Skip to main content
Top
Published in: BMC Public Health 1/2021

Open Access 01-12-2021 | Influenza Vaccination | Research article

Differences between Frequentist and Bayesian inference in routine surveillance for influenza vaccine effectiveness: a test-negative case-control study

Authors: Michael L. Jackson, Jill Ferdinands, Mary Patricia Nowalk, Richard K. Zimmerman, Burney Kieke, Manjusha Gaglani, Kempapura Murthy, Joshua G. Petrie, Emily T. Martin, Jessie R. Chung, Brendan Flannery, Lisa A. Jackson

Published in: BMC Public Health | Issue 1/2021

Login to get access

Abstract

Background

Routine influenza vaccine effectiveness (VE) surveillance networks use frequentist methods to estimate VE. With data from more than a decade of VE surveillance from diverse global populations now available, using Bayesian methods to explicitly account for this knowledge may be beneficial. This study explores differences between Bayesian vs. frequentist inference in multiple seasons with varying VE.

Methods

We used data from the United States Influenza Vaccine Effectiveness (US Flu VE) Network. Ambulatory care patients with acute respiratory illness were enrolled during seasons of varying observed VE based on traditional frequentist methods. We estimated VE against A(H1N1)pdm in 2015/16, dominated by A(H1N1)pdm; against A(H3N2) in 2017/18, dominated by A(H3N2); and compared VE for live attenuated influenza vaccine (LAIV) vs. inactivated influenza vaccine (IIV) among children aged 2–17 years in 2013/14, also dominated by A(H1N1)pdm. VE was estimated using both frequentist and Bayesian methods using the test-negative design. For the Bayesian estimates, prior VE distributions were based on data from all published test-negative studies of the same influenza type/subtype available prior to the season of interest.

Results

Across the three seasons, 16,342 subjects were included in the analyses. For 2015/16, frequentist and Bayesian VE estimates were essentially identical (41% each). For 2017/18, frequentist and Bayesian estimates of VE against A(H3N2) viruses were also nearly identical (26% vs. 23%, respectively), even though the presence of apparent antigenic match could potentially have pulled Bayesian estimates upward. Precision of estimates was similar between methods in both seasons. Frequentist and Bayesian estimates diverged for children in 2013/14. Under the frequentist approach, LAIV effectiveness was 62 percentage points lower than IIV, while LAIV was only 27 percentage points lower than IIV under the Bayesian approach.

