应用三种模型对2011-2012流感病毒活动强度的预测研究

目的 建立适合的统计模型预测2011 - 2012流感流行季流感病毒活动强度.方法 采集2007年至2010年北京市流感病原学监测数据中流感高发季节(当年9月份至次年4月份)的数据做为模拟方程的基线数据,分别应用灰色模型GM(1,1)、自回归方程和二项式方程模拟流感病毒分离率的变化趋势,根据后验差比值和方程的决定系数选...     

北京市房山区2014-2015年流感病原学监测结果分析

目的 通过对北京市房山区2014-2015年流感病原学的监测结果进行分析,了解房山区流感病毒的流行特征.方法 采集房山区哨点医院流感样病例的咽拭子标本1 339份,用荧光定量PCR法检测核酸及亚型,同时进行流感病毒分离及血凝实验(HA)检测.结果 2014年1月6日-2015年12月28日,共采集1 339份流感样病例咽拭子,荧光定量PCR法检测核酸阳性数为215例(阳性率为16.06％),其中甲型H1N1流感病毒32株,甲型H3N2流感病毒107株,乙型流感病毒76株.病毒分离阳性数为148例(阳性分离率为11.05％).本年度第2-6周和第48-52周流感阳性率较高,且第2-6周以甲型H1N1和乙型流感病毒为主,第48-52周以甲型H3N2流感病毒为主.结论 房山区2014-2015年流感高发季节为第2-6周和第48-52周,上半年致病病原体以甲型HIN1流感病毒和乙型流感病毒为主,下半年以H3N2流感病毒为主,不同性别之间各亚型流感病毒的阳性率构成比无统计学差异(P＞ 0.05).     

2011-2015年北京市海淀区流感监测结果分析

目的 分析2011-2015年北京市海淀区流感病例的流行病学特征,为海淀区流感防控措施调整提供科学依据.方法 对2011-2015年北京市海淀区63家哨点医院流感样病例(Influenza-like illness,ILI)报告数据和2011年9月-2015年8月一家国家级流感监测医院病原学监测标本检测结果进行分析.结果 2011-2015年海淀区63家哨点医院共监测门急诊就诊病例49 228815例,其中ILI 362 410例(占0.74％).5年的流感样病例占门急诊就诊总数的比例(ILI％)不同(x2=1 103.798,P＜0.05).2011-2015年各年龄组中的ILI构成情况每年与其他年份比较均不相同(P ＜0.005).2011年9月-2015年8月四个流感病原学监测季,共采集ILI咽拭子样本4 183件,检出阳性标本766件,总阳性率为18.31％.2013-2014年监测季与2014-2015年监测季流感病毒核酸检测阳性率不同(x2 =6.955,P=0.008),2011-2015年各个监测季中流感病毒型别的构成情况均不相同(P＜0.05),周流感病毒核酸检测阳性率与周ILI数和周ILI％均呈正相关(r=0.579,P＜0.05;r=0.602,P＜0.05).结论 海淀区流感流行特征有一定规律,每年第50周(12月)至第二年第16周(4月)为季节性流感的发病高峰.2014-2015年流感流行较往年相比更为活跃,优势毒株为甲型H3N2型流感病毒.各年度流感优势毒株型别均不相同,具有当年度中此消彼长的流行特点.     

北京市石景山区流感监测预警效果分析

目的 建立基于流感监测数据的北京市石景山区流感监测预警体系,评价三种方法应用于流感预警的效果.方法 利用2007～2012年石景山区流感样病例百分比(ILI％)日监测数据,分别应用历史极限法、指数加权移动平均法、累积和法三种方法进行预警分析.结果 2011年9月1日-2012年8月31日,5家监测医院共报告流感样病例26651例,流感样病例百分比为2.63％,流感病毒分离率为4.35％.流感监测数据预警分析结果显示,历史极限法在2月末开始连续出现22个预警信号,至5月末结束.指数加权移动平均法和累积和法均在2012年元旦开始显示预警信号并预警持续1个月,两种方法提示预警信号部分重叠.指数加权移动平均法预警信号出现7次,累积和法C1、C2和C3预警信号分别出现5次、3次和9次.结论 综合应用指数加权移动平均法和累积和法对石景山区流感监测数据进行分析,有助于高效、准确地对流感高峰起始进行预警.     

