Social Drivers of COVID-19 Disease Severity in Pregnant Patients

Objective While coronavirus disease 2019 (COVID-19), the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had global impact in all populations, certain groups of patients have experienced disproportionate rates of morbidity and mortality. The purpose of this study was to assess the relationship between COVID-19 disease severity, demographic variables, race and ethnicity, and social determinants of health among pregnant patients in a diverse urban population.Study Design A retrospective analysis was performed of all pregnant patients diagnosed with COVID-19 at two urban tertiary care centers in Houston, TX between March and August 2020. Maternal demographic, COVID-19 illness criteria, and delivery characteristics were collected. The Centers for Disease Control and Prevention Social Vulnerability Index (SVI) and COVID-19 Community Vulnerability Index (CCVI) were obtained based on a patients' census tract of residence. Analyses compared persons with asymptomatic, mild, or severe-critical disease at diagnosis.Results A total of 317 persons tested positive for COVID-19 during this time period. Asymptomatic persons were more likely to be diagnosed at later gestational ages, but there were no other differences in baseline maternal characteristics. Persons with more severe disease had greater social vulnerability specifically for housing and transportation than those with mild disease (mean SVI [standard error]: 0.72 [0.06] vs. 0.58 [0.2], p = 0.03). Total SVI, total CCVI, and other themed SVI and CCVI indices were not significantly different between groups.Conclusion In this cohort of pregnant persons infected with SARS-CoV-2, an association was shown between disease severity and increased vulnerability in living conditions and transportation. Drivers of the pandemic and COVID-19 outcomes are complex and multifactorial, and likely change over time. However, continued efforts to accurately identify and measure social determinants of health in medicine will likely help identify geographic areas and patient populations that are at risk of higher disease burden. This could facilitate preventative and mitigation measures in these areas in future disaster or pandemic situations.