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

描述（由申请方提供）：流感病毒是人类最易发生遗传变异的病原体之一。我们的免疫反应对病毒施加了巨大的压力，导致遗传谱系年复一年地快速更替。我们的免疫反应也包含了我们以菌株特异性抗体的形式感染的菌株的记录。虽然已经进行了一些流感病毒的前瞻性研究，但很少有人研究免疫学特征在空间或时间上的分布。这些模式提供了丰富的数据来源，用于调查人类社会互动和人口统计对流感传播的影响，这是流感病毒生态的关键决定因素。中国广东省广州和东莞的城市和农村地区提供了一个独特的机会。该项目小组将对流感的免疫状况进行研究，将个人层面的免疫状况与家庭结构、旅行行为和社交网络的数据联系起来。以及作为一个关键的人口最近出现的感染（SARS和H5N1）的研究人群也表现出重要的异质性，在社会结构，这将使我们能够调查新的和有趣的假设。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。项目小组将使用先前验证过的关于家庭结构、旅行和社会联系的调查表，分两次（间隔一年）从50个小社区的20个家庭的每个成员那里收集数据。他们还将在这两个场合收集血液样本。将针对项目开始前10年的一组代表性12种菌株，对所有血液样本进行病毒中和试验。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，流感是否在某一年跳过一些小城镇，但感染大城市的所有地理区域，儿童是否比成年人更多地感染家庭，以及我们是否可以使用过去季节的血清学数据预测某些地理区域在未来季节可能会受到更严重的打击？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人的仿真模型。除了是一种有价值的研究工具外，大型模拟模型也可能被证明是有价值的公共卫生工具，因为它们可以使用该团队在该项目中收集的血清学和社会结构数据进行准确校准。公共卫生相关性：虽然这里提出的工作将有更广泛的影响，超出了高质量的同行评议的科学文章的出版，应该记住，出版的结果本身将直接用于公共卫生政策制定者在发生流行病。本研究将提供比以往任何研究（在任何人群中）更准确的中国南方人群中突发流感大流行的可能流行病学估计。广州疾病控制中心和香港卫生防护中心等主要利益相关者将在专门为他们举行的会议上了解这些结果。

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.