Dynamic Inference

动态推理

• 批准号: 8796464
• 负责人: Pejman Rohani
• 金额: $ 29.95万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8796464
• 关键词: Address; Affect; Age; Antibody-Dependent Enhancement; Climate; Clinical; Communicable Diseases; Complex; Computer software; Computing Methodologies; Country; Data; Databases; Demography; Dengue; Development; Diffusion; Epidemiology; Evolution; Fruit; Genetic; Human; Immune; Immunity; Immunization; Immunology; Incidence; India; Infection; Methods; Mexico; Modeling; Nature; Oral; Phase; Play; Policies; Poliomyelitis; Population; Public Health; Reporting; Research; Role; Serologic tests; Serotyping; Statistical Methods; Stratification; Structure; System; Testing; Thailand; Time; Vaccines; Work; cost effective; improved; mathematical model; novel; open source; statistics; tool; transmission process

We propose to improve our understanding of the important determinants of dengue and polio epidemiology and immunology by splitting each problem into manageable units. By conducting a comprehensive comparison of multiple alternative hypotheses on long-term, spatially replicated, serotype-specific and age-specific data from different countries, we will pin down the nature and duration of immunity, the epidemiological impact of repeat infections, the role played by sub-clinical immune boosting, and the respective contributions of population demography, seasonality, and the structure of the human contact network. A key additional phase for polio research will aim to address the vaccine-related aspects of the problem by focusing on time periods with known vaccine usage (oral or inactivated polio vaccine) and immunization coverage. Ultimately, our findings will generate transmission models that are empirically validated for answering urgent policy needs for both dengue and polio. This work will rely heavily on the use of mathematical models of transmission and statistical methods for extracting information from high-dimensional data, encompassing space, age, serotype or climatic drivers. 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 to develop optimal, cost-effective immunization policy

我们建议通过将每个问题分为可管理的单位，以提高对登革热和脊髓灰质炎流行病学和免疫学的重要决定因素的理解。通过对不同国家的长期，空间复制，血清型特异性和特定年龄的数据进行多种替代假设进行全面比较，我们将确定免疫力的性质和持续时间，重复感染的流行病学影响，通过次临床免疫增强的作用，次级临床免疫增强的作用，以及人类人数的季节性，人类的接触，以及人类的接触性，以及人类的接触性，以及人类的联系，以及人类的联系，以及人类的联系，以及人类的联系，以及人类的联系，以及人类的联系，以及人类的联系。脊髓灰质炎研究的一个关键额外阶段将旨在通过重点关注已知疫苗使用（口服或灭活脊髓灰质炎疫苗）和免疫覆盖的时间段来解决问题的与疫苗有关的方面。最终，我们的发现将产生传输模型，这些模型经过经验验证，以解决登革热和小儿麻痹症的紧急政策需求。这项工作将在很大程度上依赖于传输和统计方法的数学模型，以从高维数据，包括空间，年龄，血清型或气候驱动器中提取信息。因此，该项目的主要成分是开发，使用和传播新型方法学工具将在开源公共软件中实施的。最后，我们将汇集这项努力的智力成果，以制定最佳，具有成本效益的免疫政策