The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.
Theoretical Basis of the Test-Negative Study Design for Assessment of Influenza Vaccine Effectiveness
Open accessAbstract
Influenza viruses undergo frequent antigenic changes. As a result, the viruses circulating change within and between seasons, and the composition of the influenza vaccine is updated annually. Thus, estimation of the vaccine's effectiveness is not constant across seasons. In order to provide annual estimates of the influenza vaccine's effectiveness, health departments have increasingly adopted the "test-negative design," using enhanced data from routine surveillance systems. In this design, patients presenting to participating general practitioners with influenza-like illness are swabbed for laboratory testing; those testing positive for influenza virus are defined as cases, and those testing negative form the comparison group. Data on patients' vaccination histories and confounder profiles are also collected. Vaccine effectiveness is estimated from the odds ratio comparing the odds of testing positive for influenza among vaccinated patients and unvaccinated patients, adjusting for confounders. The test-negative design is purported to reduce bias associated with confounding by health-care-seeking behavior and misclassification of cases. In this paper, we use directed acyclic graphs to characterize potential biases in studies of influenza vaccine effectiveness using the test-negative design. We show how studies using this design can avoid or minimize bias and where bias may be introduced with particular study design variations.
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Cited by
Lauring, A. S., Tenforde, M. W., Chappell, J. D., Gaglani, M., Ginde, A. A., McNeal, T., Ghamande, S., Douin, D. J., Talbot, H. K., Casey, J. D., et al. (2022) · BMJ · doi:10.1136/bmj-2021-069761 · Cited by 656
Accorsi, E. K., Britton, A., Fleming-Dutra, K. E., Smith, Z. R., Shang, N., Derado, G., Miller, J., Schrag, S. J., & Verani, J. R. (2022) · JAMA · doi:10.1001/jama.2022.0470 · Cited by 628
Effectiveness of mRNA-1273 against SARS-CoV-2 omicron and delta variants
Tseng, H. F., Ackerson, B. K., Luo, Y., Sy, L. S., Talarico, C. A., Tian, Y., Bruxvoort, K. J., Tubert, J. E., Florea, A., Ku, J. H., et al. (2022) · doi:10.1101/2022.01.07.22268919 · Cited by 541
Chung, H., He, S., Nasreen, S., Sundaram, M. E., Buchan, S. A., Wilson, S. E., Chen, B., Calzavara, A., Fell, D. B., Austin, P. C., et al. (2021) · BMJ · doi:10.1136/bmj.n1943 · Cited by 307
Lau, J. J., Cheng, S. M. S., Leung, K., Lee, C. K., Hachim, A., Tsang, L. C. H., Yam, K. W. H., Chaothai, S., Kwan, K. K. H., Chai, Z. Y. H., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02219-5 · Cited by 198
Metadata
- Authors
- Sullivan, S. G., Tchetgen Tchetgen, E. J., & Cowling, B. J.
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-08-31
- Volume
- 184
- Issue
- 5
- Pages
- 345-353
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- OpenAlex
- W2507826825
- Cited by
- 319
- References
- 62
- FWCI
- 18.26
- Type
- journal article
- Language
- en
- Open access
- bronze
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