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Tracking temporal variations of fatality and symptomology correlated with Covid-19 dominant variants and vaccine effectiveness in the United States

Bibliographic Data

ID22083331
AuthorsShao Lin (0000-0002-5535-7504, Albany State University, corresponding author), Han Liu (0000-0003-1868-9312, The University of Texas at San Antonio), Quan Qi (0000-0003-3088-6319, Albany State University), Ian Trees (0000-0003-4747-6017, Eunice Kennedy Shriver National Institute of Child Health and Human Development), Donghong Gao (0000-0001-9638-1546, Albany State University), Samantha Friedman (0000-0001-8412-9618, Albany State University), Xiaobo Romeiko Xue (Albany State University), David Lawrence (0000-0001-5464-5830, Albany State University)
Year2024
Volume12
Pages1419886-1419886
Publication date2024-09-18
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2024.1419886
PMID39360263
OpenAlexW4402576840
LanguageEN
References cited29

Introduction: We described how COVID-19 fatality and symptoms varied by dominant variant and vaccination in the US. Methods: Using the Restricted Access Dataset from the US CDC (1/1/2020-10/20/2022), we conducted a cross-sectional study assessing differences in COVID-19 deaths, severity indicators (hospitalization, ICU, pneumonia, abnormal X-ray, acute respiratory distress syndrome, mechanical ventilation) and 12 mild symptoms by dominant variant/vaccination periods using logistic regression after controlling for confounders. Results: We found the highest fatality during the dominant periods of Wild (4.6%) and Delta (3.4%). Most severe symptoms appeared when Delta was dominant (Rate range: 2.0-9.4%). Omicron was associated with higher mild symptoms than other variants. Vaccination showed consistent protection against death and severe symptoms for most variants (Risk Ratio range: 0.41-0.93). Boosters, especially the second, provided additional protection, reducing severe symptoms by over 50%. Discussion: This dataset may serve as a useful tool to monitor temporospatial changes of fatality and symptom for case management and surveillance

Acute respiratory distress · Case fatality rate · Confounding · Disease · Logistic regression · Pneumonia · Vaccination · COVID-19 epidemiological studies · Demography · Immune responses and vaccinations · Medicine · SARS-CoV-2 and COVID-19 Research · Emergency Medicine · Epidemiology · Immunology · Internal Medicine · Pediatrics

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