The External Exposome and COVID-19 Severity

外部暴露组和 COVID-19 严重程度

• 批准号: 10240752
• 负责人: Jiang Bian
• 金额: --
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-20 至 2021-09-06
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10240752
• 关键词: 2019-nCoV; Affect; Age; Air Pollution; Asthma; COVID-19; COVID-19 mortality; COVID-19 patient; COVID-19 severity; COVID-19 surveillance; Cardiovascular Diseases; Centers for Disease Control and Prevention (U.S.); Cessation of life; Characteristics; Chronic lung disease; Clinical; Clinical Research; Consumption; Data; Data Sources; Databases; Diabetes Mellitus; Diagnosis; Disease; Elderly; Electronic Health Record; Environment; Environmental Exposure; Environmental Risk Factor; Ethnic group; Exposure to; Florida; Future; Geography; Health; Hospitalization; Individual; Joints; Knowledge; Laboratories; Link; Literature; Mediation; Medical; Methods; Neighborhoods; Obesity; Outcome; Patients; Physicians; Prevention Measures; Primary Prevention; Process; Public Health; Recording of previous events; Resolution; Resources; Review Literature; Risk Factors; SARS-CoV-2 positive; Severities; Structure; Symptoms; Testing; Time; Vital Statistics; Work; base; cohort; comorbidity; coronavirus disease; data resource; demographics; deprivation; design; electronic structure; epidemiology study; high risk; improved; mortality; natural language; novel; pandemic disease; patient oriented; personalized intervention; phenotyping algorithm; predictive modeling; racial and ethnic; racial and ethnic disparities; repository; response; scale up; severe COVID-19; social; social health determinants; sociodemographics; socioeconomics; spatiotemporal; success; systematic review; walkability; young adult

PROJECT SUMMARY The 2019 novel coronavirus disease (COVID-19) is a global pandemic with severe medical and socioeconomic consequences. Young adults without any underlying health conditions can still develop severe COVID-19 disease, and there are racial and ethnic disparities in COVID-19 hospitalization and mortality rates which cannot be explained by age and underlying health conditions alone. Risk factors of severe COVID-19 beyond older age and underlying health conditions are large unknown. There are large overlaps between the currently known risk factors of severe COVID-19 and the health conditions that are affected by environmental exposures, and emerging evidence suggested that long-term environmental exposures may be important determinants of COVID-19 severity. Traditional environmental epidemiological studies usually examine environmental factors separately without considering “the totality of the external environment”. Such studies are not only time consuming as they examine individual exposures separately, but more importantly, cannot account for confounding by co-exposures. The external exposome is an ideal framework to identify novel exposures associated with severe COVID-19 as it can systematically and efficiently screen thousands of environmental exposures. In this project, we will leverage a unique real-world data (RWD) resource – OneFlorida – a large repository of linked electronic health records (EHR), claims and vital statistics data, covering more than 60% of Floridians, contributing to the national Patient-Centered Clinical Research Network (PCORnet). Building on our prior work on the external exposome, we will expand our existing external exposome database to include additional factors that may impact COVID-19 outcomes through a systematic analysis of literature and resources. We aim to (1) develop phenotyping algorithms for identifying a COVID-19 cohort and their severity and extracting associated individual-level risk factors from the OneFlorida real-world data, and (2) identify external exposome factors associated with severe COVID-19, examine how the external exposome contributes to racial and ethnic disparities in severe COVID-19, and build predictive models of severe COVID-19 with external exposome factors. This study will fill important knowledge gaps by providing timely information to understand how environmental exposures may impact COVID-19 severity that will improve identifications of high-risk COVID-19 patients and inform the design of future precision interventions. Our approach and initial results for Florida can (1) be readily scaled up to a multi-state study through PCORnet and (2) answer other novel questions such as the external exposome’s contribution to geographic disparities in COVID-19 outcomes.

项目概要 2019 年新型冠状病毒病（COVID-19）是一场全球大流行病，造成严重的医疗和社会影响 没有任何潜在健康问题的年轻人仍然可能患上严重的 COVID-19。 疾病，并且 COVID-19 住院率和死亡率存在种族和民族差异， 不能仅用年龄和潜在健康状况来解释严重 COVID-19 的风险因素。 目前，老年人的年龄和潜在的健康状况存在很大的重叠。 严重 COVID-19 的已知风险因素以及受环境影响的健康状况 暴露，新出现的证据表明，长期环境暴露可能很重要 传统的环境流行病学研究通常检查 COVID-19 严重程度的决定因素。 单独的环境因素，而不考虑“外部环境的总体”。 不仅耗时，因为他们单独检查个体暴露，而且更重要的是，无法 外部暴露组是识别新颖性的理想框架。 与严重的 COVID-19 相关的暴露，因为它可以系统、有效地筛查数千名 在这个项目中，我们将利用独特的现实世界数据（RWD）资源 - OneFlorida – 链接电子健康记录 (EHR)、索赔和生命统计数据的大型存储库， 覆盖超过 60% 的佛罗里达人，为国家以患者为中心的临床研究网络做出贡献 (PCORnet)。在我们之前关于外部暴露的工作的基础上，我们将扩展我们现有的外部暴露。 暴露数据库包含可能通过系统性影响 COVID-19 结果的其他因素 我们的目标是 (1) 开发用于识别 COVID-19 的表型分析算法。 队列及其严重性，并从 OneFlorida 现实世界中提取相关的个人风险因素 数据，以及 (2) 识别与严重 COVID-19 相关的外部暴露因素，检查外部因素如何影响 暴露组会导致严重的 COVID-19 中的种族和民族差异，并建立预测模型 这项研究将通过提供具有外部暴露因素的严重 COVID-19 来填补重要的知识空白。 及时获取信息以了解环境暴露可能如何影响 COVID-19 的严重程度，这将 改进对高风险 COVID-19 患者的识别，并为未来精准干预措施的设计提供信息。 我们针对佛罗里达州的方法和初步结果可以 (1) 通过 PCORnet 轻松扩展到多州研究 (2) 回答其他新问题，例如外部暴露对地理差异的贡献 COVID-19 结果。