2012—2013年北京市流感样病例监测与流感病原学监测结果的相关性分析

目的通过分析2012—2013年北京市流感流行季（2012年9月--2013年4月）流感样病例监测与流感病原学监测结果的相关性,评价北京市一级以上医疗机构和二级以上医疗机构流感样病例监测工作的适用性和有效性。方法分析北京市421家一级以上医疗机构和144家二级以上医疗机构的流感样病例监测数据,按周次分别与北京市14家医疗机构开展的流感病原学监测数据进行相关性分析和回归检验。结果一级以上和二级以上医疗机构门急诊流感样病例百分比（ILI％）与流感病毒病原学监测中病毒分离阳性率成正相关（一级医院r=0．794,P〈0．001;二级医院r=0．787,P〈0．001）。一级以上和二级以上医疗机构ILI％与流感病毒分离阳性率的回归确定系数r2分别为0．630（P〈0．001）和0．620（P〈0．001）。结论一级以上和二级以上医疗机构流感样病例中归因为流感病毒感染的比例基本一致,从成本效益分析角度考虑,北京市利用144家二级以上医疗机构开展流感样病例监测已经可以满足对疾病监测的需要,比扩展到421家一级以上医疗机构具有更好的成本效益比。     

应用Serfling回归模型估计北京市流行性感冒相关超额流感样病例数

目的 构建Serfling回归模型,估计北京市2007-2011年流行性感冒(简称流感)相关的超额流感样病例数.方法 使用“北京市医疗机构传染病监测预警系统”中二级以上医院流感样病例周数据,拟合Seffling回归模型,估计超额流感样病例数.结果 2007/2008、2008/2009、2009/2010和2010/2011年度各有6、3、19和8个流行周,包括有2007/2008年度第524周、2008/2009年度第51-1周、2009/2010年度第37-38周和第42-6周、2010/2011年度第48-3周.2007/2008、2008/2009、2009/2010和2010/2011年度流行周的超额流感样病例数分别为41905(95％ CI:21541～62265)、17936(95％ CI:7747～28124)、226150(95％ CI:162531 ～289768)和40083(95％ CI:13013～67154)人,占同期全部流感样病例数的44.75％ (95％ CI:23.00 ～ 66.49％)、37.93％ (95％ CI:16.38～58.47％)、50.01％ (95％ CI:35.94 ～64.08％)和27.89％ (95％ CI:8.05 ～46.73％).结论 应用本模型估算,北京市每年在流感季节性流行期间和大流行期间,流感病毒均可造成数万至数十万的超额流感样病例和超额门诊就诊量.     

北京市2015-2020年流感流行季流感样病例和流感病原学分析

目的了解2015-2020年流感流行季北京市流感流行特征。方法使用北京市2015-2020年流感样病例(influenza-like illness,ILI)和流感病原学监测数据,分析流感流行趋势和流感病毒流行特征。结果2015年第27周至2020年第26周共涉及5个流感流行季,流感样病例百分比(percentage of influenza-like illness,ILI%)为1.58%。共检测ILI标本96892件,流感病毒核酸阳性率为16.32%,其中A(H3N2)亚型6474件(40.89%)、甲型H1N14410件(27.86%)、乙型Victoria系3290件(20.78%)、乙型Yamagata系1597件(10.09%)。ILI周报告数、ILI%与流感病毒阳性率变化趋势基本一致(r=0.796,P<0.001;r=0.808,P<0.001)。2017-2018年和2018-2019年流行季活跃期较长。2017-2018、2018-2019年流行季ILI周报告数较高(49628人次和71555人次),核酸阳性率峰值较高(58.51%和57.08%)。结论2015-2020年北京市流感流行符合北半球流行特征,其中2017-2018和2018-2019流行季活跃期较长、流行水平较高,且各流行季优势毒株不同。     

CUSUM模型在北京市流感流行起始预警中的应用

目的 应用CUSUM模型探讨北京市流感流行起始时间.方法 应用CUSUM模型,对北京市2014年至2016年流感监测数据进行预警分析,并与流感病原学“金标准”判断流行高峰和流感流行预警基线的时间进行比较.结果 2014-2015监测年,CUSUM模型在2014年第46周发出预警,较“金标准”流行起始时间提起前1周,较ILI％预警基线提前3周.2015-2016监测年,CUSUM模型在2015年第46周发出预警,较“金标准”流行起始时间提前8周,较ILI％预警基线提前7周.结论 应用CUSUM模型对北京市流感监测数据进行分析,可以及时预警流感流行起始时间.     

