Ecology of Infectious Diseases (EID)-Immune Landscapes of Human Influenza in Hous

传染病生态学（EID）-人类流感在室内的免疫景观

• 批准号: 7687542
• 负责人: Derek A Cummings
• 金额: $ 50万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2012-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7687542
• 关键词: Adult; Age; Antibodies; Area; Arts; Behavior; Biological Assay; Blood specimen; Censuses; Centers for Disease Control and Prevention (U.S.); Child; China; Cities; Code; Communicable Diseases; Communities; Complex; Data; Data Sources; Ecology; Epidemiology; Equation; Event; Exhibits; Future; Genetic; Hand' s disease; Health Policy; Health protection; Heterogeneity; Hong Kong; Household; Human; Immune; Immune response; Immunity; Incidence; Individual; Infection; Influenza; Influenza A Virus, H1N1 Subtype; Influenza A Virus, H5N1 Subtype; Intention; Investigation; Link; Location; Measures; Methods; Modeling; Organism; Pattern; Peer Review; Policy Maker; Population; Population Density; Population Study; Postdoctoral Fellow; Prospective Studies; Province; Public Health; Publications; Publishing; Questionnaires; Recruitment Activity; Research; Research Personnel; Resources; Rural; Sampling; Seasons; Serologic tests; Serological; Serum; Severe Acute Respiratory Syndrome; Skin; Social Environment; Social Interaction; Social Network; Socioeconomic Status; Source Code; Structure; Surveys; Techniques; Testing; Theoretical model; Time; Training; Travel; Viral; Virus; Work; base; behavior influence; cost; demographics; diaries; disease transmission; flu transmission; follow-up; graduate student; influenzavirus; interest; mathematical model; meetings; member; models and simulation; novel; pandemic disease; pandemic influenza; pathogen; pressure; public health relevance; repository; rural area; seasonal influenza; simulation; social; tool; transmission process; urban area

DESCRIPTION (provided by applicant): The influenza virus is one of the most genetically mutable pathogens of humans. Our immune response places substantial pressure on the virus, resulting in rapid turnover of genetic lineages from year to year. Our immune response also contains a record of the strains we have been infected with in the form of strain-specific antibodies. Though some prospective studies of influenza viruses have been conducted, little has been done to investigate the distribution of immunological profiles in space or time. These patterns present a rich data source for investigation of the impact of human social interactions and demographics on influenza transmission, key determinants of the ecology of the influenza virus. The urban and rural areas in and near Guangzhou and Dongguan in Guangdong province, China, provide a unique opportunity. The project team will conduct a study of the immune landscape of influenza, linking that immune landscape, at the individual-level, to data on household structure, travel behavior and social networks. As well as being a key human population for recent emergent infections (SARS and H5N1) the study population also exhibits important heterogeneities in social structure which will allow us to investigate novel and interesting hypotheses. For example, both population density and average socio-economic status vary massively over relatively small distances. The project team will use previously-validated questionnaires on household structure, travel and social contacts to gather data from each member of 20 households in 50 small communities on two separate occasions (one year apart). They will also gather blood samples on both occasions. Viral neutralization assays will be conducted for all blood samples against a representative set of 12 strains from the 10 years prior to the start of the project. These social structure and serological data will be used alongside mathematical models of infectious disease transmission to help answer fundamental questions about how human behavior influences disease transmission. For example, does influenza skip some small towns on a given year but infect all geographical areas of large cities, do children bring much more infection into households than adults, and can we predict that some geographical areas might be harder hit in future seasons using serological data from past seasons? The mathematical models used to help answer these questions will vary from simple differential equation models to large-scale individual-based simulation models. As well as being a valuable research tool, large simulation models may prove to be valuable public health tools when they can be accurately calibrated using serology and social structure data of the kind the team will gather in this project. PUBLIC HEALTH RELEVANCE: Although the work proposed here will have broader impact beyond the publication of high quality peer-reviewed scientific articles, it should be remembered that the published results themselves will be of direct use to public health policy makers in the event of a pandemic. This study will provide more accurate estimates of the likely epidemiology of an emergent pandemic of influenza in the human population of southern China than any previous studies (in any population). Key stakeholders such as the Center for Disease Control in Guangzhou and the Center for Health Protection in Hong Kong will be made aware of these results during meetings held specifically for them.

描述（由申请人提供）：流感病毒是人类遗传性最大的病原体之一。我们的免疫反应对病毒施加了巨大压力，导致遗传谱系每年迅速转移。我们的免疫反应还包含以应变特异性抗体形式感染菌株的记录。尽管已经对流感病毒进行了一些前瞻性研究，但几乎没有采取任何研究来研究免疫学特征在时空或时间上的分布。这些模式为研究人类社会互动和人口统计学对流感传播的影响的影响提供了丰富的数据源，这是流感病毒生态学的关键决定因素。中国广东省的广州和东方附近的城市和农村地区提供了独特的机会。该项目团队将对流感的免疫景观进行研究，将免疫景观（个人级别的免疫景观）与家庭结构，旅行行为和社交网络的数据联系起来。除了成为最近新兴感染（SARS和H5N1）的关键人口外，研究人群还表现出社会结构中重要的异质性，这将使我们能够研究新颖而有趣的假设。例如，人口密度和平均社会经济地位在相对较小的距离上差异很大。项目团队将在家庭结构，旅行和社会联系方面使用先前验证的问卷，以两次不同的场合（相距一年），从50个小社区的每个家庭中的每个家庭中收集数据。他们还将两次收集血液样本。从项目开始之前的10年中，将对所有血液样本对所有血液样本进行病毒中和测定。这些社会结构和血清学数据将与传染病传播的数学模型一起使用，以帮助回答有关人类行为如何影响疾病传播的基本问题。例如，流感在给定的一年中跳过了一些小镇，但是感染了大城市的所有地理区域，孩子是否比成年人会给家庭带来更多的感染，我们是否可以预测，在未来季节，在将来的季节中，某些地理区域可能会受到更大的打击？用于帮助回答这些问题的数学模型将从简单的微分方程模型到大规模的基于个体的仿真模型不同。除了成为有价值的研究工具外，大型仿真模型可能被证明是有价值的公共卫生工具，即使用团队将在该项目中收集的血清学和社会结构数据对其进行准确校准。公共卫生相关性：尽管此处提出的工作将在出版高质量的同行评审科学文章之外产生更大的影响，但应记住，出版的结果本身将直接用于公共卫生政策制定者，但事件发生了大流行。这项研究将为中国南方人口中出现的流感大流行病的可能流行病学提供比以前的任何研究（在任何人群中）更准确的估计。关键利益相关者，例如广州疾病控制中心和香港的卫生保护中心，将在专门为他们举行的会议期间了解这些结果。