers and promote service equity. ③Forecasting models. The highest accuracy of SARIMA (1,1,1) (1,1,1)[12] model was demonstrated, among the six models (MAPE=10.85%). The projected monthly online claims for free contraceptives citywide were expected to increase gradually from 316 800 units in January 2025 to 476 900 units in December 2026. The projected year-on-year growth rates for 2025 and 2026 were 20.14% and 19.01%, respectively, indicating a steady growth across all districts. Conclusions: The demand for online contraceptives in Guangzhou shows seasonality and a sustained upward trend, while demonstrating a pronounced pattern of spatial dispersion. The SARIMA model has a strong adaptability. The spatiotemporal patterns revealed by this study may provide scientific support for the precise supply of contraceptives and the optimization of digital services.

Key words: Delivery of health care, Internet-based service, Spatio-temporal analysis, SARIMA model, Forecasting