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.

项目概要 由严重急性呼吸系统综合症引起的 2019 年冠状病毒病 (COVID-19) 大流行 冠状病毒-2 (SARS-CoV-2) 已导致全球超过 500 万人死亡。由于疫情的重担 在美国，从城市社区向农村社区的转变，初步研究表明农村人口 与城市人口相比，他们的疾病严重程度和死亡率更高。然而，尽管 20% 美国人口生活在农村地区，农村人口的已知风险因素与城市人口不同 人口，大多数 COVID-19 研究主要集中在大城市中心和疾病 农村社区的缓解努力很大程度上取决于以城市为中心的数据。因此，迫切需要 了解农村地区和农村地区 SARS-CoV-2 变种的进化、传播和临床影响 城乡地区疾病的相互作用。然而，有限的临床和基因组数据，特别是 来自农村地区的病毒无法获得，这使我们无法充分了解 COVID-19 的疾病动态。 该培训补助金的目的是确定 SARS-CoV-2 变种如何在人群中出现和传播 城市和农村社区，并确定与临床相关的病毒、宿主和人口因素 在对医学博士生进行高级生物信息学方法、转化研究设计、 和计算思维成为一名独立的医师科学家。中心假设是 SARS-CoV-2 变种出现在城市中心并传播到农村环境，并且一组协同作用 病毒、宿主和人群因素与疾病严重程度相关。为了检验我们的假设，有两个具体的 提出的目标是确定城市中 SARS-CoV-2 变体的遗传多样性和传播 和农村地区（目标 1），并模拟宿主、SARS-CoV-2 病毒和人口因素的临床影响 （目标 2）。现有且正在进行的多年数据集，包括临床信息和全基因组 将使用对密苏里州城市和农村地区个体的 COVID-19 阳性样本进行测序 在这两个目标中。 本提案是为了响应 NIAID COVID-19 研究优先事项 1 战略计划而提交的， “评估新出现的 SARS-CoV-2 变体的功能后果。”我们期待这个结果 研究以两种方式支持这一优先事项：1）我们将确定 SARS-CoV-2 变种的传播模式 城市和农村社区之间的关系，以及 2) 我们将确定现有和新兴的临床影响 SARS-CoV-2 变体与各种其他病毒和宿主因素相互作用。该项目的结果将 提高对 SARS-CoV-2 传播动态和临床影响的了解，特别是在农村地区 人口，这对于缓解 COVID-19 和未来的流行病非常重要。