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解为可管理的单元来提高我们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。通过对来自不同国家的长期、空间复制、特定类型和特定年龄数据的多个备选假设进行全面比较，我们将确定免疫的性质和持续时间、重复感染的流行病学影响、亚临床免疫增强所发挥的作用以及人口统计学、季节性和人类接触网络结构的各自贡献。小儿麻痹症研究的另一个关键阶段将着眼于解决与疫苗有关的问题，重点是已知疫苗使用（口服或灭活小儿麻痹症疫苗）和免疫覆盖率的时间段。最终，我们的研究结果将产生经经验验证的传播模型，以满足登革热和脊髓灰质炎的紧急政策需求。这项工作将在很大程度上依赖于使用传播的数学模型和统计方法，从高维数据中提取信息，包括空间、年龄、血清型或气候驱动因素。因此，该项目的一个主要组成部分是开发、使用和传播将在开源公共软件中实现的新方法工具。最后，我们将汇集这一努力的智力成果，以制定最佳的、具有成本效益的免疫政策