天津市红桥区2012年～2014年哨点医院流感样病例流行情况分析

目的 对2012年～2014年天津市红桥区流感监测结果进行分析,为流感防控工作提供科学依据.方法 采集国家级哨点医院门诊流感样病例的咽拭子,采样对象为发病3d之内未使用抗病毒类药物的流感样病例,采集咽拭子,以荧光PCR方法检测病毒核酸,用MDCK进行病毒分离培养.所获得数据采用EXCEL和SPSS软件进行处理,不同样本类型的阳性率的比较使用x2检验.结果 对974份流感样病例咽拭子进行核酸检测,检测出流感病毒核酸阳性40份,检出率为12.01％,其中56份新甲H1型,37份季节性H3型,12份乙型未分型、12份乙型Yamagata型.按年度分析,2012年～2014年流感病毒检出率依次为12.12％和11.96％.结论 天津市红桥区2012年～2013年以季节性H3流感流行为主;2013年～2014年流感活动以新甲H1型流感流行为主.     

应用SEIR模型预测2009年甲型H1N1流感流行趋势

目的 探讨SEIR模型预测甲型H1N1流感流行趋势的功效.方法 利用国庆前北京市流感样病例数、流感样病例中甲型H1N1流感阳性率及二级以上医院流感样病例就诊率等参数估算甲型H1N1流感实际感染人数,基于传染病传播动力学,建立SEIR模型,对国庆后甲型H1N1流感的流行趋势及高峰达到时间进行预测,与甲型H1N1流感病原学...     

2012-2014年河北省流感暴发疫情流行病学特征分析

目的 探讨2012-2014年河北省流感暴发疫情的流行特征,为河北省流感的防控提供科学依据.方法 收集2012-2014年河北省突发公共卫生事件管理信息系统及流感监测信息系统中流感暴发疫情资料,分析流感暴发疫情的流行特征.结果 2012-2014年河北省共报告16起流感暴发疫情,累计发病1176例;疫情分布于5个地市,其中廊坊报告暴发疫情数最多(6起).暴发时间主要集中在每年的11月至次年2月,占87.50％(14/16).除1起发生在医院外,其余15起均发生在学校,以中小学校为主(13起,81.25％);地市市区(城市)11起(68.75％).引起流感暴发疫情的流感病毒主要为季节性H3N2流感病毒.流感暴发疫情首例发病到接报时间与疫情持续时间成正相关(r=0.913,P＜0.001).结论 河北省流感暴发疫情主要集中在冬季,以局部暴发为主,中小学校是流感暴发疫情的高发场所,加强监测、尽早采取措施是控制流感暴发疫情的关键.     

Comparison of the effects of acute influenza infection and Influenza vaccination on HIV viral load and CD4 cell counts.

PURPOSE: Influenza vaccination is recommended for HIV-infected patients, although the efficacy is not clear. Prior studies have yielded differing results with regard to the effects of influenza vaccination on HIV viral load and CD4 cell counts. The effects of acute influenza on HIV viral replication and CD4 cell counts have not been well described. We sought to assess the effect of influenza infection and vaccination on HIV viral load and CD4 cell counts. SUBJECTS AND METHODS: All cases of influenza occurring in HIV-infected individuals over 3 years at a large county hospital were reviewed. For the year 1997-1998, data on all HIV clinic patients who were vaccinated for influenza were recorded prospectively. In order to assess the effects of influenza infection (Group I) and vaccination (Group II) on HIV viral load and CD4 cell counts, values from before and after influenza infection or vaccination were compared to each other and to a matched control group not vaccinated and without influenza infection (Group III). RESULTS: Forty-three cases of influenza were diagnosed. Pre- and post-influenza viral load in Group I was not significantly different: 3.34 versus 3.49 log copies/ml (P=0.36). Viral load was unchanged in 22 of 37 patients, increased in ten patients and decreased in five patients. Similarly, pre- and post-vaccination viral load in Group II was not significantly different: 3.52 versus 3.66 log copies/ml (P=0.12). Thirty-four of 47 patients who received influenza vaccine had no significant change in viral load-viral load increased in ten patients and decreased in three patients. No significant CD4 cell count changes were noted following influenza infection or vaccination. In contrast, Group III patients experienced a small decline in viral load from 4.23 to 3.39 log copies/ml, P<0.05, while there was a trend towards an increase in CD4 cell counts (P=0.06). CONCLUSIONS: Following influenza infection or vaccination, most patients did not have a significant increase in HIV viral load or decrease in CD4 cell count.     

