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

目前，由严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）引起的2019冠状病毒病（COVID-19）正在全球大流行。截至2020年4月2日，COVID-19确诊病例超过100万例，死亡病例超过5.5万例。这些数字正在迅速增加。然而，自这次疫情开始以来的短时间限制了我们对SARS-CoV-2如何传播的理解。这个项目的目标是解决这一差距。有证据表明，卫生保健提供者之间的感染率高得惊人，为此，该项目将揭示医院环境中的传播模式。通过与克利夫兰诊所的合作，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。这个项目的活动将按照三个目标来组织。目标1：对克利夫兰诊所采集的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序列数据以及其他物种的现有序列数据来增强。目标2：建立分析管道，并对目标1中获得的基因组数据进行进化分析。目标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直接将已识别的基因组菌株与临床数据联系起来。这些活动对更好地保护卫生保健工作者和尽量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，以帮助其他医院在本次大流行期间获得更多数据时进行进一步分析。该奖项反映了美国国家科学基金会的法定使命，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.