The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Scaling up COVID-19 rapid antigen tests: promises and challenges
Open accessAbstract
WHO recommends a minimum of 80% sensitivity and 97% specificity for antigen-detection rapid diagnostic tests (Ag-RDTs), which can be used for patients with symptoms consistent with COVID-19. However, after the acute phase when viral load decreases, use of Ag-RDTs might lead to high rates of false negatives, suggesting that the tests should be replaced by a combination of molecular and serological tests. When the likelihood of having COVID-19 is low, such as for asymptomatic individuals in low prevalence settings, for travel, return to schools, workplaces, and mass gatherings, Ag-RDTs with high negative predictive values can be used with confidence to rule out infection. For those who test positive in low prevalence settings, the high false positive rate means that mitigation strategies, such as molecular testing to confirm positive results, are needed. Ag-RDTs, when used appropriately, are promising tools for scaling up testing and ensuring that patient management and public health measures can be implemented without delay.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Virological assessment of hospitalized patients with COVID-2019
Wölfel, R., Corman, V. M., Guggemos, W., Seilmaier, M., Zange, S., Müller, M. A., Niemeyer, D., Jones, T. C., Vollmar, P., Rothe, C., et al. (2020) · Nature · doi:10.1038/s41586-020-2196-x · Cited by 6,661
Temporal dynamics in viral shedding and transmissibility of COVID-19
He, X., Lau, E. H. Y., Wu, P., Deng, X., Wang, J., Hao, X., Lau, Y. C., Wong, J. Y., Guan, Y., Tan, X., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0869-5 · Cited by 4,247
Antibody Responses to SARS-CoV-2 in Patients With Novel Coronavirus Disease 2019
Zhao, J., Yuan, Q., Wang, H., Liu, W., Liao, X., Su, Y., Wang, X., Yuan, J., Li, T., Li, J., et al. (2020) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa344 · Cited by 2,607
Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility
Arons, M. M., Hatfield, K. M., Reddy, S. C., Kimball, A., James, A., Jacobs, J. R., Taylor, J., Spicer, K., Bardossy, A. C., Oakley, L. P., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2008457 · Cited by 2,052
Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening
Larremore, D. B., Wilder, B., Lester, E., Shehata, S., Burke, J. M., Hay, J. A., Tambe, M., Mina, M. J., & Parker, R. (2021) · Science Advances · doi:10.1126/sciadv.abd5393 · Cited by 1,216
Predicting infectious severe acute respiratory syndrome coronavirus 2 from diagnostic samples
Bullard, J., Dust, K., Funk, D., Strong, J. E., Alexander, D., Garnett, L., Boodman, C., Bello, A., Hedley, A., Schiffman, Z., et al. (2020) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa638 · Cited by 1,075
Rethinking Covid-19 Test Sensitivity — A Strategy for Containment
Mina, M. J., Parker, R., & Larremore, D. B. (2020) · New England Journal of Medicine · doi:10.1056/nejmp2025631 · Cited by 703
SARS-CoV-2 detection, viral load and infectivity over the course of an infection
Walsh, K. A., Jordan, K., Clyne, B., Rohde, D., Drummond, L., Byrne, P., Ahern, S., Carty, P. G., O'Brien, K. K., O'Murchu, E., et al. (2020) · Journal of Infection · doi:10.1016/j.jinf.2020.06.067 · Cited by 608
Porte, L., Legarraga, P., Vollrath, V., Aguilera, X., Munita, J. M., Araos, R., Pizarro, G., Vial, P., Iruretagoyena, M., Dittrich, S., et al. (2020) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2020.05.098 · Cited by 371
Serology testing in the COVID-19 pandemic response
Peeling, R. W., Wedderburn, C. J., Garcia, P. J., Boeras, D., Fongwen, N., Nkengasong, J., Sall, A., Tanuri, A., & Heymann, D. L. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30517-x · Cited by 360
Self-citation
Cited by
Diagnostics for COVID-19: moving from pandemic response to control
Peeling, R. W., Heymann, D. L., Teo, Y.-Y., & Garcia, P. J. (2022) · The Lancet · doi:10.1016/s0140-6736(21)02346-1 · Cited by 486
Self-citationLateral flow test engineering and lessons learned from COVID-19
Budd, J., Miller, B. S., Weckman, N. E., Cherkaoui, D., Huang, D., Decruz, A. T., Fongwen, N., Han, G.-R., Broto, M., Estcourt, C. S., et al. (2023) · Nature Reviews Bioengineering · doi:10.1038/s44222-022-00007-3 · Cited by 308
Self-citation
Metadata
- Authors
- Peeling, R. W., Olliaro, P. L., Boeras, D. I., & Fongwen, N.
- Venue
- The Lancet Infectious Diseases
- Publisher
- Elsevier BV
- Published
- 2021-09
- Volume
- 21
- Issue
- 9
- Pages
- e290-e295
- ISSN
- 1473-3099 (ISSN-L)
- OpenAlex
- W3132070651
- Cited by
- 323
- References
- 18
- FWCI
- 20.58
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Scaling up COVID-19 rapid antigen tests: promises and challenges. https://app.cochat.ai/papers/10.1016/s1473-3099(21)00048-7
- The paper
- Peeling, R. W., Olliaro, P. L., Boeras, D. I., & Fongwen, N. (2021). Scaling up COVID-19 rapid antigen tests: promises and challenges. The Lancet Infectious Diseases. https://doi.org/10.1016/s1473-3099(21)00048-7
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
