目的 分析2015—2021年合肥市流感病原亚型检出情况，了解各亚型的变迁情况以及和疫情关联，为流感预警预测和防控提供参考。方法 对“中国流感监测信息系统”流感监测哨点医院流感样病例（influenza-like illness,ILI）监测、流感病原学、暴发/聚集性疫情等有关数据进行分析。结果2015—2021年合肥市哨点医院门急诊接诊的3 332 553例病例中ILI 139 082例，占4.17%，月占比介于1.60%～7.15%。ILI送检标本14 663份，送检率10.54%，流感病毒检出阳性率为11.30%。每月的ILI占比与检出率之间无相关性（rs=0.176，P=0.107），流感病毒亚型构成比差异较大，呈现多样化的季节性，流行株不断变迁，疫情以乙型Victoria亚型（BV亚型）为主（40.21%）。每月哨点医院ILI中检出阳性率和每月发生疫情的起数之间存在中等相关(rs=0.696，P=0.000)。每月发生的疫情数和检出率存在强相关(rs=0.696，P=0.000)。甲型季H3亚型和BV亚型有强相关关系(rs-季H3=0.686，P=0.030;rs-BV=0.632，P=0.000);甲型新甲1亚型和乙型Yamagata亚型存在中等程度相关（rs-新甲H1=0.481，P=0.000 0；rs-BY=0.515，P=0.000）。结论 合肥市存在春季和冬季两个流行高峰；流感亚型不断变迁，呈现多样化；病原学监测结果可预警预测不同亚型流感暴发/聚集性疫情的流行。应将预测和监测情况及时服务于流感控制和疫情处置中。
Objective To analyze the correlation between detection of influenza pathogenic subtypes and epidemic situation in Hefei City during the surveillance years of 2015-2021, and to provide references for developing influenza prevention and control strategies. Methods The relevant data of influenza-like illness (ILI) surveillance, influenza etiology, and outbreak/cluster outbreaks reported from influenza surveillance sentinel hospitals in Hefei City from 2015 to 2021 in the China Influenza Surveillance Information System were analyzed. The statistical analysis was carried out. Results A total of 3 332 553 outpatient and emergency visits in 2 sentinel hospitals were reported in Hefei City from 2015 to 2021, of which 139,082 were ILI cases, accounting for 4.17%. The monthly proportion ranged from 1.60% to 7.15%. A total of 14 663 ILI specimens were submitted for detection, the submission rate was 10.54%, and the positive rate of influenza virus detection was 11.30%. There was no correlation between the proportion of monthly influenza like cases and the detection rate (rs=0.176, P=0.107). The composition ratio of each subtype of influenza virus varied greatly, showing diversified seasonality, and the epidemic strains changed constantly. The Victoria subtype (BV subtype) was dominant (40.21%). There was a moderate correlation between the positive rate of ILI in sentinel hospitals and the number of outbreaks per month (rs =0.696, P=0.000). There was a strong correlation between the monthly number of outbreaks and the detection rate (rs =0.696, P=0.000). There was a strong correlation between influenza A virus H3 subtype and BV subtype (rs -H3=0.686, P=0.030; rs -BV=0.632, P=0.000). There was a moderate correlation between the new A1 subtype and B Yamagata subtype (rs -new A H1=0.481, P=0.000 0; rs -BY=0.515, P=0.000). Conclusion There are two epidemic peaks in spring and winter in Hefei. Influenza subtypes are diverse. The results of ILI etiology can predict the outbreaks of different subtypes of influenza. Prediction and surveillance should be used for influenza control and outbreak management in a timely manner.