Environmental Factors Predicting Risk of Severe COVID Infection

预测严重新冠病毒感染风险的环境因素

基本信息

批准号：
10208054
负责人：
ELIZABETH ANNE REGAN
金额：
$ 24.28万
依托单位：
NATIONAL JEWISH HEALTH
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-14 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10208054
关键词：
2019-nCoV Address African American Air Pollutants Air Pollution Airway Disease COVID-19 COVID-19 morbidity COVID-19 mortality COVID-19 pandemic COVID-19 severity Censuses Cessation of life Characteristics Chronic Chronic Obstructive Airway Disease Cohort Analysis Contracts County Crowding Data Data Collection Diabetes Mellitus Disease Economic Factors Enrollment Environmental Risk Factor Exposure to Gases Genetic Hispanics Hospitalization Housing Hypertension Image Incidence Individual Infection Institutes Link Location Long-Term Effects Longitudinal cohort Longitudinal cohort study Lung Lung diseases Lung infections Measurement Measures Medical Meteorology Modeling Modification Monitor Observational Study Outcome Ozone Parents Participant Particulate Phenotype Play Predictive Factor Predisposition Prevalence Public Health Research Risk Risk Factors Role SARS-CoV-2 infection Severity of illness Smoker Social Distance Socioeconomic Factors Spirometry Structure Time United States Update Variant Viral Virus Virus Diseases Workplace X-Ray Computed Tomography airway inflammation ambient air pollution base chest computed tomography clinical center coarse particles cohort comorbidity coronavirus disease disorder risk former smoker geographic difference high risk high risk population instrument longitudinal analysis older men pandemic disease particle pollutant professional atmosphere residence respiratory risk mitigation rural area severe COVID-19 small airways disease social socioeconomics transmission process trend urban area viral detection

项目摘要

Project Summary/ Abstract The objective of this project is to identify the effect of air pollution on the risk and severity of COVID-19 illness. Air pollution may increase the risk of viral infections of the lung in general and there is emerging evidence that COVID-19 illness may be increased in regions where air pollution levels are high. Identification of factors that increase risk of COVID-19 illness will have major public health impacts. We will assess the incidence, prevalence and severity of COVID-19 infection within COPDGene, a well-characterized, longitudinal cohort of subjects with and without existing lung disease. The cohort is distributed at 20 clinical centers across the United States and includes subjects with a broad distribution of socioeconomic characteristics, rural and urban locations and air pollution exposures. The cohort was enriched for African-American subjects. We will adjust for other socioeconomic factors in the models using county level census data and normalize the cohort data to county level disease prevalence. Longitudinal analyses of COVID-19 incidence in relation to changing levels of monthly air pollution will be done and the impact of pre-existing lung disease on the outcomes will be studied. The air pollution data will be based on spatial analysis of the cohort using satellite and ground monitoring measures of particulates, NOx, SO2, CO and ozone, to identify factors that modify risk of: any disease, severe disease or death. The impact of air pollution on lung structural damage after COVID-19 illness will be measured using pre and post-COVID chest CT scans and spirometric changes in the cohort to identify extent of lung involvement and persistent effects.

项目概要/摘要该项目的目标是确定空气污染对风险和严重程度的影响 2019冠状病毒病。一般来说，空气污染可能会增加肺部病毒感染的风险并且有新的证据表明，在空气质量较差的地区，COVID-19 患病率可能会增加污染程度很高。识别增加 COVID-19 疾病风险的因素将有重大公共卫生影响。我们将评估 COVID-19 的发病率、流行率和严重程度 COPDGene 中的感染，这是一个特征明确的纵向队列，受试者患有和没有现有的肺部疾病。该队列分布在美国 20 个临床中心国家并包括具有广泛社会经济特征分布的主体，农村以及城市地点和空气污染暴露。该群体的非洲裔美国人更加丰富科目。我们将在使用县级的模型中调整其他社会经济因素人口普查数据并将队列数据标准化为县级疾病患病率。纵向将分析与每月空气污染水平变化相关的 COVID-19 发病率已完成，并将研究先前存在的肺部疾病对结果的影响。空气污染数据将基于使用卫星和地面对队列进行空间分析监测颗粒物、氮氧化物、二氧化硫、一氧化碳和臭氧的措施，以确定改变的因素风险：任何疾病、严重疾病或死亡。空气污染对肺结构的影响将使用 COVID-19 患病前后的胸部 CT 扫描来测量 COVID-19 患病后的损害，队列中肺活量变化以确定肺部受累程度和持续影响。