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.
Emerging evidence suggested that environmental exposures may be important determinants of COVID-19 severity. This study leverages a unique data resource ? OneFlorida ? a large repository of linked electronic health records (EHR), claims and vital statistics data, covering more than 60% of Floridians and builds upon our prior work on the external exposome to (1) identify novel environmental factors associated with severe COVID-19, (2) examine whether the external exposome contributes to racial and ethnic disparities in severe COVID-19, and (3) develop predictive models of high-risk patients with external exposome factors. This study will fill important knowledge gaps and provide timely information to understand how environmental exposures may impact COVID-19 severity to inform future precision interventions.
