Comparative Effectiveness of Mitigation Strategies for Pandemic Influenza

项目摘要/摘要 流感大流行是21世纪最重要的国际公共卫生挑战之一。 在过去的400年里，发生了11次可能的大流行和3次可能的大流行。四月， 2009年墨西哥城爆发的一种新的甲型H1N1流感病毒株表明，感染可以 在全球范围内几天内传播，并在怀孕的年轻人中造成不成比例的发病率和死亡率 女性和少数族裔。2009年甲型H1N1流感大流行的定义是其传染性和病例- 死亡比例为“轻微”的大流行；世卫组织估计，更严重的大流行可能会导致 数亿人死亡，并使医疗保健能力不堪重负。即使在这场温和的大流行期间， 医院和重症监护室在传播高峰期接近或处于高峰状态。公共卫生 官员们的决策支持技术有限，无法计划或防止未来医疗保健使用率激增 流感大流行。尽管对目前的大流行采取了适当的公共卫生应对措施，但有几个 甲型流感病毒仍然是大流行的威胁。下一次流感大流行的确切时间尚不确定， 但毫无疑问，另一场危机将会发生。 在过去的三年里，我培养了成本效益分析和传染病方面的技能 通过设计流感疾病传播模型来比较效率和成本- 替代大流行缓解战略的有效性。我的几个模型参数基于 假设或来自季节性流感流行或20世纪大流行的数据，我的模型是有限的 与大流行性流感在城市内的传播有关。我想提高模型的精确度 参数，并扩大其地理范围，以比较医疗保健的有效性 利用激增准备战略，并为大流行医疗保健决策支持提供信息。要做到这一点，我 需要在大型数据库分析和多变量统计建模方面培养更多技能 在一支经验丰富的多学科团队的指导下完成课程和项目 导师和顾问。结合我现有的方法背景，这些技能将使我 作为传染病卫生政策的独立调查员进行研究。 2009年甲型H1N1流感大流行发生在一个医疗数据库收集先进的时代， 为我提供了一个独特的机会，通过以下方式实现所有这些目标：(1)衡量与流感有关的 大流行期间的医疗费用和利用情况；(2)将目标1的住院时间结果纳入 预测流感医疗服务利用高峰时间分布的多变量分析；(3)输入 将AIMS 1和AIMS 2的结果添加到我的大流行流感传播模型中，以比较其有效性和 针对一系列流行病严重程度的替代增援准备战略的成本效益；以及(4) 通过疾病预防控制中心传播目标1、目标2和目标3的结果，以更新医疗决策支持技术。

PROJECT SUMMARY / ABSTRACT Influenza pandemics are among the foremost international public health challenges of the 21st century. Eleven probable and three possible pandemics have occurred in the past four-hundred years. The April, 2009 outbreak of a novel strain of influenza A (H1N1) in Mexico City demonstrated that infection can be transmitted globally in days and cause disproportionate morbidity and mortality in young adults, pregnant women, and minorities. The 2009 (H1N1) Pandemic has been defined by its transmissibility and case- fatality proportion as a "mild" pandemic; the WHO estimates that a more severe pandemic could cause hundreds of millions of deaths, and overwhelm healthcare capacity. Even during this mild pandemic, hospitals and ICUs were operating near or at surge capacity during peaks of transmission. Public health officials have limited decision support technology to plan for or prevent healthcare utilization surge in future influenza pandemics. Despite an appropriate public health response to the ongoing pandemic, several influenza A viruses remain pandemic threats. The exact timing of the next influenza pandemic is uncertain, but there is no doubt that another one will occur. Over the past three years, I have developed skills in cost-effectiveness analysis and infectious disease modeling by designing an influenza disease transmission model to compare the effectiveness and cost- effectiveness of alternative pandemic mitigation strategies. Several of my model parameters are based on assumptions or data from seasonal influenza epidemics or 20th century pandemics, and my model is limited to the spread of pandemic influenza within a city. I would like to improve the accuracy of the model parameters and expand its geographical scope in order to compare the effectiveness of healthcare utilization surge preparation strategies and to inform pandemic healthcare decision support. To do so, I need to develop additional skills in large database analysis and multivariable statistical modeling by completing coursework and projects under the guidance of an experienced, multi-disciplinary team of mentors and advisors. Combined with my existing methodological background, these skills will enable me to perform research as an independent investigator in infectious disease health policy. The 2009 (H1N1) Pandemic, occurring in an era with advanced healthcare database collection, has provided a unique opportunity for me to meet all of these objectives by: (1) Measuring influenza-related healthcare costs and utilization during a pandemic; (2) Incorporating length-of-stay results from Aim 1 into multivariate analyses to predict the temporal spread of peak influenza healthcare utilization; (3) Inputting results of Aims 1 and 2 into my pandemic influenza transmission model to compare the effectiveness and cost-effectiveness of alternative surge preparation strategies over a range of pandemic severities; and (4) Disseminating results of Aims 1, 2, and 3 through CDC to update healthcare decision support technology.