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288 Self-Reported Symptoms for COVID-19 Public Health Surveillance: A Window to Social Determinants of Health

Published online by Cambridge University Press:  19 April 2022

Hope G. Gray
Affiliation:
University of Alabama at Birmingham
Sue S. Feldman
Affiliation:
University of Alabama at Birmingham
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Abstract

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OBJECTIVES/GOALS: HelpBeatCOVID19.org, a novel self-reporting symptom tracking surveillance system, is based at the University of Alabama, Birmingham. Helpbeatcovid19.org captures social determinants of health (SDOH) data. This presentation will report research in progress to understand the utility of self-reported data with communicable disease outbreaks. METHODS/STUDY POPULATION: Individuals voluntarily completed an online questionnaire at HelpBeatCOVID19.org which captured SDOH data and other disease surveillance variables including zip code, gender, age group, race, ethnicity, symptoms, underlying conditions, type of home (e.g., single-family, mobile home, etc.), and household COVID-19 diagnosis status. The data are stored on HIPAA-compliant servers. De-identified self-reported data were culled from the HelpBeatCOVID19 database, cleaned, sorted, and analyzed by zip code. Using STATA/SE 16.1, we employed regression analysis to determine if there might be any statistically significant associations that could be made based on zip codes, especially where there are health disparities in historically African American neighborhoods in Jefferson County. RESULTS/ANTICIPATED RESULTS: To date, 102,308 people have reported their symptoms in HelpBeatCOVID19. Of those, 77,903 are from Alabama. More than half of the people who completed HelpBeatCOVID19.org reported zero symptoms. However, 19.3% of Alabamians reported having underlying health conditions. Midfield, AL, a predominantly African-American neighborhood (81.1%), has 74.1% of people reporting underlying conditions where the median household income is $38,750. By comparison, Vestavia Hills, AL, a more affluent neighborhood with an 88.8% White population and median household income being $109,485, had more people participating in HelpBeatCOVID19 (3,920), yet a smaller percentage (15.2%) with underlying health conditions. Final results will be reported during the ACTS Conference. DISCUSSION/SIGNIFICANCE: Our analysis of the data reveals that in Jefferson County, AL, a greater number of people in affluent communities participated in the study. Whereas state-wide, a greater percentage of individuals indicated that they had zero symptoms. Identifying self-reported underlying conditions that impact persons with COVID-19 symptoms will be significant.

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Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2022. The Association for Clinical and Translational Science