Healthcare-Seeking Behavior for Respiratory Illness Among Flu Near You Participants in the United States During the 2015-2016 Through 2018-2019 Influenza Seasons.

citizen science digital epidemiology healthcare-seeking behavior influenza surveillance influenza-like illness respiratory illness

Journal

The Journal of infectious diseases
ISSN: 1537-6613
Titre abrégé: J Infect Dis
Pays: United States
ID NLM: 0413675

Informations de publication

Date de publication:
24 08 2022
Historique:
received: 26 02 2020
accepted: 27 07 2020
pubmed: 8 8 2020
medline: 19 11 2022
entrez: 8 8 2020
Statut: ppublish

Résumé

Flu Near You (FNY) is an online participatory syndromic surveillance system that collects health-related information. In this article, we summarized the healthcare-seeking behavior of FNY participants who reported influenza-like illness (ILI) symptoms. We applied inverse probability weighting to calculate age-adjusted estimates of the percentage of FNY participants in the United States who sought health care for ILI symptoms during the 2015-2016 through 2018-2019 influenza season and compared seasonal trends across different demographic and regional subgroups, including age group, sex, census region, and place of care using adjusted χ 2 tests. The overall age-adjusted percentage of FNY participants who sought healthcare for ILI symptoms varied by season and ranged from 22.8% to 35.6%. Across all seasons, healthcare seeking was highest for the <18 and 65+ years age groups, women had a greater percentage compared with men, and the South census region had the largest percentage while the West census region had the smallest percentage. The percentage of FNY participants who sought healthcare for ILI symptoms varied by season, geographical region, age group, and sex. FNY compliments existing surveillance systems and informs estimates of influenza-associated illness by adding important real-time insights into healthcare-seeking behavior.

Sections du résumé

BACKGROUND
Flu Near You (FNY) is an online participatory syndromic surveillance system that collects health-related information. In this article, we summarized the healthcare-seeking behavior of FNY participants who reported influenza-like illness (ILI) symptoms.
METHODS
We applied inverse probability weighting to calculate age-adjusted estimates of the percentage of FNY participants in the United States who sought health care for ILI symptoms during the 2015-2016 through 2018-2019 influenza season and compared seasonal trends across different demographic and regional subgroups, including age group, sex, census region, and place of care using adjusted χ 2 tests.
RESULTS
The overall age-adjusted percentage of FNY participants who sought healthcare for ILI symptoms varied by season and ranged from 22.8% to 35.6%. Across all seasons, healthcare seeking was highest for the <18 and 65+ years age groups, women had a greater percentage compared with men, and the South census region had the largest percentage while the West census region had the smallest percentage.
CONCLUSIONS
The percentage of FNY participants who sought healthcare for ILI symptoms varied by season, geographical region, age group, and sex. FNY compliments existing surveillance systems and informs estimates of influenza-associated illness by adding important real-time insights into healthcare-seeking behavior.

Identifiants

pubmed: 32761050
pii: 5881614
doi: 10.1093/infdis/jiaa465
pmc: PMC9400452
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

270-277

Subventions

Organisme : NIGMS NIH HHS
ID : T32 GM074905
Pays : United States

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America.

Auteurs

Kristin Baltrusaitis (K)

Center for Biostatistics in AIDS Research, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA.

Carrie Reed (C)

Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

Kara Sewalk (K)

Computational Epidemiology Laboratory, Boston Children's Hospital, Boston, Massachusetts, USA.

John S Brownstein (JS)

Computational Epidemiology Laboratory, Boston Children's Hospital, Boston, Massachusetts, USA.
Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA.
Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.

Adam W Crawley (AW)

Ending Pandemics, San Francisco, California, USA.

Matthew Biggerstaff (M)

Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

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