Application of moving epidemic method in early warning of influenza incidence intensity in winter-spring season in Ningbo city
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摘要:
目的 探索移动流行区间法(MEM)在浙江省宁波市冬春季流行性感冒(流感)流行强度预警中的应用,为采取相应的干预措施提供参考依据。 方法 收集2013年1月 — 2022年5月宁波市2家国家级流感哨点医院的流感监测数据,最终选择2013年1月 — 2019年12月的冬春季流感病毒检测阳性率建立MEM模型,对宁波市2019 — 2020年流感流行季(2019年第40周至2020年第20周)开始、结束以及流行强度进行分析,并与实际流行情况进行比较,分析MEM模型的应用效果。 结果 宁波市2013 — 2022年流感病毒分为甲型H1N1、甲型H3N2和乙型(以Victoria株和Yamagata株为主),分别占24.59%、37.03%和38.38%;本研究建立的MEM模型参数 δ 为2.7,灵敏度为87.97%,特异度为87.68%,约登指数为0.76,拟合优度最高;经MEM模型拟合,2019 — 2020年流感季流行开始阈值为22.76%,流行结束阈值为25.05%,中流行强度阈值为43.18%,高流行强度阈值为63.22%,极高流行强度阈值为74.83%;2019年第40周至第48周为流行前期,在2019年第49周流感突破流行开始阈值进入低流行阶段,从第51周开始达到中等流行强度一直持续到2020年第3周,2020年第4周后再降为低流行强度;2020年第7周以后处于流行后阶段,第10周流感流行结束;2019 — 2020年与2013 — 2019年比较,流感流行季的开始时间提前了1周,但流行结束时间提前了3周。 结论 MEM模型在宁波市冬春季流感流行早期识别和流行强度预警中的应用效果较好。 -
关键词:
- 流行性感冒(流感) /
- 流行强度 /
- 预警 /
- 移动流行区间法(MEM) /
- 应用
Abstract:Objective To explore the application of moving epidemic interval method (MEM) in early warning of influenza incidence intensity in winter-spring season in Ningbo city and to provide a reference for developing effective intervention measures. Methods Influenza surveillance data for the period of January 2013 – May 2022 were collected from 2 national influenza sentinel hospitals in Ningbo city, Zhejiang province and a part of the data on positive rate of influenza virus detection among the registered cases in winter-spring seasons from January 2013 to December 2019 were extracted to establish a MEM model. The constructed MEM model was adopted to analyzed the beginning, the end and incidence intensity seasonal influenza epidemic during 2019 – 2020 (40th week, 2019 – 20th week, 2020) in Ningbo city; the model analysis results were compared with actual situation of the epidemic. Results For the virus- positive cases in the city during the 2013 – 2022, the proportions of isolated viral strains were 24.59% for influenza A (H1N1), 37.03% for influenza A (H3N2), and 38.38% for influenza B (mainly Victoria and Yamagata strain), respectively. The established MEM model showed a better goodness-of-fit, with the parameter δ of 2.7, the sensitivity of 87.97%, the specificity of 87.68%, and the Yoden index of 0.76. Based on the fitting results of the established MEM model, the thresholds of virus-positive rate were 22.76% and 25.05% for identifying the onset and the end of the influenza epidemic and the thresholds were 43.18%, 63.22%, and 74.83% for indicating a moderate-, high-, extremely high-intensity of the influenza epidemic during 2019 – 2020 influenza season. With the established MEM threshold estimations, the trajectory of the influenza could described as following: pre-epidemic stage from 40th week to 48th week of 2019, onset/low- intensity stage from 49th week of 2019, moderate-intensity stage from 51th week if 2019 to third week of 2020, subsequent low-intensity stage from 4th week of 2020, late stage from 7th week of 2020, and the end of the epidemic by the 10th week of 2020. Compared to the seasonal epidemics between 2013 – 2019, the 2019 – 2020 winter spring influenza epidemic occurred one week earlier but ended three weeks sooner. Conclusion MEM model could be adopted effectively in early identification and intensity warning of seasonal influenza epidemic. -
Key words:
- influenza /
- epidemic intensity /
- early warning /
- moving epidemic method /
- application
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