This article is a Preprint
Preprints are preliminary research reports that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Preprints posted online allow authors to receive rapid feedback and the entire scientific community can appraise the work for themselves and respond appropriately. Those comments are posted alongside the preprints for anyone to read them and serve as a post publication assessment.
Assessment of Sociodemographic Factors Associated with Time to Self-reported COVID-19 Infection Among a Large Multi-Center Prospective Cohort Population in the Southeastern United States (preprint)
medrxiv; 2023.
Preprint
in English
| medRxiv | ID: ppzbmed-10.1101.2023.10.20.23297306
ABSTRACT
Objective:
We aimed to investigate sociodemographic factors associated with self-reported COVID-19 infection.Methods:
The study population is a multicenter prospective cohort of adult volunteers recruited from healthcare systems located in the mid-Atlantic and southern United States. Between April 2020 and October 2021 participants completed daily online questionnaires about symptoms, exposures, and risk behaviors related to COVID-19, including self-reports of positive SARS CoV-2 detection tests and COVID-19 vaccination. Analysis of time from study enrollment to self-reported COVID-19 infection used a time-varying mixed effects Cox-proportional hazards framework.Results:
Overall, 1,603 of 27,214 study participants (5.9%) reported a positive COVID-19 test during the study period. The adjusted hazard ratio demonstrated lower risk for women, those with a graduate level degree, and smokers. A higher risk was observed for healthcare workers, those aged 18-34, those in rural areas, those from households where a member attends school or interacts with the public, and those who visited a health provider in the last year.Conclusions:
Increased risk of self-reported COVID-19 was associated with specific demographic characteristics, which may help to inform targeted interventions for future pandemics.
Full text:
Available
Collection:
Preprints
Database:
medRxiv
Main subject:
COVID-19
Language:
English
Year:
2023
Document Type:
Preprint
Similar
MEDLINE
...
LILACS
LIS