Introduction: The COVID-19 pandemic has affected communities of colour the hardest. Non-Hispanic black and Hispanic pregnant women appear to have disproportionate SARS-CoV-2 infection and death rates.
Methods and analysis: We will use the socioecological framework and employ a concurrent triangulation, mixed-methods study design to achieve three specific aims: (1) examine the impacts of the COVID-19 pandemic on racial/ethnic disparities in severe maternal morbidity and mortality (SMMM); (2) explore how social contexts (eg, racial/ethnic residential segregation) have contributed to the widening of racial/ethnic disparities in SMMM during the pandemic and identify distinct mediating pathways through maternity care and mental health; and (3) determine the role of social contextual factors on racial/ethnic disparities in pregnancy-related morbidities using machine learning algorithms. We will leverage an existing South Carolina COVID-19 Cohort by creating a pregnancy cohort that links COVID-19 testing data, electronic health records (EHRs), vital records data, healthcare utilisation data and billing data for all births in South Carolina (SC) between 2018 and 2021 (>200 000 births). We will also conduct similar analyses using EHR data from the National COVID-19 Cohort Collaborative including >270 000 women who had a childbirth between 2018 and 2021 in the USA. We will use a convergent parallel design which includes a quantitative analysis of data from the 2018-2021 SC Pregnancy Risk Assessment and Monitoring System (unweighted n>2000) and in-depth interviews of 40 postpartum women and 10 maternal care providers to identify distinct mediating pathways.
Ethics and dissemination: The study was approved by institutional review boards at the University of SC (Pro00115169) and the SC Department of Health and Environmental Control (DHEC IRB.21-030). Informed consent will be provided by the participants in the in-depth interviews. Study findings will be disseminated with key stakeholders including patients, presented at academic conferences and published in peer-reviewed journals.
Keywords: COVID-19; EPIDEMIOLOGY; Health informatics; Maternal medicine; PERINATOLOGY; PUBLIC HEALTH.
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