CoVPN 5002: SARS-CoV-2 Prevalence Study

CoVPN 5002：SARS-CoV-2 流行率研究

• 批准号: 10226718
• 负责人: Deborah J Donnell
• 金额: $ 29.6万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2020-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10226718
• 关键词: 2019-nCoV; Adult; Antibodies; Attitude; Biological Assay; COVID-19; COVID-19 pandemic; Cessation of life; Characteristics; Child; Clinical; Clinical Trials; Communities; Containment; Data; Detection; Development; Disease; Disease Outcome; Disease Progression; Faculty; Foundations; Fred Hutchinson Cancer Research Center; Frequencies; Future; General Population; Goals; HIV Vaccine Trials Network; Health Knowledge, Attitudes, Practice; Health Resources; Household; Immune response; Immunoglobulin G; Immunoglobulin M; Incidence; Individual; Infection; Institution; Laboratories; Leadership; Liquid substance; Measures; Medical; Medical Records; Modeling; National Institute of Allergy and Infectious Disease; Nose; Oral; Outcome; Participant; Patient Self-Report; Performance; Phylogenetic Analysis; Play; Population Sizes; Prevalence; Prevalence Study; Prevention; Prevention strategy; Prevention trial; Preventive Intervention; Public Health; Questionnaires; RNA; Readiness; Recording of previous events; Reporting; Research; Research Support; Risk; Risk Factors; Role; Saliva; Sampling; Serological; Seroprevalences; Severe Acute Respiratory Syndrome; Site; Specificity; Specimen; Statistical Methods; Swab; Symptoms; Testing; Time; Vaccines; Virus; age group; base; clinical research site; co-infection; comorbidity; coronavirus disease; data management; design; electronic data; epidemiological model; ethnic health disparity; experience; innovation; mathematical model; member; racial and ethnic; seropositive; social; social factors; surveillance study; transmission process; treatment strategy; treatment trial; uptake

Abstract The proposed research, CoVPN 5002, will directly contribute to preparedness for SARS-CoV-2 vaccine and other COVID-19 prevention and treatment studies by determining the prevalence of SARS-CoV-2 infection and seroprevalence among samples of individuals at elevated risk as well as the general population. This research will determine the extent to which children and adults in the study communities have SARS-CoV-2 infection or evidence of prior SARS-CoV-2 infection (based on antibody tests, self-report, and medical records). Additionally, about participants’ household members with COVID-like illness and deaths, combined with serologic data from participants, may also provide information about transmission dynamics within households. Questionnaire data will inform estimates of the percent of individuals of different age groups, including children, who may have had an asymptomatic COVID-19 infection. The frequency of infection among children and whether children play an important role in community transmission is poorly understood. The study will also estimate the association of SARS-CoV-2 seroprevalence with medical co-morbidities associated with more severe disease outcomes and identify demographic and social risk factors associated with infection. Finally, this research will provide important information about SARS-CoV-2 transmission, COVID-19 disease, attitudes about and uptake of containment and mitigation measures, racial and ethnic health disparities, varied access to testing and public health resources by key demographic indicators, prospects for new prevention and treatment strategies, and inform mathematical models of disease progression and projection of future COVID-19 risk. The HPTN SDMC, housed at the Fred Hutchinson Cancer Research Center in Seattle, takes advantage of the strengths of the institution, which also includes the HVTN SDMC. The HPTN SDMC has faculty biostatisticians experienced in the design, conduct and analysis of global clinical trials and surveillance studies, who support research through leadership in statistical design, trial conduct and analysis, and development and implementation of innovative statistical methods as needed and motivated by the scientific goals. The SDMC provides regulatory compliant data management functions for all trials it implements, including electronic data capture directly from research sites or the field, integration of laboratory specimens and assay results, and electronic participant reported outcomes.

抽象的 拟议的研究 CoVPN 5002 将直接有助于应对 SARS-CoV-2 疫苗和其他 COVID-19 预防和治疗研究，通过确定流行率 高风险个体样本中的 SARS-CoV-2 感染和血清流行率以及 普通民众。这项研究将确定儿童和成人在多大程度上 研究社区有 SARS-CoV-2 感染或之前有 SARS-CoV-2 感染的证据（基于 抗体测试、自我报告和医疗记录）。此外，关于参与者的家庭成员 与新冠病毒类似的疾病和死亡，结合参与者的血清学数据，也可能提供 有关家庭内传播动态的信息。问卷数据将为估计提供信息 不同年龄组（包括儿童）的个人百分比 无症状的 COVID-19 感染。儿童感染频率以及儿童是否感染 人们对它在社区传播中发挥的重要作用知之甚少。该研究还将估计 SARS-CoV-2 血清流行率与更多疾病相关的医学并发症之间的关系 严重疾病结果并确定与感染相关的人口和社会风险因素。 最后，这项研究将提供有关 SARS-CoV-2 传播、COVID-19 的重要信息 疾病、对遏制和缓解措施的态度和采取情况、种族和民族健康 不同关键人群获得检测和公共卫生资源的机会存在差异 指标、新的预防和治疗策略的前景，并为数学模型提供信息 疾病进展和未来 COVID-19 风险的预测。 HPTN SDMC 位于西雅图 Fred Hutchinson 癌症研究中心，负责 利用该机构的优势，其中还包括 HVTN SDMC。 HPTN SDMC 拥有在全球临床试验的设计、实施和分析方面经验丰富的生物统计学家 监测研究，通过统计设计、试验实施和领导力支持研究 根据需要分析、开发和实施创新统计方法 受到科学目标的激励。 SDMC 提供符合法规的数据管理 其实施的所有试验的功能，包括直接从研究场所采集电子数据或 现场、实验室标本和化验结果的整合以及电子参与者报告 结果。