Evolution, transmission, and clinical impacts of SARS-CoV-2 variants among urban and rural populations

城乡人群中 SARS-CoV-2 变种的进化、传播和临床影响

• 批准号: 10535916
• 负责人: Cynthia Y Tang
• 金额: $ 3.9万
• 依托单位: UNIVERSITY OF MISSOURI-COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10535916
• 关键词: 2019-nCoV; Algorithms; Bayesian Analysis; Bioinformatics; COVID-19; COVID-19 impact; COVID-19 pandemic; COVID-19 severity; COVID-19 vaccination; Catchment Area; Cessation of life; Cities; Classification; Clinical; Clinical Data; Data; Data Set; Disease; Disease Outcome; Economic Burden; Epidemiologic Factors; Epidemiology; Evolution; Fellowship; Future; Genetic Variation; Genome; Genomic approach; Genomics; Geographic Factor; Geographic Information Systems; Geography; Goals; Grant; Healthcare Systems; Individual; Integration Host Factors; Knowledge; Lasso; Linear Regressions; Machine Learning; Medical center; Midwestern United States; Missouri; Modeling; Mutation; Mutation Analysis; National Institute of Allergy and Infectious Disease; Outcome; Patients; Pattern; Phylogenetic Analysis; Physicians; Population; Property; Research; Research Design; Research Priority; Risk Factors; Rural; Rural Community; Rural Population; SARS-CoV-2 positive; SARS-CoV-2 transmission; SARS-CoV-2 variant; Sampling; Scientist; Severity of illness; Statistical Models; Strategic Planning; Testing; Training; United States; Urban Community; Urban Population; Variant; Viral Load result; Virus; base; comorbidity; comparative; computational reasoning; design; disease transmission; doctoral student; experience; genome sequencing; genomic data; health care economics; improved; information system analysis; mortality; multi-task learning; nasopharyngeal swab; novel; pandemic disease; prevent; response; rural area; rural counties; rural disparities; rural environment; social structure; socioeconomics; translational approach; translational study; transmission process; urban area; whole genome

Project Summary The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has resulted in over 5 million deaths worldwide. As the burdens of the pandemic in the United States (US) shift from urban to rural communities, preliminary studies suggest that rural populations suffer from higher disease severity and mortality rates than urban populations. However, even while 20% of the US population lives in a rural area and rural populations have known risk factors that differ from urban populations, the majority of COVID-19 research has primarily focused on large urban centers, and disease mitigation efforts in rural communities are largely informed by urban-centric data. Thus, it is urgently necessary to understand the evolution, spread, and clinical impacts of SARS-CoV-2 variants in rural areas and the disease interactions among urban and rural regions. However, limited clinical and genomic data, particularly from rural areas, are available, preventing us from fully understanding the disease dynamics of COVID-19. The objectives of this training grant are to determine how SARS-CoV-2 variants emerge and spread among urban and rural communities and to determine the virus, host, and population factors associated with clinical outcomes while training an MD-PhD student in advanced bioinformatics approaches, translational study design, and computational thinking to become an independent physician scientist. The Central Hypotheses are that SARS-CoV-2 variants arise in urban centers and spread into rural environments and that a synergistic set of virus, host, and population factors are associated with disease severity. To test our hypotheses, two specific aims are proposed to determine the genetic diversity and spread of SARS-CoV-2 variants among urban and rural regions (Aim 1) and to model clinical impacts of host, SARS-CoV-2 virus, and population factors (Aim 2). An existing and ongoing multi-year dataset that includes clinical information and whole genome sequencing of COVID-19-positive samples of individuals from urban and rural regions of Missouri will be used in both aims. This proposal is submitted in response to the NIAID Strategic Plan for COVID-19 Research Priority 1, “Assess functional consequences of newly emerging SARS-CoV-2 variants.” We expect the results from this study to support this priority in two ways: 1) We will determine the transmission patterns of SARS-CoV-2 variants between urban and rural communities, and 2) We will determine the clinical implications of existing and emerging SARS-CoV-2 variants as they interact with various other virus and host factors. The results from this project will improve the understanding of SARS-CoV-2 transmission dynamics and clinical impacts, particularly among rural populations, which will be important for the mitigation of COVID-19 and future pandemics.

项目摘要 冠状病毒疾病2019（COVID-19）大流行，由严重的急性呼吸系统综合征引起 冠状病毒2（SARS-COV-2）在全球范围内导致超过500万人死亡。作为大流行的伯恩斯 在美国（美国）从城市转移到农村社区，初步研究表明农村人口 疾病的严重程度和死亡率高于城市人口。但是，即使有20％ 美国人口居住在崎 人口，大多数Covid-19研究主要集中在大型城市中心和疾病上 以城市为中心的数据为农村社区的缓解工作。那是迫切需要的 了解SARS-COV-2变体在粗糙地区和 城市和农村地区之间的疾病相互作用。但是，临床和基因组数据有限，特别是 可以从粗糙区域获得，使我们无法完全了解Covid-19的疾病动态。 这项培训赠款的目标是确定SARS-COV-2变体如何在 城市和粗糙社区，并确定与临床相关的病毒，宿主和人群因素 结果在培训MD-PHD学生的高级生物信息学方法时，翻译研究设计， 和计算思维成为一名独立的物理科学家。中心假设是 SARS-COV-2变体在城市中心出现，并扩散到粗糙的环境中，并协同集合 病毒，宿主和人口因素与疾病严重程度有关。为了检验我们的假设，两个特定的 提出了目的来确定城市中SARS-COV-2变体的遗传多样性和传播 和粗糙区域（AIM 1），并建模宿主，SARS-COV-2病毒和人群因素的临床影响 （目标2）。现有的和正在进行的多年数据集，其中包括临床信息和整个基因组 将使用来自密苏里州城市和农村地区的个人的COVID-19阳性样本的测序 在两个目标中。 该提案是针对Covid-19优先级的NIAID战略计划提交的， “评估新出现的SARS-COV-2变体的功能后果。”我们期望从中获得结果 研究以两种方式支持此优先级：1）我们将确定SARS-COV-2变体的传输模式 在城市和农村社区之间，以及2）我们将确定现有和新兴的临床意义 SARS-COV-2变体与其他各种病毒和宿主因素相互作用。这个项目的结果将 提高对SARS-COV-2传播动态和临床影响的理解，尤其是在农村 人群，这对于减轻19和未来大流行的减轻至关重要。