基于城市污水监测系统的2023年广东省深圳市某区域流行性感冒流行趋势分析

古丽斯; 李雪梅; 林凯; 龚泽龙; 徐震东; 黄仁湛; 崔栋; 肖娜

doi:10.3784/jbjc.202406230373

基于城市污水监测系统的2023年广东省深圳市某区域流行性感冒流行趋势分析

Analysis on incidence trend of influenza in an area of Shenzhen, Guangdong in 2023 based on urban wastewater surveillance system

摘要

摘要:
目的分析广东省深圳市某区域污水中流感病毒监测情况，评估其预警效果，为流感病毒污水监测的应用提供参考。
方法依托深圳市新型冠状病毒污水监测系统，2023年第10周至2024年第9周选取某区域污水监测点4个，每周开展流感病毒检测。运用Kendall's tau及时间滞后互相关方法分析污水中流感病毒浓度与流行性感冒（流感）报告病例数的相关性和时效性。
结果该区域监测周期内共报告流感病例5 066例，报告发病率为4.61%。污水样品流感病毒检出率（42.31%，88/208）高于流感样病例中流感病毒检出率（38.48%，227/575），差异无统计学意义（χ²=0.509，P=0.476）。污水流感病毒浓度为0～4.11×10⁶拷贝/mL，呈现春、秋、冬季3个流行高峰，春季以H1N1亚型为主（34.62%），秋、冬季以H3N2型为主，分别占23.08%、36.54%。 Kendall's tau相关分析结果显示，污水中流感病毒浓度与流感报告病例数相关系数为0.63且差异有统计意义（Z=6.507，P＜0.001）。时间滞后互相关分析显示，流感报告病例数向右（未来方向）平移1周时，污水中流感病毒浓度达到最大的相关性（平移量=1）。
结论该区域污水监测反映的流感病毒流行趋势、病毒亚型构成与基于医疗机构的流感报告病例监测数据资料相关性较高，能提前1周预警流行高峰，可作为传统流感病例监测系统的补充。

Abstract:
Objective To analyze the wastewater surveillance data of influenza virus in an area in Shenzhen, Guangdong province, evaluate its early warning effect and provide reference for the application of wastewater surveillance for influenza virus.
Methods Based on the wastewater surveillance system for severe acute respiratory syndrome coronavirus 2 in Shenzhen, influenza virus detection was conducted weekly at four wastewater surveillance sites in an area in Shenzhen from the 10^th week of 2023 to the 9^th week of 2024. Kendall's tau and time-lagged cross-correlation methods were used to analyze the correlation between the influenza virus concentration in wastewater and the reported influenza cases.
Results During the surveillance period, a total of 5 066 influenza cases were reported in this area, with an incidence rate of 4.61%. The detection rate of influenza virus in wastewater samples was 42.31% (88/208), higher than influenza-like illness detection rate (38.48%, 227/575), the difference was not significant (χ²=0.509, P=0.476). The concentration of influenza virus in wastewater ranged from 0 to 4.11×10⁶ copies/mL. The detection rate was high in spring, autumn, and winter. H1N1 subtype was predominated in spring (34.62%), while H3N2 subtype was predominated in autumn (23.08%) and in winter (36.54%). Kendall's tau correlation analysis showed a significant correlation coefficient of 0.63 between the concentration of influenza virus in wastewater and the reported influenza case count (Z=6.507, P<0.001). Time-lagged cross-correlation analysis indicated that when the reported influenza case count shifted to the right (future direction) by one week, the concentration of influenza virus in wastewater showed the highest correlation (offset=1).
Conclusion The influenza virus detection rate and virus subtype composition reflected by wastewater surveillance in this area were significantly correlated with the hospital-based influenza surveillance data, and early warning of influenza epidemic by one week can be made based on wastewater surveillance results. It is demonstrated that the wastewater surveillance could be used as a supplement to the traditional influenza surveillance system.

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