MIDAS Center for Communicable Disease Dynamics

MIDAS 传染病动态中心

• 批准号: 8747003
• 负责人: MARC LIPSITCH
• 金额: $ 227.99万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8747003
• 关键词: Academia; Accounting; Achievement; Address; Antibiotic Resistance; Biological; Car Phone; Collaborations; Communicable Diseases; Computer Simulation; Data; Data Sources; Development; Discipline; Dose; Drug resistance; Education and Outreach; Emerging Communicable Diseases; Epidemiology; Evolution; Foundations; Funding; Genetic; Genetic Recombination; Genomics; Gonorrhea; Health; Heterogeneity; Infection; Intervention; Journalism; Knowledge; Malaria; Maps; Measures; Mediating; Methods; Modeling; Peer Review; Pneumococcal Infections; Policies; Population; Prevalence; Public Health; Public Health Schools; Publications; Readiness; Recruitment Activity; Research; Research Activity; Research Infrastructure; Risk; Route; Severities; Source; Statistical Models; Testing; Time; Training; Tuberculosis; Vaccines; Virus; Work; disease transmission; mathematical model; next generation; pathogen; public health emergency; resistance mechanism; response; software development; theories; transmission process

DESCRIPTION (provided by applicant): We propose a competing renewal of the MIDAS Center for Communicable Disease Dynamics (CCDD) at Harvard School of Public Health. Building on a four-year record of over 170 peer-reviewed publications and significant achievements in outreaching and education, we propose a multipronged approach to extend the activities of this Center of Excellence into the next funding period. Combining expertise in mathematical and statistical modeling of infection with related disciplines, we will undertake methodologic development and application to a range of public health problems. Project I. Pathogen Genomics and Evolution develops computational and statistical models to infer local and global transmission and clustering of infections, antigenic change by recombination, and evolution under vaccine-mediated selection. Project II. New Analytic Methods for New Data Sources develops and tests statistical approaches for interpreting participatory surveillance and mobile phone data for parameterization and testing of transmission-dynamic models, uses hydrological modeling to build risk maps for malaria, and develops the statistical theory of negative controls. Project III. Accounting for Measured and Unmeasured Heterogeneity in Host Populations proposes a variety of studies to assess the contribution of host heterogeneity to model parameter estimation for infections with different transmission routes and creates models incorporating two key sources of such heterogeneity: virus interference and dose-response relationships. Project IV. Understanding and Controlling Antibiotic Resistance studies drug resistance in gonorrhea, tuberculosis, and pneumococcal infections, applying methods from earlier projects to understand the genetic and selective origins of resistance and the mechanisms underlying observed heterogeneities in its prevalence. Project V. Collaborative Modeling for Assessment and Optimization in Public Health proposes work with public health partners to address two key aspects of their work ~ burden/severity estimation and optimization of interventions - using a range of modeling approaches. Software development and sharing and Policy Studies are integral parts of our research activities. In Outreach and Education we propose an ambitious set of initiatives aimed at pipeline and recruiting, training the next generation of modelers, and engaging colleagues in policy, academia and journalism.

描述（由申请人提供）：我们建议在哈佛公共卫生学院的MIDAS中心传染病动力学（CCDD）的竞争性更新。基于四年来超过170篇同行评审的出版物以及在外展和教育方面取得的重大成就，我们提出了一个多管齐下的方法，将这个卓越中心的活动扩展到下一个资助期。结合感染的数学和统计建模与相关学科的专业知识，我们将进行方法的开发和应用到一系列公共卫生问题。项目一病原体基因组学和进化开发计算和统计模型，以推断局部和全球的传播和感染的聚集，通过重组的抗原变化，以及疫苗介导的选择下的进化。项目二.新数据源的新分析方法开发和测试统计方法，用于解释参与式监测和移动的电话数据，用于传播动态模型的参数化和测试，使用水文建模来构建疟疾风险图，并开发阴性对照的统计理论。项目三.解释宿主群体中可测量和不可测量的异质性提出了各种研究来评估宿主异质性对不同传播途径感染的模型参数估计的贡献，并创建了包含这种异质性的两个关键来源的模型：病毒干扰和剂量-反应关系。项目四.了解和控制抗生素耐药性研究淋病，结核病和肺炎球菌感染的耐药性，应用早期项目的方法来了解耐药性的遗传和选择性起源以及观察到的流行异质性的机制。项目五：公共卫生评估和优化的协作建模建议与公共卫生合作伙伴合作，使用一系列建模方法解决其工作的两个关键方面-负担/严重程度估计和干预措施的优化。软件开发和共享以及政策研究是我们研究活动的组成部分。在推广和教育中，我们提出了一系列雄心勃勃的举措，旨在管道和招聘，培训下一代建模人员，并让政策，学术界和新闻界的同事参与进来。