MIDAS Center for Communicable Disease Dynamics

我们建议对MIDAS传染病动力学中心(CCDD)进行竞争性更新，网址为 哈佛大学公共卫生学院。基于四年来170多份同行评议的出版物和 在外展和教育方面取得重大成就，我们建议采取多管齐下的方法，扩大 该英才中心的活动将持续到下一个资助期。结合数学和数学方面的专业知识 感染的统计建模与相关学科，我们将进行方法学开发和 应用于一系列公共卫生问题。项目I.病原体基因组学和进化进展 用于推断感染的局部和全球传播和聚集的计算和统计模型， 重组后的抗原性变化，以及疫苗介导性选择下的进化。项目II.新分析 新数据来源方法开发和测试参与式口译的统计方法 传输的参数化和试验用监视和移动电话数据.动态模型.使用 建立疟疾风险图的水文模型，并发展负控制的统计理论。 项目三.考虑到宿主种群的可测量和未测量的异质性，提出了一种 评估宿主异质性对感染的模型参数估计的贡献的研究 不同的传播途径并创建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 方法从早期的项目中了解抗性的遗传和选择起源以及 在其流行中观察到的异质性的潜在机制。项目V.协同建模 公共卫生评估和优化建议与公共卫生合作伙伴合作解决两个关键问题 他们工作的方方面面~负担/严重性评估和干预措施的优化--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的 研究活动。在外联和教育方面，我们提出了一套雄心勃勃的倡议，旨在流水线 招募、培训下一代模特儿，并让政策、学术界和 新闻业。

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.