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传染病动力学中心（CCDD）进行竞争性更新