热带病与寄生虫学 ›› 2025, Vol. 23 ›› Issue (4): 222-228.doi: 10.20199/j.issn.1672-2302.2025.04.006

• 防治研究 • 上一篇    下一篇

云南省诺如病毒感染流行特征与趋势预测

郑尔达1(), 贾豫晨1(), 刘思娴2, 沈秀莲1, 黄甜1, 何继波1(), 刘慧慧3()   

  1. 1.云南省疾病预防控制中心云南昆明 650500
    2.昆明医科大学
    3.中国疾病预防控制中心
  • 收稿日期:2024-11-28 出版日期:2025-08-20 发布日期:2025-09-19
  • 通信作者: 何继波,E-mail: ynhejibo@163.com;刘慧慧,E-mail: liuhh@chinacdc.cn
  • 作者简介:郑尔达,男,硕士,主管医师,研究方向:传染病控制与卫生应急。E-mail: 755130864@qq.com;|贾豫晨,女,硕士,主管医师,研究方向:传染病控制与卫生应急。E-mail: 116431867@qq.com
  • 基金资助:
    云南省疾病预防控制中心科技计划项目(2023ZX011)

Epidemiological characteristics and prediction of epidemic trend of norovirus infections in Yunnan Province

ZHENG Erda1(), JIA Yuchen1(), LIU Sixian2, SHEN Xiulian1, HUANG Tian1, HE Jibo1(), LIU Huihui3()   

  1. 1. Yunnan Center for Disease Control and Prevention, Kunming 650500, Yunnan Province, China
    2. Kunming Medical University
    3. Chinese Center for Disease Control and Prevention
  • Received:2024-11-28 Online:2025-08-20 Published:2025-09-19
  • Contact: HE Jibo, E-mail: ynhejibo@163.com; LIU Huihui, E-mail: liuhh@chinacdc.cn

摘要:

目的 分析云南省诺如病毒感染的流行特征,探讨差分自回归移动平均(autoregressive integrated moving average, ARIMA)模型与前瞻性时空扫描在诺如病毒感染发病趋势分析及早期预警中的应用。方法 收集中国疾病预防控制信息系统中2017—2024年云南省报告的诺如病毒感染病例资料,采用描述流行病学方法分析病例的时间、地区、人群等分布特征;构建ARIMA模型,采用前瞻性时空扫描对报告病例数进行时空聚集性分析。结果 2017—2024年云南省累计报告诺如病毒感染病例15 600例,2024年报告发病率最高(17.473/10万)。发病高峰整体为2—5月,报告病例数占总病例数的53.99%(8 422/15 600)。年均报告发病率前3位的州(市)为曲靖市(14.167/10万)、普洱市(11.062/10万)、丽江市(10.706/10万)。人群分布中,男性和女性报告病例数分别为8 709例和6 891例;0~4岁人群报告病例数占比最高,为68.93%(10 753/15 600);职业主要为散居儿童,占63.23%(9 864/15 600)。ARIMA(2,0,0)(0,1,0)12模型Ljung-Box Q=7.449(P=0.964),提示残差序列为白噪声;模型拟合效果较好,2024年1—12月预测值与实际值相对误差为14.76%。在前瞻性时空扫描中,以50%风险人口数作为最大空间扫描窗口,14 d作为最大时间扫描窗口进行时空扫描聚集性分析,得出的2024年1月时空聚集区与实际发生聚集性疫情的地区一致,发出预警时间比实际发生时间提前5 d。结论 近年来,云南省诺如病毒感染报告病例数快速上升,病例报告的地区范围扩大,5岁以下散居儿童是主要发病人群。利用ARIMA模型和前瞻性时空扫描可较为准确地进行早期预警。

关键词: 诺如病毒, 流行特征, ARIMA模型, 前瞻性时空扫描, 预测

Abstract:

Objective To analyze the epidemiological characteristics of norovirus infection in Yunnan Province from 2017 to 2023,and assess the application of autoregressive integrated moving average (ARIMA) model and prospective spatialtemporal scan statistics in the incidence trend and early warning of norovirus infection. Methods The case data of norovirus infections in Yunnan Province reported from 2017 to 2024 were collected from the Chinese Disease Prevention and Control Information System, and analyzed regarding the characteristics of temporal, regional, and population distribution using descriptive epidemiology. ARIMA model was established to predict the number of cases, and prospective spatio-temporal scan was used for spatiotemporal aggregation analysis of monthly reported cases. Results Between 2017 and 2024, a total of 15 600 cases of norovirus infections were reported in Yunnan Province, with the highest incidence reported in 2024 (17.473 /100 000). The incidence generally peaked from February to May, during which 53.99% (8 422/15 600) of the cases were reported. The top three prefectures (cities) with higher annual reported incidence were Qujing City (14.167 /100 000), Pu’er City (11.062 /100 000) and Lijiang City (10.706 /100 000). By population distribution, 8 709 cases were males, and 6 891 females. The 0-4 age group had the highest proportion of reported cases, who accounted for 68.93% (10 753/15 600). Children living at home were dominated by occupation distribution, who accounted for 63.23% (9 864/15 600). Ljung Box test of ARIMA (2,0,0)(0,1,0)12 model indicated Q=7.449 (P=0.964), and that the residual sequence was white noise. The model fitting effect appeared sound. The relative error between predicted value and the actual value from January to December 2024 was 14.76%. In the prospective spatiotemporal scanning statistics, 50% of the high-risk population was used as the maximum spatial scanning window, and 14 days were used as the maximum time scanning window for spatiotemporal scanning clustering analysis. The results showed that the spatiotemporal clustering areas in January 2024 were consistent with the actual areas where clustering epidemics occurred, and the warning time was 5 days earlier than the outbreak occurred. Conclusion In recent years, the number of reported cases of norovirus infection in Yunnan Province has risen rapidly, and the areas with reported infections expanded. Children under 5 years old living at home are the main affected population. ARIMA model and prospective spatiotemporal scan statistics can be more accurate for early warning of this infection, which has important application value in practical work.

Key words: Norovirus, Epidemiological characteristics, ARIMA model, Prospective spatiotemporal scan, Prediction

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