Study Designs for Estimating the Effectiveness of Vaccination Against Influenza

评估流感疫苗有效性的研究设计

• 批准号: 8671999
• 负责人: Michael J Haber
• 金额: $ 31.2万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-03-01 至 2017-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8671999
• 关键词: Accounting; Age-Months; Attention; Caring; Characteristics; Cohort Studies; Communities; Controlled Study; Data; Disease; Disease Outbreaks; Dose; Effectiveness; Ethics; Evaluation; Failure; Goals; Guidelines; Health; Household; Individual; Influenza; Influenza vaccination; Laboratories; Life; Measures; Medical; Methods; Modeling; Monitor; Morbidity - disease rate; Observational Study; Participant; Patients; Persons; Population; Process; Randomized Clinical Trials; Randomized Controlled Clinical Trials; Reporting; Research Design; Research Personnel; Research Project Grants; Resort; Risk Factors; Sample Size; Seasons; Selection Bias; Source; Specific qualifier value; Structure; Study Subject; Symptoms; Testing; Vaccination; Vaccines; authority; base; case control; cohort; design; expectation; flu transmission; improved; influenza outbreak; influenza virus vaccine; influenzavirus; models and simulation; mortality; novel vaccines; pandemic influenza; programs; public health relevance; seasonal influenza; simulation; vaccine effectiveness

DESCRIPTION (provided by applicant): Vaccination is the most effective method to reduce influenza-associated morbidity and mortality. Accurate annual assessment of the effectiveness of influenza vaccines is very important for (a) understanding the relationship between antigenic match and mismatch and vaccine effectiveness, (b) evaluation of vaccination programs and strategies in terms of individual and population-wide benefits, (c) identifying risk factors for vaccine failure to assist in determining strategies to improve effectiveness in such groups (e.g., higher doses). As influenza vaccination is now recommended in the U.S. for almost everybody above 6 months of age, randomized clinical trials to evaluate influenza vaccine effectiveness (IVE) are no longer ethical, and health authorities have to rely on observational studies that are known to produce biased IVE estimates. The main objectives of the proposed research project are to (a) evaluate and compare existing observational study designs for estimating IVE, and (b) develop new study designs that are expected to result in improved IVE estimates. We will pay special attention to the test-negative-controls (TNC) study design, where patients with an influenza-like-illness (ILI) who test negative for influenza infection serve as controls. This simpe study design is now the most commonly used design in the U.S. and world-wide, though its bias and precision have not yet been fully evaluated. We propose to improve this design by combining it with a smaller cohort study where participants are constantly monitored and are tested for influenza infection once they develop an ILI. We also plan to develop guidelines for determining sample sizes for IVE studies and to explore the accuracy of mid-season (interim) estimates of IVE. To achieve these goals we will develop a detailed agent-based stochastic simulation model to (a) generate outbreaks of influenza infection/illness and cases of non-influenza ILI in a structured population, and (b) use data from these outbreaks to conduct observational IVE studies following specified study designs. Multiple simulations under fixed settings will be conducted to evaluate bias and precision of estimates from different study designs. This is the first project to evaluate IVE study designs from stochastic simulations accounting for various underlying contact processes, influenza transmission dynamics and other real-life factors. Results of the proposed research project will guide investigators conducting IVE studies in selecting the most appropriate study design in terms of reducing bias and improving precision of resulting estimates. This will help produce more robust estimates of vaccine effectiveness, which are essential for developing new and improved vaccines, for making the public aware of the benefits of influenza vaccination, and for targeting sub- populations in which IVE is low. While parameters of our model will be based on data from seasonal influenza outbreaks, we believe that our results will also be useful when designing studies to evaluate the effectiveness of vaccines against possible influenza pandemics. 1

描述（由申请人提供）：疫苗接种是降低与流感相关的发病率和死亡率的最有效方法。对（a）了解抗原匹配与不匹配和疫苗有效性之间的关系的准确年度评估非常重要，（b）评估疫苗接种计划和个人和人口范围的福利方面的疫苗接种计划和策略，（C）（C）（c）疫苗失败以确定这种策略以确定策略以确定此类组中的有效性（E.G.G.G.G.G）。由于现在在美国推荐的几乎每个6个月以上的每个人都推荐了流感疫苗，因此评估流感疫苗有效性（IVE）的随机临床试验不再是道德的，卫生当局必须依靠已知的观察性研究来产生偏见的IVE估计。 拟议的研究项目的主要目标是（a）评估和比较现有的观察性研究设计以估算IVE，以及（b）开发新的研究设计，这些设计有望改善IVE估计。我们将特别注意测试阴性控制（TNC）研究设计，其中患有类似流感的易碎度（ILI）的患者对流感感染进行阴性测试作为对照。这种Simpe研究设计现在是美国和全球最常用的设计，尽管尚未对其偏见和精度进行全面评估。我们建议通过将其与较小的队列研究结合起来来改进该设计，在该研究中，参与者一旦开发ILI，就会不断监测参与者的流感感染。我们还计划制定用于确定IVE研究样本量的准则，并探讨IVE季节中期（临时）估计的准确性。 为了实现这些目标，我们将开发一个基于代理的随机模拟模型，以（a）在结构化的人群中产生流感感染/疾病的暴发和非影响力的ILI病例，以及（b）使用这些疫情的数据来进行指定研究设计后进行观察性研究。将在固定设置下进行多次模拟，以评估不同研究设计的估计值的偏差和精度。这是第一个评估来自随机模拟的IVE研究设计的项目，这些项目涉及各种潜在的接触过程，流感传播动态和其他现实生活中的因素。 拟议的研究项目的结果将指导研究人员在选择最合适的研究设计方面，以减少偏见和提高结果估计的精度。这将有助于对疫苗有效性产生更强大的估计，这对于开发新的和改进的疫苗至关重要，以使公众意识到流感疫苗接种的好处，以及针对IVE较低的亚种群的目标。虽然我们的模型参数将基于季节性流感爆发的数据，但我们认为，在设计研究以评估疫苗对可能的流感流感大流感的有效性时，我们的结果也将很有用。 1