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Population-based correlates of COVID-19 infection: An analysis from the DFW COVID-19 prevalence study

BACKGROUND: COVID-19 has resulted in over 1 million deaths in the U.S. as of June 2022, with continued surges after vaccine availability. Information on related attitudes and behaviors are needed to inform public health strategies. We aimed to estimate the prevalence of COVID-19, risk factors of inf...

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Autores principales: Singal, Amit G., Masica, Andrew, Esselink, Kate, Murphy, Caitlin C., Dever, Jill A., Reczek, Annika, Bensen, Matthew, Mack, Nicole, Stutts, Ellen, Ridenhour, Jamie L., Galt, Evan, Brainerd, Jordan, Kopplin, Noa, Yekkaluri, Sruthi, Rubio, Chris, Anderson, Shelby, Jan, Kathryn, Whitworth, Natalie, Wagner, Jacqueline, Allen, Stephen, Muthukumar, Alagar R., Tiro, Jasmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714738/
https://www.ncbi.nlm.nih.gov/pubmed/36454745
http://dx.doi.org/10.1371/journal.pone.0278335
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author Singal, Amit G.
Masica, Andrew
Esselink, Kate
Murphy, Caitlin C.
Dever, Jill A.
Reczek, Annika
Bensen, Matthew
Mack, Nicole
Stutts, Ellen
Ridenhour, Jamie L.
Galt, Evan
Brainerd, Jordan
Kopplin, Noa
Yekkaluri, Sruthi
Rubio, Chris
Anderson, Shelby
Jan, Kathryn
Whitworth, Natalie
Wagner, Jacqueline
Allen, Stephen
Muthukumar, Alagar R.
Tiro, Jasmin
author_facet Singal, Amit G.
Masica, Andrew
Esselink, Kate
Murphy, Caitlin C.
Dever, Jill A.
Reczek, Annika
Bensen, Matthew
Mack, Nicole
Stutts, Ellen
Ridenhour, Jamie L.
Galt, Evan
Brainerd, Jordan
Kopplin, Noa
Yekkaluri, Sruthi
Rubio, Chris
Anderson, Shelby
Jan, Kathryn
Whitworth, Natalie
Wagner, Jacqueline
Allen, Stephen
Muthukumar, Alagar R.
Tiro, Jasmin
author_sort Singal, Amit G.
collection PubMed
description BACKGROUND: COVID-19 has resulted in over 1 million deaths in the U.S. as of June 2022, with continued surges after vaccine availability. Information on related attitudes and behaviors are needed to inform public health strategies. We aimed to estimate the prevalence of COVID-19, risk factors of infection, and related attitudes and behaviors in a racially, ethnically, and socioeconomically diverse urban population. METHODS: The DFW COVID-19 Prevalence Study Protocol 1 was conducted from July 2020 to March 2021 on a randomly selected sample of adults aged 18–89 years, living in Dallas or Tarrant Counties, Texas. Participants were asked to complete a 15-minute questionnaire and COVID-19 PCR and antibody testing. COVID-19 prevalence estimates were calculated with survey-weighted data. RESULTS: Of 2969 adults who completed the questionnaire (7.4% weighted response), 1772 (53.9% weighted) completed COVID-19 testing. Overall, 11.5% of adults had evidence of COVID-19 infection, with a higher prevalence among Hispanic and non-Hispanic Black persons, essential workers, those in low-income neighborhoods, and those with lower education attainment compared to their counterparts. We observed differences in attitudes and behaviors by race and ethnicity, with non-Hispanic White persons being less likely to believe in the importance of mask wearing, and racial and ethnic minorities more likely to attend social gatherings. CONCLUSION: Over 10% of an urban population was infected with COVID-19 early during the pandemic. Differences in attitudes and behaviors likely contribute to sociodemographic disparities in COVID-19 prevalence.
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spelling pubmed-97147382022-12-02 Population-based correlates of COVID-19 infection: An analysis from the DFW COVID-19 prevalence study Singal, Amit G. Masica, Andrew Esselink, Kate Murphy, Caitlin C. Dever, Jill A. Reczek, Annika Bensen, Matthew Mack, Nicole Stutts, Ellen Ridenhour, Jamie L. Galt, Evan Brainerd, Jordan Kopplin, Noa Yekkaluri, Sruthi Rubio, Chris Anderson, Shelby Jan, Kathryn Whitworth, Natalie Wagner, Jacqueline Allen, Stephen Muthukumar, Alagar R. Tiro, Jasmin PLoS One Research Article BACKGROUND: COVID-19 has resulted in over 1 million deaths in the U.S. as of June 2022, with continued surges after vaccine availability. Information on related attitudes and behaviors are needed to inform public health strategies. We aimed to estimate the prevalence of COVID-19, risk factors of infection, and related attitudes and behaviors in a racially, ethnically, and socioeconomically diverse urban population. METHODS: The DFW COVID-19 Prevalence Study Protocol 1 was conducted from July 2020 to March 2021 on a randomly selected sample of adults aged 18–89 years, living in Dallas or Tarrant Counties, Texas. Participants were asked to complete a 15-minute questionnaire and COVID-19 PCR and antibody testing. COVID-19 prevalence estimates were calculated with survey-weighted data. RESULTS: Of 2969 adults who completed the questionnaire (7.4% weighted response), 1772 (53.9% weighted) completed COVID-19 testing. Overall, 11.5% of adults had evidence of COVID-19 infection, with a higher prevalence among Hispanic and non-Hispanic Black persons, essential workers, those in low-income neighborhoods, and those with lower education attainment compared to their counterparts. We observed differences in attitudes and behaviors by race and ethnicity, with non-Hispanic White persons being less likely to believe in the importance of mask wearing, and racial and ethnic minorities more likely to attend social gatherings. CONCLUSION: Over 10% of an urban population was infected with COVID-19 early during the pandemic. Differences in attitudes and behaviors likely contribute to sociodemographic disparities in COVID-19 prevalence. Public Library of Science 2022-12-01 /pmc/articles/PMC9714738/ /pubmed/36454745 http://dx.doi.org/10.1371/journal.pone.0278335 Text en © 2022 Singal et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Singal, Amit G.
Masica, Andrew
Esselink, Kate
Murphy, Caitlin C.
Dever, Jill A.
Reczek, Annika
Bensen, Matthew
Mack, Nicole
Stutts, Ellen
Ridenhour, Jamie L.
Galt, Evan
Brainerd, Jordan
Kopplin, Noa
Yekkaluri, Sruthi
Rubio, Chris
Anderson, Shelby
Jan, Kathryn
Whitworth, Natalie
Wagner, Jacqueline
Allen, Stephen
Muthukumar, Alagar R.
Tiro, Jasmin
Population-based correlates of COVID-19 infection: An analysis from the DFW COVID-19 prevalence study
title Population-based correlates of COVID-19 infection: An analysis from the DFW COVID-19 prevalence study
title_full Population-based correlates of COVID-19 infection: An analysis from the DFW COVID-19 prevalence study
title_fullStr Population-based correlates of COVID-19 infection: An analysis from the DFW COVID-19 prevalence study
title_full_unstemmed Population-based correlates of COVID-19 infection: An analysis from the DFW COVID-19 prevalence study
title_short Population-based correlates of COVID-19 infection: An analysis from the DFW COVID-19 prevalence study
title_sort population-based correlates of covid-19 infection: an analysis from the dfw covid-19 prevalence study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714738/
https://www.ncbi.nlm.nih.gov/pubmed/36454745
http://dx.doi.org/10.1371/journal.pone.0278335
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