Using Data Science and a Health Equity Lens to Identify Long-COVID Sequelae Among Medically Underserved Populations.

Md Nasir, Nicole Cook, Daniel Parras,Sumit Mukherjee,Geralyn Miller,Juan Lavista Ferres, Katherine Chung-Bridges

Journal of health care for the poor and underserved(2023)

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摘要
Understanding how post-acute COVID-19 syndrome (PACS or long COVID) manifests among underserved populations, who experienced a disproportionate burden of acute COVID-19, can help providers and policymakers better address this ongoing crisis. To identify clinical sequelae of long COVID among underserved populations treated in the primary care safety net, we conducted a causal impact analysis with electronic health records (EHR) to compare symptoms among community health center patients who tested positive (n=4,091) and negative (n=7,118) for acute COVID-19. We found 18 sequelae with statistical significance and causal dependence among patients who had a visit after 60 days or more following acute COVID-19. These sequelae encompass most organ systems and include breathing abnormalities, malaise and fatigue, and headache. This study adds to current knowledge about how long COVID manifests in a large, underserved population.
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COVID-19,long COVID,post-acute COVID-19 syndrome,electronic health records (EHR),time series,causality,underserved populations
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