Temporal Trend of COVID-19 Clinical Severity and the Ethnic/Racial Disparity: A Report from the Maryland Study Group

Abstract

Objectives This study aimed to evaluate the temporal trend of novel coronavirus disease 2019 (COVID-19) symptoms and severity of clinical outcomes among pregnant women over a calendar year in the State of Maryland and compare clinical outcomes between different ethnic and racial groups. Study Design We conducted a retrospective, multicenter observational study of the temporal trend of COVID-19 clinical presentation during pregnancy in the State of Maryland. We reviewed consecutive charts of adult pregnant females, aged 18 to 55 years, with laboratory-confirmed severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection between March 1, 2020, and February 28, 2021, and managed within the University of Maryland Medical System and Johns Hopkins Medicine. We excluded cases with insufficient data for assessing the COVID-19 diagnosis, pregnancy status, or clinical outcomes. We evaluated the evolution of COVID-19 symptoms at the time of presentation. Also, we compared COVID-19 infection rate, hospitalization rate, oxygen use, and intensive care unit (ICU) admission rates between different ethnic and racial groups. Results We included 595 pregnant women with laboratory-confirmed COVID-19 over the study period. The prevalence of respiratory and systemic symptoms decreased over time with incidence rate ratios (IRRs) of 0.91 per month (95% confidence interval [CI]: 0.88–0.95) and 0.87 per month (95% CI: 0.83–0.95), respectively. The prevalence of hospitalization, O2 requirement, and ICU admission decreased over time with IRRs of 0.86 per month (95% CI: 0.82–0.91), 0.91 per month (95% CI: 0.84–0.98), and 0.70 per month (95% CI: 0.57–0.85), respectively. The Hispanic and Black populations had a higher COVID-19 infection rate and hospitalization rate than the non-Hispanic White population (p = 0.004, < 0.001, and < 0.001, respectively). Conclusion Understanding the concepts of viral evolution could potentially help the fight against pandemics like COVID-19. Moreover, this might improve the knowledge of how pandemics affect disadvantaged populations and help close the gap in health care inequities. Key Points