The Impact of Increasing Disease Prevalence, False Omissions, and Diagnostic Uncertainty on Coronavirus Disease 2019 (COVID-19) Test Performance
Open accessAbstract
CONTEXT.—: Coronavirus disease 2019 (COVID-19) test performance depends on predictive values in settings of increasing disease prevalence. Geospatially distributed diagnostics with minimal uncertainty facilitate efficient point-of-need strategies. OBJECTIVES.—: To use original mathematics to interpret COVID-19 test metrics; assess US Food and Drug Administration Emergency Use Authorizations and Health Canada targets; compare predictive values for multiplex, antigen, polymerase chain reaction kit, point-of-care antibody, and home tests; enhance test performance; and improve decision-making. DESIGN.—: PubMed/newsprint-generated articles documenting prevalence. Mathematica and open access software helped perform recursive calculations, graph multivariate relationships, and visualize performance by comparing predictive value geometric mean-squared patterns. RESULTS.—: Tiered sensitivity/specificity comprised: T1, 90%, 95%; T2, 95%, 97.5%; and T3, 100%, ≥99%. Tier 1 false negatives exceeded true negatives at >90.5% prevalence; false positives exceeded true positives at <5.3% prevalence. High-sensitivity/specificity tests reduced false negatives and false positives, yielding superior predictive values. Recursive testing improved predictive values. Visual logistics facilitated test comparisons. Antigen test quality fell off as prevalence increased. Multiplex severe acute respiratory syndrome (SARS)-CoV-2)*influenza A/B*respiratory syncytial virus testing performed reasonably well compared with tier 3. Tier 3 performance with a tier 2 confidence band lower limit will generate excellent performance and reliability. CONCLUSIONS.—: The overriding principle is to select the best combined performance and reliability pattern for the prevalence bracket. Some public health professionals recommend repetitive testing to compensate for low sensitivity. More logically, improved COVID-19 assays with less uncertainty conserve resources. Multiplex differentiation of COVID-19 from influenza A/B-respiratory syncytial virus represents an effective strategy if seasonal flu surges next year.
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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 [75]
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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
- 2021-03-08
- Volume
- 145
- Issue
- 7
- Pages
- 797-813
- ISSN
- 0003-9985 (ISSN-L)
- 1543-2165
- OpenAlex
- W3134030341
- Cited by
- 23
- References
- 45
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 4 · 2023: 2 · 2022: 3 · 2021: 9
- FWCI
- 1.43
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- other-oa
- Locations
- Archives of Pathology & Laboratory Medicine (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Funders
- Fulbright Program
- University of California, Davis
- 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 › COVID-19 Clinical Research Studies
- Keywords
- COVID-19 pandemic, SARS-CoV-2, diagnostic performance, disease prevalence, predictive value, false-negative results, false positives, diagnostic uncertainty, point-of-care testing, home testing, antigen testing, multiplex PCR, influenza A/B, respiratory syncytial virus, emergency use authorization, sensitivity and specificity
- MeSH terms
- COVID-19, COVID-19 Testing, Canada, False Negative Reactions, False Positive Reactions, Humans, Predictive Value of Tests, Sensitivity and Specificity, United States, Reproducibility of Results, Prevalence, Point-of-Care Systems, Uncertainty
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