Integrating immunology, epidemiology, and evolution to understand and control per

整合免疫学、流行病学和进化论来理解和控制

• 批准号: 8459378
• 负责人: Aaron A. King
• 金额: $ 31.86万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-01 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8459378
• 关键词: Accounting; Address; Affect; Age; Biology; Birth; Cells; Cessation of life; Child; Childhood; Clinical; Communicable Diseases; Comparative Study; Complex; Computer software; Country; Data; Data Set; Databases; Demography; Development; Disease Outbreaks; Economics; Encapsulated; Environmental Impact; Epidemiology; Evolution; Finland; Fruit; Future; Geographic state; Geography; Immigration; Immune; Immunity; Immunization; Immunization Programs; Immunization Schedule; Immunology; Incidence; Infant; Infection; Knowledge; Methods; Mission; Modeling; Natural Immunity; Nature; Notification; Pattern; Perception; Pertussis; Phase; Play; Policies; Population; Relative (related person); Reporting; Research; Role; Schedule; Scheme; Seasons; Secondary Immunization; Senegal; Serotyping; Statistical Methods; Stratification; Sweden; System; Testing; Thailand; Time; Uncertainty; Vaccinated; Vaccination; Vaccines; Variant; Virulent; Work; comparative; cost; cost effective; experience; improved; mathematical model; mortality; novel; open source; optimism; pathogen; programs; public health priorities; success; theories; tool; transmission process; trend; uptake

Pertussis remains a major epidemiological burden, accounting for roughly 300,000 deaths worldwide each year, most of them children. The early success of infant immunization programs in the 1950s and 1960s led to a substantial reduction in incidence and a sense of optimism that elimination of pertussis might be a achievable. Over the past two decades, however, documented outbreaks in a number of wellvaccinated populations has pointed out major gaps in our understanding of pertussis epidemiology, immunology, evolution, and control. The availability and use of various vaccines with poorly understood efficacy and immunity profiles contributes to the uncertainty. We propose to improve our understanding of these important determinants of pertussis transmission by splitting the problem into manageable units. By conducting a comprehensive, comparative testing of multiple alternative hypotheses on long-term, spatially replicated, and age-specific data from different countries in the pre-vaccine era, we will aim to pin down the duration of infection-derived immunity, the epidemiological impact of repeat infections, the role played by sub-clinical immune boosting, and the respective contributions of population demography, age-specific contacts, and seasonality. The next phase of research will aim to address the vaccine-specific aspects of the problem by focusing on countries with known vaccine usage (whole cell vs. acellular) and immunization schedules. The ultimate test of whether our understanding of pertussis has significantly advanced will be to explain an enigmatic body of data, namely the changing patterns of pertussis incidence in the US over the past thirty years. This work will rely heavily on the use of mathematical models of pertussis transmission and statistical methods for extracting information from data. A major ingredient in this project, therefore, is the development, use, and dissemination of novel methodological tools that will be implemented in open-source public software. Finally, we will bring together the intellectual fruits of this effort in order to develop optimal, cost-effective immunization policy.

百日咳仍然是一个主要的流行病负担，约占30万 全世界每年都有人死亡，其中大部分是儿童。婴儿早期的成功 20世纪50年代和60年代的免疫接种计划导致了 百日咳的发病率和消除百日咳可能是可以实现的乐观情绪。 然而，在过去的二十年里，有记录表明，在一些接种良好的疫苗中爆发了疫情 人口指出了我们对百日咳认识的主要差距 流行病学、免疫学、进化和控制。提供和使用各种不同的 效力和免疫谱知之甚少的疫苗导致了 不确定性。 我们建议提高我们对百日咳的这些重要决定因素的理解。 通过将问题分成可管理的单元进行传播。通过进行一次 对长期、长期、长期的多个备选假设进行全面、比较的测试 在疫苗之前，来自不同国家的空间复制的、特定于年龄的数据， 我们将致力于确定感染衍生免疫的持续时间，即流行病学 重复感染的影响，亚临床免疫增强所起的作用，以及 人口统计、特定年龄段的联系人和 季节性。下一阶段的研究将致力于解决疫苗特有的方面 通过关注已知疫苗使用情况的国家/地区(全细胞与 无细胞)和免疫时间表。最终的考验是我们是否理解 百日咳的研究已经有了很大的进步，将解释一个谜团的数据体， 即美国过去三十年百日咳发病率的变化模式。 这项工作将在很大程度上依赖于百日咳传播数学模型的使用 以及从数据中提取信息的统计方法。这里面的一个主要成分 因此，项目是开发、使用和传播新的方法 将在开源公共软件中实现的工具。最后，我们将带来 将这一努力的智力成果结合起来，以开发最优、成本效益高的 免疫政策。