A composite symptoms severity score based on survey self-reports as a predictor of SARS-CoV-2 infection and viral load
Our findings demonstrate that self-reported symptom severity and number of symptoms are robust predictors of SARS-CoV-2 infection and viral load, providing potential utility in clinical risk stratification. However, limitations, including a small sample size for viral load analyses and reliance on self-reported data, should be considered.
Authors
- Daniel A. Jarem (ORCID: https://orcid.org/0000-0001-6190-1441)
- Jesse Canchola (ORCID: https://orcid.org/0000-0001-5831-7463)
- Priscilla Moonsamy
- Tuna Toptan (ORCID: https://orcid.org/0000-0002-5399-9263)
- Sandra Ciesek (ORCID: https://orcid.org/0000-0002-1802-7565)
- Maria J. G. T. Vehreschild (ORCID: https://orcid.org/0000-0003-0446-3224)
- Alison Kuchta
- Annemarie Berger (ORCID: https://orcid.org/0000-0002-4612-4290)
- Damian Diaz
- Ana M. Groh
Institutions
- Goethe University Frankfurt (DE)
- Fraunhofer Institute for Translational Medicine and Pharmacology (DE)
- Department of Virology (FR)
- Materials Systems (United States) (US)
- University Hospital Frankfurt (DE)
Publication Details
- Journal
- BMC Infectious Diseases
- Published
- 2025-09-23
- DOI
- https://doi.org/10.1186/s12879-025-11653-4
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00