RAPID:Genomic Variation Analysis of Coronavirus to Better Understand the Spread of COVID-19

目前，由严重急性呼吸系统综合征冠状病毒2型（SARS-CoV-2）引起的2019冠状病毒病（COVID-19）在全球范围内大流行。截至2020年4月2日，COVID-19确诊病例已超过100万例，死亡病例超过55，000例。这些数字正在迅速增加。然而，自这次爆发以来的短暂时间限制了我们对SARS-CoV-2如何传播的理解。该项目的目标是弥补这一差距。有证据表明，医疗服务提供者之间的感染率高得惊人，为了应对这一情况，该项目将揭示医院环境中的传播模式。在与克利夫兰诊所的合作中，研究人员将获得基因组，流行病学和临床患者数据。对这些数据的联合计算分析将产生一个计算模型，该模型将提供对医院中传播模式的见解，例如从患者到医生和卫生工作者，或从医生到医生。本项目的活动将围绕沿着三个目标组织。目的1：对克利夫兰诊所收集的SARS-CoV-2样本进行全基因组测序。这些数据将通过来自多个在线数据库的现有SARS-CoV-2序列数据以及来自其他物种的现有序列数据进行扩充。目标2：构建分析管道，并对目标1中获得的基因组数据进行进化分析。目的3：对基因组、流行病学和临床数据进行联合分析，以推断传播模式。该项目的独特优势之一是能够将鉴定的基因组菌株与临床数据直接联系起来。这些活动对更好地保护医护人员和最大限度地减少医院环境中的总体感染率具有直接的临床意义。该项目的研究结果将与整个研究界分享，以帮助其他医院在这场大流行期间获得更多数据进行进一步分析。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Currently, there is a world-wide pandemic of the Coronavirus Disease 2019 (COVID-19) that is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of April 2, 2020, there have been more than one million confirmed cases of COVID-19 and more than 55,000 deaths. These numbers are increasing rapidly. Yet, the short time since the beginning of this outbreak limits our understanding of how SARS-CoV-2 spreads. The objective of this project is to address this gap. In response to evidence that the rate of infections among healthcare providers is alarmingly high, this project will expose transmission patterns in the hospital setting. In collaboration with the Cleveland Clinic, the investigators will have access to genomic, epidemiological, and clinical patient data. Joint computational analysis of this data will result in a computational model that will provide insights into transmission patterns in hospitals, such as from patients to doctors and health workers, or from doctors to doctors. The activities in this project will be organized along three Aims. Aim 1: Perform whole-genome sequencing of SARS-CoV-2 samples collected at the Cleveland Clinic. The data will be augmented by existing SARS-CoV-2 sequence data from multiple online databases, as well as existing sequence data from other species. Aim 2: Build an analysis pipeline and perform evolutionary analysis of genomic data obtained in Aim 1. Aim 3: Perform joint analysis of genomic, epidemiological, and clinical data to infer transmission patterns. One of the unique advantages of the project is the ability to directly link identified genomic strains to clinical data. The activities have direct clinical implications for better protecting healthcare workers and minimizing the overall rate of infections in the hospital setting. Findings from this project will be shared with the research community at large to aid further analysis in other hospitals as more data becomes available during this pandemic.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.