The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Serologic assays for influenza surveillance, diagnosis and vaccine evaluation
Abstract
Serological techniques play a critical role in various aspects of influenza surveillance, vaccine development and evaluation, and sometimes in diagnosis, particularly for novel influenza virus infections of humans. Because individuals are repeatedly exposed to antigenically and genetically diverse influenza viruses over a lifetime, the gold standard for detection of a recent influenza virus infection or response to current vaccination is the demonstration of a seroconversion, a fourfold or greater rise in antibody titer relative to a baseline sample, to a circulating influenza strain or vaccine component. The hemagglutination-inhibition assay remains the most widely used assay to detect strain-specific serum antibodies to influenza. The hemagglutination-inhibition assay is also used to monitor antigenic changes among influenza viruses which are constantly evolving; such antigenic data is essential for consideration of changes in influenza vaccine composition. The use of the hemagglutinin-specific microneutralization assay has increased, in part, owing to its sensitivity for detection of human antibodies to novel influenza viruses of animal origin. Neutralization assays using replication-incompetent pseudotyped particles may be advantageous in some laboratory settings for detection of antibodies to influenza viruses with heightened biocontainment requirements. The use of standardized protocols and antibody standards are important steps to improve reproducibility and interlaboratory comparability of results of serologic assays for influenza viruses.
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
Mapping the Antigenic and Genetic Evolution of Influenza Virus
Smith, D. J., Lapedes, A. S., de Jong, J. C., Bestebroer, T. M., Rimmelzwaan, G. F., Osterhaus, A. D. M. E., & Fouchier, R. A. M. (2004) · Science · doi:10.1126/science.1097211 · Cited by 1,868
Hospitalized patients with 2009 H1N1 influenza in the United States, April-June 2009
Jain, S., Kamimoto, L., Bramley, A. M., Schmitz, A. M., Benoit, S. R., Louie, J., Sugerman, D. E., Druckenmiller, J. K., Ritger, K. A., Chugh, R., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0906695 · Cited by 1,700
Cocirculation of two distinct evolutionary lineages of influenza type B virus since 1983
Rota, P. A., Wallis, T. R., Harmon, M. W., Rota, J. S., Kendal, A. P., & Nerome, K. (1990) · Virology · doi:10.1016/0042-6822(90)90186-u · Cited by 539
Cited by
Belongia, E. A., Simpson, M. D., King, J. P., Sundaram, M. E., Kelley, N. S., Osterholm, M. T., & McLean, H. Q. (2016) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(16)00129-8 · Cited by 698
Skowronski, D. M., Janjua, N. Z., De Serres, G., Sabaiduc, S., Eshaghi, A., Dickinson, J. A., Fonseca, K., Winter, A.-L., Gubbay, J. B., Krajden, M., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0092153 · Cited by 416
Antibody to Influenza Virus Neuraminidase: An Independent Correlate of Protection
Monto, A. S., Petrie, J. G., Cross, R. T., Johnson, E., Liu, M., Zhong, W., Levine, M., Katz, J. M., & Ohmit, S. E. (2015) · Journal of Infectious Diseases · doi:10.1093/infdis/jiv195 · Cited by 369
Self-citationInfluenza Vaccine Effectiveness in the United States during the 2015–2016 Season
Jackson, M. L., Chung, J. R., Jackson, L. A., Phillips, C. H., Benoit, J., Monto, A. S., Martin, E. T., Belongia, E. A., McLean, H. Q., Gaglani, M., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1700153 · Cited by 283
Mannosylation of LNP Results in Improved Potency for Self-Amplifying RNA (SAM) Vaccines
Goswami, R., Chatzikleanthous, D., Lou, G., Giusti, F., Bonci, A., Taccone, M., Brazzoli, M., Gallorini, S., Ferlenghi, I., Berti, F., et al. (2019) · ACS Infectious Diseases · doi:10.1021/acsinfecdis.9b00084 · Cited by 113
Metadata
- Authors
- Katz, J. M., Hancock, K., & Xu, X.
- Venue
- Expert Review of Anti-infective Therapy
- Publisher
- Informa UK Limited
- Published
- 2011-06
- Volume
- 9
- Issue
- 6
- Pages
- 669-683
- ISSN
- 1478-7210 (ISSN-L)
- 1744-8336
- OpenAlex
- W2153968193
- Cited by
- 235
- References
- 3
- FWCI
- 10.81
- Type
- journal article
- Language
- en
- Open access
- closed
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: Serologic assays for influenza surveillance, diagnosis and vaccine evaluation. https://app.cochat.ai/papers/10.1586/eri.11.51
- The paper
- Katz, J. M., Hancock, K., & Xu, X. (2011). Serologic assays for influenza surveillance, diagnosis and vaccine evaluation. Expert Review of Anti-infective Therapy. https://doi.org/10.1586/eri.11.51
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.