Core_plus Option_A_C_Influenza Surveillance and Vaccine Effectiveness in a Large

摘要 流感造成重大的公共卫生负担，所需的巨大努力证明了这一点。 在最近的H1N1大流行期间预防和治疗疾病。预防流感的主要方法是 接种疫苗；然而，流感疫苗的效力因宿主因素和疫苗而异。 特征包括个体免疫反应和疫苗株与 在任何一年中都有循环菌株。因此，疫苗效力(VE)每年都不同，特别是在 这是一个引起国际争议的问题。 我们提出了一项关于UPMC流感疫苗有效性的年龄匹配病例对照研究。 卫生系统。使用病例对照方法，我们建议计算流感疫苗的有效性。 3个年龄段：6个月-18岁门诊患者预防实验室确诊流感病毒感染情况 年、19-49岁和50岁以上。我们将利用现有的症状监测来确定何时出现流感样疾病 (ILI)从社区开始；招募、同意和登记急诊就医的门诊患者 呼吸系统疾病(Maari)；用逆转录聚合酶链式反应(RT-PCR)检测 病例和对照；主要使用UPMC电子健康记录(EHR)和 全州疫苗电子登记(PA-SIIS)；使用以下方法量化潜在的混杂因素和效果修饰物 EHR(例如，查尔逊共病评分)和调查方法；确定VE；并进行敏感性 关于潜在的未测量混杂因素的影响的分析。此外，我们还将确定当地的 流感的流行病学、负担和病程，并估计以人群为基础的发病率 实验室确认的流感，使用匹兹堡超级计算中心基于代理的建模。 拟议的研究是基于我们正在进行的流感症状监测的坚实基础上， 先进的生物医学信息学使用系统范围的电子病历，广泛的基础研究 提高疫苗接种率、多重呼吸道病毒检测的临床背景和基于代理的建模以 编制人口对疾病负担和成本的估计，并涉及一支发表得很好的调查团队。

Abstract Influenza causes a major public health burden, as evidenced by the tremendous efforts required to prevent and treat disease during the recent H1N1 pandemic. The primary influenza prevention method is vaccination; however, the effectiveness of influenza vaccine varies depending upon host factors and vaccine characteristics that include individual immune response and the match between the vaccine strains and circulating strains in any given year. Therefore, vaccine effectiveness (VE) varies annually, particularly among elderly persons, and is a subject of international controversy. We propose an age-matched case-control study of the effectiveness of influenza vaccine in the UPMC- Health System. Using case-control methods, we propose to calculate the effectiveness of influenza vaccines against laboratory-confirmed influenza virus infections among outpatients in three age groups: 6 months-18 yrs, 19-49 yrs, and 50+yrs. We will use existing syndromic surveillance to identify when influenza-like illness (ILI) begins in the community; recruit, consent and enroll outpatients with for medically-attended acute respiratory illness (MAARI); test with reverse transcriptase-polymerase chain reaction (RT-PCR) to identify cases and controls; determine vaccination status using primarily the UPMC electronic health record (EHR) and the electronic statewide vaccine registry (PA-SIIS); quantify potential confounders and effect modifiers using the EHR (e.g., Charleson co-morbidity score) and survey methodology; determine VE; and conduct sensitivity analyses about the impact of potential unmeasured confounders. Additionally we will determine the local epidemiology, burden and course of influenza illness and estimate the population-based attack rate for laboratory-confirmed influenza, using agent-based modeling at the Pittsburgh Supercomputing Center. The proposed study is based on a strong foundation of our ongoing syndromic surveillance of influenza, advanced biomedical informatics using system-wide electronic medical record, broadly-based research to increase vaccination rates, clinical context of multiplex respiratory virus testing, and agent-based modeling to produce population estimates of disease burden and cost and involves a well-published team of investigators.