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目的探讨季节性流感监测的同时,针对人群中循环的优势毒株开展基因变异分析的意义。方法以2007年深圳市流感监测系统累积的数据为基础,按周分析不同监测医院流感样病例占门诊和急诊就诊者的比例,并对病毒型别进行常规分离鉴定,对优势毒株扩增HA1区基因片段,并进行基因变异分析。结果深圳市流感样病例2007年流感样病例(ILI)比例为6.67%,以低年龄为高发人群;按市、区医院和社区健康服务中心等分别分析,ILI的比例按周分布一致,呈现明显的夏季高峰,最活跃季节在5～7月;ILI暴发疫情比散发病例提早2周出现。流感病毒分离率为11.63%,优势株为H3N2亚型(占59.5%),B型次之(占37.0%)。H3N2亚型流感病毒HA1基因进化分析分成两支,WHO当年疫苗株和我国代表株仅与1～4月毒株接近,而与5月之后分离株产生了遗传距离,虽然还不能确定新的变异株出现,但提示A/sz/9/2007和A/sz122/2007两个分离株值得高度关注。B型流感病毒HA1基因进化分析发现,2007年以Yamagata系最活跃。结论季节性流感监测中开展病毒分子变异分析,可以进一步查明人群中所发生的优势毒株的特性,便于流行病学综合分析。
Objective To investigate the effect of seasonal influenza surveillance on the genetic variation of dominant strains circulating in the population. Methods Based on the data accumulated in Shenzhen’s influenza surveillance system in 2007, the proportion of flu-like cases in outpatients and emergency departments in different monitoring hospitals was analyzed by week. The virus strains were routinely isolated and identified. HA1 District gene fragments, and gene mutation analysis. Results In 2007, influenza-like illness (ILI) prevalence was 6.67% in Shenzhen. The incidence of ILI in low-age population was high. According to the analysis by city and district hospitals and community health service centers, the proportion of ILI was consistent with that of ILI Of the summer peak, the most active season in May to July; ILI outbreak than the two cases of sporadic cases. Influenza virus isolation rate was 11.63%, predominant strains were H3N2 subtype (59.5%), type B (37.0%). The evolutionary analysis of HA1 gene of H3N2 subtype influenza virus is divided into two parts. The current WHO vaccine strains and our representative strains are only close to the strains from January to April, and have genetic distance with the isolates after May, although new mutations can not be identified However, the two isolates A / sz / 9/2007 and A / sz122 / 2007 deserve high attention. The evolution analysis of HA1 gene of influenza B virus found that Yamagata was the most active in 2007. Conclusion The analysis of virus molecular variation in seasonal influenza surveillance can further identify the characteristics of the dominant strains that occur in the population and facilitate epidemiological analysis.