SARS-CoV-2 whole genome sequencing from large-scale campus testing and state-wide communities in NH--Center of Integrated Biomedical and Bioengineering Research (CIBBR)

来自新罕布什尔州大规模校园测试和全州社区的 SARS-CoV-2 全基因组测序——综合生物医学和生物工程研究中心 (CIBBR)

• 批准号: 10381231
• 负责人: Rick H Cote
• 金额: $ 75.71万
• 依托单位: UNIVERSITY OF NEW HAMPSHIRE
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10381231
• 关键词: 2019-nCoV; Age; Appearance; Area; Biomedical Engineering; COVID-19; COVID-19 pandemic; COVID-19 severity; COVID-19 surveillance; Characteristics; Clinical; Communities; Contact Tracing; Deposition; Diagnostic tests; Disease; Disease Outbreaks; Exhibits; Genbank; Gender; Genomics; Health system; Herd Immunity; Hospitals; Human; Immune system; Immunity; Immunization Programs; Incidence; Individual; Infection; Knowledge; Laboratories; Large-Scale Sequencing; Measures; Metadata; Molecular Diagnostic Testing; New Hampshire; Phase; Population; Population Characteristics; Predisposition; Prevalence; Public Health; Recording of previous events; Research; Reverse Transcriptase Polymerase Chain Reaction; SARS-CoV-2 genome; SARS-CoV-2 infection; SARS-CoV-2 variant; Sample Size; Sampling; Sequence Analysis; Severities; Severity of illness; Specimen; Symptoms; Testing; United States Dept. of Health and Human Services; Universities; Vaccinated; Vaccination; Variant; Viral; Viral Load result; Virus; age group; base; community living; disorder risk; experience; genome sequencing; infection rate; novel; racial and ethnic; response; study population; transmission process; variants of concern; whole genome

PROJECT SUMMARY/ABSTRACT The Covid-19 pandemic has challenged public health systems throughout the world. Since October 2020, novel variants of concern of the SARS-CoV-2 virus have been identified and appear to be a significant concern for rates of infection, severity of disease, and the potential for variable responses to prior infection and/or vaccination. In the US—and especially in the state of New Hampshire—the number of SARS-CoV-2 genomes sequenced has been sparse. Furthermore, SARS-CoV-2 sequencing efforts have primarily been directed toward symptomatic individuals and/or contact tracing of special cases (e.g., hospital transmission). We currently lack knowledge in several areas including the temporal sequence and geolocation of the appearance of SARS-CoV-2 variants in regional communities; the correlation between incidents of viral outbreaks and SARS-CoV-2 variants; and the racial, ethnic, gender, and age susceptibility to infection (and severity of COVID-19 symptoms) by specific SARS-CoV-2 variants. In addition, as the U.S. enters a critical phase of the SARS-CoV-2 pandemic to develop herd immunity through prior infection and the vaccination program, we also lack an understanding of to what extent previously infected and/or vaccinated individuals are still susceptible to infection by SARS-CoV-2, and if so, what variants are infecting these supposedly “protected” individuals. The objective of this project is to determine the genomic sequence of a large majority of the SARS- CoV-2 variants identified in infected individuals in the state of NH and to apply this knowledge to better understand the likelihood that SARS-CoV-2 variants of concern increase the transmissibility of the virus, evade the immune systems of those previously infected, or result in a greater likelihood of infected individuals to experience clinical symptoms. The study population for this project consists of 12,000 stored human specimens previously confirmed by diagnostic tests to contain the SARS-CoV-2 virus, as well as newly identified specimens infected with SARS-CoV-2 as they become available during the project period. Preliminary whole-genome sequencing results document the quality of stored specimens as well as the ability to determine the lineage of SARS-CoV-2 variants present in the UNH congregate community and in the general NH population. Large-scale genomic surveillance of SARS-CoV-2 will permit correlating SARS-CoV-2 variant prevalence with available metadata (e.g., date of infection, geolocation, severity of outbreaks, symptomology, and characteristics of the sample population. Understanding the distribution and infectivity of SARS-CoV-2 variants will provide public health agencies with more accurate and specific information on public health measures that need to be enacted to control COVID-19 based on the types of SARS-CoV-2 variants present in specific populations, including those in congregate communities and previously infected individuals.

项目总结/文摘