Hospital‐based influenza surveillance in Korea: Hospital‐based influenza morbidity and mortality study group

Influenza epidemics occur annually with variations in size and severity. Hospital‐based Influenza Morbidity & Mortality was established to monitor influenza epidemics and their severity, which is composed of two surveillance systems: emergency room‐based and inpatient‐based surveillance. Regarding emergency room‐based surveillance, influenza‐like illness index (influenza‐like illness cases per 1,000 emergency room‐visiting subjects), number of laboratory‐confirmed cases and the distribution of influenza types were estimated weekly. Inpatient‐based surveillance included monitoring for hospitalization, complications, and mortality. The emergency room influenza‐like illness index correlated well with the number of laboratory‐confirmed influenza cases, and showed a bimodal peak at Week 4 (179.2/1,000 emergency room visits) and Weeks 13‐14 (169.6/1,000 emergency room visits) of 2012. Influenza A was the predominant strain during the first epidemic peak, while influenza B was isolated exclusively during the second peak. In 2011–2012 season, the mean admission rate of emergency room‐visiting patients with influenza‐like illness was 16.3% without any increase over the epidemic period. Among the hospitalized patients with influenza, 33.6% (41 out of 122 patients) were accompanied by complications, and pneumonia (28.7%, 35 out of 122 patients) was the most common. Most fatal cases were caused by influenza A (96.2%) after the first epidemic peak. In conclusion, Hospital‐based Influenza Morbidity & Mortality was effective for monitoring the trends in circulating influenza activity concurrently with its severity. In the 2011–2012 season, the influenza epidemic persisted for a ≥5‐month period, with a bimodal peak of influenza A and B in sequence. Overall, influenza A was more severe than influenza B. J. Med. Virol. 85:910–917, 2013. © 2013 Wiley Periodicals, Inc.     

2012-2015年北京市顺义区流感监测结果分析

目的 分析顺义区2012-2015年流感病毒核酸的监测结果,掌握流感流行规律.方法 用实时定量PCR法对采集的流感样病例标本进行核酸检测.结果 2012年9月-2013年8月共检测流感样病例标本1040份,核酸检测阳性标本95例,阳性率为9.13％,高峰出现在12月-次年1月,主要以H3N2和新甲型H1N1流感病毒为主;2013年9月-2014年8月共检测流感样病例标本889份,核酸阳性标本138例,阳性率为15.52％,流行高峰出现在1-3月,以H3N2和甲型H1N1流感、乙型流感病毒为主.在2014年9月-2015年8月共检测流感样病例标本798份,核酸阳性标本151例,阳性率为18.92％,流行高峰出现在2014年11月-2015年4月份,以H3N2和乙型流感为主.检测阳性率最高的为60岁以上人群,其次是5-14岁组.结论 2012-2015年,顺义区新甲型H1N1亚型、H3N2亚型、乙型流感均有流行,且各年度优势毒株不一.     

Genetic diversity of influenza A(H3N2) viruses in Northern Cameroon during the 2014-2016 influenza seasons

In Cameroon, genome characterization of influenza virus has been performed only in the Southern regions meanwhile genetic diversity of this virus varies with respect to locality. The Northern region characterized by a Sudan tropical climate might have distinct genetic characterization. This study aimed to better understand the genetic diversity of influenza A(H3N2) viruses circulating in Northern Cameroon. Sequences of three gene segments (hemagglutinin (HA), neuraminidase (NA) and matrix (M) genes) were obtained from 16 A(H3N2) virus strains collected during the 2014 to 2016 influenza seasons in Garoua. The HA gene segments were analysed with respect to reference strains while the NA and M gene was analysed for reported genetic markers of resistance to antivirals. Analysis of the HA sequences revealed that majority of the virus strains grouped together with the 2016-2017 vaccine strain (3C.2a-A/Hong Kong/4801/2014) while 3/5 (60%) of the 2015 viral strains grouped together with the 2015-2016 vaccine strain 3C.3a-A/Switzerland/9715293/2013. Within clade 3C.2a, Northern Cameroon sequences mostly grouped in sub-clade A3 (10/16). Analysis of the coding regions of the NA and M genes showed that none had genetic markers of resistance to neuraminidase inhibitors but all strains possessed the S31N substitution of resistance to amantadine. Due to some discrepancies observed in this region with respect to the Southern regions of Cameroon, there is necessity of including all regions within a country in the sentinel surveillance of influenza. These data will enable to track changes in influenza viruses in Cameroon.     

