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，这一点从以下方面所需的巨大努力中可以得到证明： 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 疫苗接种;然而，流感疫苗的有效性取决于宿主因素和疫苗 特征，包括个体免疫应答和疫苗株之间的匹配， 在任何一年都有流行的菌株因此，疫苗有效性（VE）每年都有变化，特别是在 老年人，是一个国际争议的问题。 我们提出了一项年龄匹配的病例对照研究流感疫苗的有效性，在UPMC- 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 针对三个年龄组的门诊患者中实验室确认的流感病毒感染：6个月至18岁 我们将使用现有的症状监测，以确定何时流感样疾病 (ILI)从社区开始;招募、同意和登记门诊患者， 呼吸道疾病（MAARI）;用逆转录酶-聚合酶链反应（RT-PCR）检测以确定 病例和对照;主要使用UPMC电子健康记录（EHR）确定疫苗接种状态， 电子全州疫苗登记处（PA-SIIS）;使用 EHR（例如，Charleson共病评分）和调查方法;确定VE;并进行敏感性 分析潜在不可测量混杂因素的影响。此外，我们将确定当地 流行病学、负担和病程，并估计 实验室确认的流感，在匹兹堡超级计算中心使用基于代理的建模。 这项拟议的研究是基于我们正在进行的流感综合征监测的坚实基础， 先进的生物医学信息学使用全系统的电子病历，广泛的研究， 提高疫苗接种率，多重呼吸道病毒检测的临床背景，以及基于代理的建模， 编制疾病负担和费用的人口估计数，并有一个发表过大量文章的调查小组参与。

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.