Diagnostic Strategies for Endemic Coronavirus Disease 2019 (COVID-19)
Open accessAbstract
Context.—: Coronavirus disease 2019 (COVID-19) rapid antigen tests generate intrinsically fast, inherently spatial, and immediately actionable results. They quickly confirm COVID-19, but weakly rule out infection. Test performance depends on prevalence and testing protocol. Both affect predictive values. Objectives.—: To use original mathematics and visual logistics for interpreting COVID-19 rapid antigen test performance patterns, gauge the influence of prevalence, and evaluate repeated testing. Design.—: Mathematica and open access software helped graph relationships, perform recursive computations, and compare performance patterns. PubMed retrieved articles addressing endemic COVID-19 were reviewed. Results.—: Tiered sensitivity/specificity comprise the following: T1 (90%/95%), T2 (95%/97.5%), and T3 (100%/≥99%). Performance of self-tests and home antigen tests with US Food and Drug Administration Emergency Use Authorization peaks in low prevalence. Fall-off in performance appears with increasing prevalence because suboptimal sensitivity creates false negatives. The rate of false omissions limits clinical use because of prevalence boundaries based on tolerance for risk. Mathematical analysis supports testing twice to improve predictive values and extend prevalence boundaries nearly to levels of herd immunity. Conclusions.—: COVID-19 is quickly becoming endemic. Suboptimal sensitivity of rapid antigen tests limits performance in high prevalence. Risk of contagion in packed spaces (eg, airplanes) might be avoided with dual testing 36 hours apart, allowing time for viral load to increase. Awareness of community prevalence and proof of improved performance with repeated testing will help manage COVID-19 risk, while meeting rapid decision-making needs for highly contagious and new variants (eg, Delta). New COVID-19 variants call for high-quality, low cost, readily accessible, fast, user friendly, and ubiquitous point-of-care testing.
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Tiered sensitivity/specificity comprise Tier-1 90%/95%, Tier-2 95%/97.5%, Tier-3 100%/≥99%.
“Tiered sensitivity/speci fi city comprise: Tier-1) 90 %, 95 %; Tier-2) 95 %, 97.5 %; and Tier-3) 100 %, ≥ 99 %, respectively [74 -77].”
From Point-of-care testing: state-of-the art and perspectives (2025) · cites this paper as [74]
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Kost, G. J. (2021) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2020-0716-sa · Cited by 23 · see citing works
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Point-of-care testing: state-of-the art and perspectives
Plebani, M., Nichols, J. H., Luppa, P. B., Greene, D., Sciacovelli, L., Shaw, J., Khan, A. I., Carraro, P., Freckmann, G., Dimech, W., et al. (2025) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm-2024-0675 · Cited by 119 · see citing works
Self-citationThe Coronavirus Disease 2019 Spatial Care Path: Home, Community, and Emergency Diagnostic Portals
Kost, G. J. (2022) · Diagnostics · doi:10.3390/diagnostics12051216 · Cited by 13 · see citing works
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- Authors
- Kost, G. J.
- Affiliations
- University of California, Davis (US)
- Corresponding author
- Kost, Gerald J.
- ORCID
- Kost, Gerald J.
- Venue
- Archives of Pathology & Laboratory Medicine
- Published
- 2021-09-22
- Volume
- 146
- Issue
- 1
- Pages
- 16-25
- ISSN
- 0003-9985 (ISSN-L)
- 1543-2165
- OpenAlex
- W4206791061
- Cited by
- 22
- References
- 1
- Citations by year
- 2025: 2 · 2024: 6 · 2023: 2 · 2022: 7 · 2021: 5
- FWCI
- 1.59
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Archives of Pathology & Laboratory Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Keywords
- COVID-19 pandemic, SARS-CoV-2, rapid antigen test, diagnostic performance, prevalence, predictive value, retesting, sensitivity and specificity, false-negative results, self-testing, point-of-care testing, herd immunity, viral load, airborne transmission
- MeSH terms
- COVID-19, SARS-CoV-2, COVID-19 Testing, Humans, Sensitivity and Specificity
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