Statistical determination of endotoxin content in influenza virus vaccine by the limulus amoebocyte lysate test.

To determine laboratory-to-laboratory variability of the limulus amoebocyte lysate (LAL) test for evaluating endotoxin content in influenza virus vaccine, a collaborative study was designed. Participants were six influenza virus vaccine manufacturers and the Bureau of Biologics (BoB). Lysate lot 116, Reference Influenza Virus Vaccine for Endotoxin Assay E-1, and four test vaccines having different ratios of LAL activity relative to reference E-1 were supplied by the BoB. Each laboratory used its normal test procedure. All vaccines were coded. One pair (reference and test) of vaccines per day was tested for 4 days a week over a 4-week period. All data were analyzed at the BoB. The degree of variability experienced by testing laboratories was estimated by the study. This estimate did not conflict with experience gained from previous routine testing in any of the participating laboratories. A statistical approach to the evaluation of LAL data from testing influenza virus vaccine for endotoxin content was developed based upon the overall variation obtained from the collaborative study.     

不同亚型禽流感病毒红细胞凝集特性分析

目的了解不同亚型禽流感病毒与不同动物来源红细胞的凝集特性,为流感环境样本监测工作选择更适宜的检测用红细胞。方法选取2009-2016年我国禽流感环境监测中分离到的不同亚型的禽流感毒株,采用红细胞凝集试验,选用5种动物红细胞(鸡、火鸡、豚鼠、马和绵羊)进行检测;应用流式细胞仪检测不同动物红细胞表面唾液酸受体的表达及类型,通过氨基酸序列分析病毒血凝素蛋白受体结合区(receptor binding domain,RBD)的特征。结果本研究共检测了14种亚型的28株禽流感病毒。结果显示所有毒株均能与火鸡和豚鼠红细胞发生凝集,其余红细胞均出现不能与某些毒株产生凝集的现象;其中1株H9N2(A/环境/安徽/43762/2015)毒株与鸡红细胞不产生凝集反应;1株H1N1(A/环境/山东/76972/2014)和2株H9N2(A/环境/重庆/79449/2014和A/环境/安徽/43762/2015)毒株与马红细胞不产生凝集反应;2株H9N2(A/环境/重庆/79449/2014和A/环境/安徽/43762/2015)和2株H13N8(A/环境/青海湖/166/2012和A/环境/青海湖/13/2012)毒株与绵羊红细胞不产生凝集反应。流式检测结果显示在火鸡、鸡和豚鼠红细胞表面可检测到两种类型唾液酸受体α2,3和α2,6,但两种受体表达比例不同;马和绵羊红细胞表面唾液酸受体只检测到表达α2,3。序列分析提示病毒RBD关键区域的氨基酸替换可能是影响病毒红细胞结合特性的重要因素。结论在禽流感病毒检测中,火鸡和豚鼠红细胞在红细胞凝集试验中敏感性最好。不同来源的红细胞其受体表达及类型会显著影响不同亚型禽流感病毒的凝集反应,同时RBD关键区域的氨基酸变化也会影响病毒与不同红细胞的结合。     

Cultural influenza vaccines

Recent achievements in development of influenza vaccines using long-term cell cultures MDSK or Vero are reviewed. Cell cultures were grown in bioreactors (fermenters) filled with microcarriers using serum-free culture media. Inactivated cultural influenza vaccines were clinically tested in many countries. The results of these trials showed that cultural influenza vaccines are as safe and immunogenic as conventional vaccines prepared using chicken embryos. It is emphasized that cultural influenza vaccines prepared using serum-free culture media have a number of advantages over embryonic influenza vaccines: standard preparation technology, intactness of all hemagglutinin antigen domains, absence of protein allergens and possible viral contamination inherent in chicken embryos and blood serum, and possibility of easy intensification of vaccine production in case of influenza pandemic. Taking into consideration these advantages, it may be suggested that cultural influenza vaccines will soon be widely used in medical practice.