MIDAS Center for Communicable Disease Dynamics

MIDAS 传染病动态中心

• 批准号: 9335878
• 负责人: MARC LIPSITCH
• 金额: $ 225万
• 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/9335878
• 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; Heterogeneity; Infection; Intervention; Journalism; Knowledge; Malaria; Maps; Mathematics; Measures; Mediating; Methodology; 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; analytical method; disease transmission; mathematical model; next generation; pathogen; public health emergency; resistance mechanism; response; software development; theories; transmission process

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 outreach 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 incorporrating 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.

我们建议对MIDAS传染病动态中心（CCDD）进行竞争性更新， 哈佛公共卫生学院。基于四年来170多份同行评审出版物的记录， 在推广和教育方面取得重大成就，我们建议采取多管齐下的方法， 该中心的活动将在下一个供资期间进行。结合数学和 与相关学科感染的统计建模，我们将进行方法的发展， 适用于一系列公共卫生问题。项目一病原体基因组学和进化发展 计算和统计模型来推断感染的局部和全球传播和聚集， 通过重组的抗原性变化，以及在疫苗介导的选择下的进化。项目二.新的分析 新数据源的方法开发和测试用于解释参与性的统计方法 传输动态模型的参数化和测试用监视和移动的电话数据的应用 水文建模，以建立疟疾风险图，并发展阴性控制的统计理论。 项目三.对宿主种群中可测量和不可测量的异质性的解释提出了各种 的研究，以评估宿主异质性的贡献，以模型参数估计感染 不同的传播途径，并创建模型，以评估这种异质性的两个关键来源：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、肺结核和肺炎球菌感染的耐药性， 早期项目的方法来了解抗性的遗传和选择性起源， 观察到其患病率的异质性的潜在机制。项目五.建立合作模式 公共卫生评估和优化建议与公共卫生合作伙伴合作，以解决两个关键问题 他们的工作的各个方面-负担/严重程度估计和干预措施的优化-使用一系列 建模方法。软件开发和共享以及政策研究是我们 研究活动。在推广和教育方面，我们提出了一套雄心勃勃的计划，旨在 招募、培训下一代建模人员，并让政策、学术界和 新闻业