Symptoms and symptom clusters associated with SARS-CoV-2 infection in community-based populations: Results from a statewide epidemiological study

Date
2020-10-22
Language
American English
Embargo Lift Date
Committee Members
Degree
Degree Year
Department
Grantor
Journal Title
Journal ISSN
Volume Title
Found At
Cold Spring Harbor Laboratory
Abstract

Background: Prior studies examining symptoms of COVID-19 are primarily descriptive and measured among hospitalized individuals. Understanding symptoms of SARS-CoV-2 infection in pre-clinical, community-based populations may improve clinical screening, particularly during flu season. We sought to identify key symptoms and symptom combinations in a community-based population using robust methods.

Methods: We pooled community-based cohorts of individuals aged 12 and older screened for SARS-CoV-2 infection in April and June 2020 for a statewide seroprevalence study. Main outcome was SARS-CoV-2 positivity. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for individual symptoms as well as symptom combinations. We further employed multivariable logistic regression and exploratory factor analysis (EFA) to examine symptoms and combinations associated with SARS-CoV-2 infection.

Results: Among 8214 individuals screened, 368 individuals (4.5%) were RT-PCR positive for SARS-CoV-2. Although two-thirds of symptoms were highly specific (>90.0%), most symptoms individually possessed a PPV <50.0%. The individual symptoms most greatly associated with SARS-CoV-2 positivity were fever (OR=5.34, p<0.001), anosmia (OR=4.08, p<0.001), ageusia (OR=2.38, p=0.006), and cough (OR=2.86, p<0.001). Results from EFA identified two primary symptom clusters most associated with SARS-CoV-2 infection: (1) ageusia, anosmia, and fever; and (2) shortness of breath, cough, and chest pain. Moreover, being non-white (13.6% vs. 2.3%, p<0.001), Hispanic (27.9% vs. 2.5%, p<0.001), or living in an Urban area (5.4% vs. 3.8%, p<0.001) was associated with infection.

Conclusions: Symptoms can help distinguish SARS-CoV-2 infection from other respiratory viruses, especially in community or urgent care settings where rapid testing may be limited. Symptoms should further be structured in clinical documentation to support identification of new cases and mitigation of disease spread by public health. These symptoms, derived from asymptomatic as well as mildly infected individuals, can also inform vaccine and therapeutic clinical trials.

Description
item.page.description.tableofcontents
item.page.relation.haspart
Cite As
Dixon, B. E., Wools-Kaloustian, K., Fadel, W. F., Duszynski, T. J., Yiannoutsos, C., Halverson, P. K., & Menachemi, N. (2020). Symptoms and symptom clusters associated with SARS-CoV-2 infection in community-based populations: Results from a statewide epidemiological study. MedRxiv. https://doi.org/10.1101/2020.10.11.20210922
ISSN
Publisher
Series/Report
Sponsorship
This work was supported by a grant from the State of Indiana to the IU Fairbanks School of Public Health to conduct seroprevalence testing in the state population. Dr. Dixon receives funding from the U.S. National Library of Medicine (T15LM012502) as well as the U.S. Centers for Disease Control and Prevention (U18DP006500) and the Indiana State Department of Health to support disease surveillance research. The funder had no role in study design, data collection, data analysis, data interpretation, or writing of the paper.
Major
Extent
Identifier
Relation
Journal
medRxiv
Source
medRxiv
Alternative Title
Type
Preprint
Number
Volume
Conference Dates
Conference Host
Conference Location
Conference Name
Conference Panel
Conference Secretariat Location
Version
Full Text Available at
This item is under embargo {{howLong}}