Mathematical, Computational, and Predictive Modeling Core

数学、计算和预测建模核心

• 批准号: 10706800
• 负责人: Laurent Hébert-Dufresne
• 金额: $ 22.4万
• 依托单位: UNIVERSITY OF VERMONT & ST AGRIC COLLEGE
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10706800
• 关键词: 2019-nCoV; Address; Affect; Antimicrobial Resistance; Area; Attention; Behavior; Behavioral; Biological; Biology; Biomedical Computing; COVID-19 pandemic; Centers of Research Excellence; Clinical; Collaborations; Communicable Diseases; Communication; Complex; Computer Models; Conscious; Development; Diagnostic tests; Disease; Doctor of Philosophy; Education; Epidemic; Epidemiology; Eye; Faculty; Fostering; Funding; Goals; Growth; Human; Immune response; Immunologics; Inequity; Infectious Diseases Research; Inflammatory; Institution; Intervention; Knowledge; Language; Mathematics; Measures; Mission; Modeling; Morbidity - disease rate; Pattern; Phase; Pilot Projects; Play; Population; Predisposition; Public Health; Research; Research Personnel; Research Project Grants; Research Support; Risk; Role; Scientist; Services; Societies; Structure; Testing; Therapeutic; Time; Training; Uncertainty; Vaccines; antimicrobial; biomedical scientist; bridge program; current pandemic; design; disease transmission; disorder control; education research; experience; improved; interest; low and middle-income countries; mathematical model; microbiome; mortality; next generation; pandemic disease; pathogen; predictive modeling; pressure; prevent; programs; response; synergism; tool; vaccine-induced immunity

PROJECT SUMMARY: Laurent Hebert-Dufresne, PhD, MCP Core (Research Core 2) Reducing the enormous burden of global infectious diseases remains one of the most important public health problems in the world. This realization was brought to the attention of the world during the COVID-19 pandemic. Mathematical and Computational Predictive (MCP) modeling is essential for understanding the epidemiology and mechanistic biology behind the spread of global infectious diseases. Modeling can play a critical role, for example, in improving our understanding and prediction of antimicrobial resistance, in the design of new antimicrobials and diagnostic tests, and in clarifying the complexities of the immune response involved in vaccine-induced protection. To fully exploit the potential of MCP modeling in global infectious disease research, however, we need to continue developing a common language and purpose that is still often lacking between the biological and computational worlds. In Phase I of this TGIR COBRE, we made significant progress in bridging this biomedical-computational “culture gap” through collaborative research and reciprocal education about each group’s domain expertise. In Phase 2 of this TGIR COBRE program, the MCP Core will continue to advance this mission by making its primary goal to serve the TGIR COBRE by bringing MCP modeling to bear on global infectious diseases research at UVM and to support our developing research project leaders (RPL) and junior faculty. At the same time, the MCP Core will continue its crucially important and already successful program of bridging the scientific culture gap between scientists with biomedical backgrounds and those with computational modeling expertise. To do this, the MCP Core will expand the TGIR COBRE institutional strength in Phase 2 by actively fostering cross-campus research projects focused on global infectious disease. Particular focus will be given to developing RPLs and creating funded research projects led by investigators from both the biomedical and mathematical/computational domains. These goals will be pursued in three Specific Aims: 1) to provide expertise and services directly to TGIR COBRE research project leaders, pilot awardees, and junior faculty, as well as other TGIR faculty to build and test computational models of globally important infectious diseases, 2) to expand and mature the educational components needed to train the next generation of scientists to employ both biomedical and computational research tools to reduce the global burden of infectious disease, and 3) to build institutional strength by fostering the development of fundable cross-campus research projects that bring biomedical and mathematical/computational scientists together in synergistic collaborations focused on global infectious disease.

项目摘要：Laurent Hebert-Duresne，博士，MCP核心(研究核心2) 减少全球传染病的巨大负担仍然是最重要的公共卫生之一 世界上的问题。这一认识在新冠肺炎期间引起了世界的关注 大流行。数学和计算预测(MCP)建模对于理解 全球传染病传播背后的流行病学和机制生物学。建模可以起到一种 例如，在提高我们对抗菌素耐药性的理解和预测方面， 设计新的抗菌剂和诊断测试，并澄清免疫反应的复杂性 参与疫苗诱导的保护。充分挖掘MCP模拟在全球传染病研究中的潜力 然而，疾病研究需要我们继续发展一种共同语言和目标，这种共同语言和目标仍然经常 生物界和计算界之间缺乏联系。在这个TGIR Cobre的第一阶段，我们做出了重要的 通过合作研究和互惠来弥合生物医学-计算“文化鸿沟”的进展 关于每个小组的领域专业知识的教育。在此TGIR Cobre计划的第二阶段，MCP核心将 继续推进这一使命，其主要目标是通过带来MCP为TGIR Cobre服务 建模以支持UVM的全球传染病研究并支持我们正在进行的研究 项目负责人(RPL)和初级教员。与此同时，MCP核心将继续其至关重要的 已经成功地弥合了科学家与生物医学之间的科学文化鸿沟 背景和那些具有计算建模专业知识的人。为此，MCP核心将扩展TGIR Cobre在第二阶段的机构实力，通过积极促进专注于以下项目的跨校园研究项目 全球传染病。将特别关注开发RPL和创建资助研究 由生物医学和数学/计算领域的研究人员领导的项目。这些目标 将追求三个具体目标：1)直接向TGIR Cobre研究提供专业知识和服务 项目负责人、试点获奖者和初级教师以及其他TGIR教师，以构建和测试计算 全球重要传染病的模型，2)扩大和成熟所需的教育组成部分 培训下一代科学家同时使用生物医学和计算研究工具来减少 传染病的全球负担，以及3)通过促进 可资助的跨校园研究项目，吸引生物医学和数学/计算科学家 共同开展以全球传染病为重点的协同合作。