Conclusion

Bayesian estimates of influenza VE can differ from frequentist estimates to a clinically meaningful degree when VE diverges substantially from previous seasons.
Appendix
Available only for authorised users
Literature
1.
go back to reference Jackson ML, Chung JR, Jackson LA, Phillips CH, Benoit J, Monto AS, Martin ET, Belongia EA, McLean HQ, Gaglani M, et al. Influenza vaccine effectiveness in the United States during the 2015-2016 season. N Engl J Med. 2017;377(6):534–43.CrossRef Jackson ML, Chung JR, Jackson LA, Phillips CH, Benoit J, Monto AS, Martin ET, Belongia EA, McLean HQ, Gaglani M, et al. Influenza vaccine effectiveness in the United States during the 2015-2016 season. N Engl J Med. 2017;377(6):534–43.CrossRef
2.
go back to reference Kissling E, Valenciano M, Pozo F, Vilcu AM, Reuss A, Rizzo C, Larrauri A, Horvath JK, Brytting M, Domegan L, et al. 2015/16 I-MOVE/I-MOVE+ multicentre case control study in Europe: moderate vaccine effectiveness estimates against influenza A(H1N1)pdm09 and low estimates against lineage mismatched influenza B among children. Influenza Other Respir Viruses. 2017;12:423–37. Kissling E, Valenciano M, Pozo F, Vilcu AM, Reuss A, Rizzo C, Larrauri A, Horvath JK, Brytting M, Domegan L, et al. 2015/16 I-MOVE/I-MOVE+ multicentre case control study in Europe: moderate vaccine effectiveness estimates against influenza A(H1N1)pdm09 and low estimates against lineage mismatched influenza B among children. Influenza Other Respir Viruses. 2017;12:423–37.
3.
go back to reference Pebody R, Warburton F, Ellis J, Andrews N, Potts A, Cottrell S, Reynolds A, Gunson R, Thompson C, Galiano M, et al. End-of-season influenza vaccine effectiveness in adults and children, United Kingdom, 2016/17. Euro Surveill. 2017;22(44):17–00306. Pebody R, Warburton F, Ellis J, Andrews N, Potts A, Cottrell S, Reynolds A, Gunson R, Thompson C, Galiano M, et al. End-of-season influenza vaccine effectiveness in adults and children, United Kingdom, 2016/17. Euro Surveill. 2017;22(44):17–00306.
4.
go back to reference Skowronski DM, Chambers C, Sabaiduc S, De Serres G, Winter AL, Dickinson JA, Gubbay JB, Drews SJ, Martineau C, Charest H, et al. Beyond antigenic match: possible agent-host and immuno-epidemiological influences on influenza vaccine effectiveness during the 2015-2016 season in Canada. J Infect Dis. 2017;216(12):1487–500.CrossRef Skowronski DM, Chambers C, Sabaiduc S, De Serres G, Winter AL, Dickinson JA, Gubbay JB, Drews SJ, Martineau C, Charest H, et al. Beyond antigenic match: possible agent-host and immuno-epidemiological influences on influenza vaccine effectiveness during the 2015-2016 season in Canada. J Infect Dis. 2017;216(12):1487–500.CrossRef
5.
go back to reference Sullivan SG, Chilver MB, Higgins G, Cheng AC, Stocks NP. Influenza vaccine effectiveness in Australia: results from the Australian sentinel practices research network. Med J Aust. 2014;201(2):109–11.CrossRef Sullivan SG, Chilver MB, Higgins G, Cheng AC, Stocks NP. Influenza vaccine effectiveness in Australia: results from the Australian sentinel practices research network. Med J Aust. 2014;201(2):109–11.CrossRef
6.
go back to reference Skrepnek GH. The contrast and convergence of Bayesian and frequentist statistical approaches in pharmacoeconomic analysis. Pharmacoeconomics. 2007;25(8):649–64.CrossRef Skrepnek GH. The contrast and convergence of Bayesian and frequentist statistical approaches in pharmacoeconomic analysis. Pharmacoeconomics. 2007;25(8):649–64.CrossRef
7.
go back to reference Greenland S. Bayesian perspectives for epidemiological research: I. Foundations and basic methods. Int J Epidemiol. 2006;35(3):765–75.CrossRef Greenland S. Bayesian perspectives for epidemiological research: I. Foundations and basic methods. Int J Epidemiol. 2006;35(3):765–75.CrossRef
8.
go back to reference Flannery B, Chung JR, Monto AS, Martin ET, Belongia EA, McLean HQ, Gaglani M, Murthy K, Zimmerman RK, Nowalk MP, et al. Influenza vaccine effectiveness in the United States during the 2016-2017 season. Clin Infect Dis. 2019;68(11):1798–806.CrossRef Flannery B, Chung JR, Monto AS, Martin ET, Belongia EA, McLean HQ, Gaglani M, Murthy K, Zimmerman RK, Nowalk MP, et al. Influenza vaccine effectiveness in the United States during the 2016-2017 season. Clin Infect Dis. 2019;68(11):1798–806.CrossRef
9.
go back to reference Davlin SL, Blanton L, Kniss K, Mustaquim D, Smith S, Kramer N, Cohen J, Cummings CN, Garg S, Flannery B, et al. Influenza activity - United States, 2015-16 season and composition of the 2016-17 influenza vaccine. MMWR Morb Mortal Wkly Rep. 2016;65(22):567–75.CrossRef Davlin SL, Blanton L, Kniss K, Mustaquim D, Smith S, Kramer N, Cohen J, Cummings CN, Garg S, Flannery B, et al. Influenza activity - United States, 2015-16 season and composition of the 2016-17 influenza vaccine. MMWR Morb Mortal Wkly Rep. 2016;65(22):567–75.CrossRef
10.
go back to reference Rolfes MA, Flannery B, Chung J, O'Halloran A, Garg S, Belongia EA, Gaglani M, Zimmerman R, Jackson ML, Monto AS, et al. Effects of influenza vaccination in the United States during the 2017-2018 Influenza season. Clin Infect Dis. 2019;69(11):1845-53. Rolfes MA, Flannery B, Chung J, O'Halloran A, Garg S, Belongia EA, Gaglani M, Zimmerman R, Jackson ML, Monto AS, et al. Effects of influenza vaccination in the United States during the 2017-2018 Influenza season. Clin Infect Dis. 2019;69(11):1845-53.
11.
go back to reference Garten R, Blanton L, Elal AIA, Alabi N, Barnes J, Biggerstaff M, Brammer L, Budd AP, Burns E, Cummings CN, et al. Update: influenza activity in the United States during the 2017-18 season and composition of the 2018-19 influenza vaccine. MMWR Morb Mortal Wkly Rep. 2018;67(22):634–42.CrossRef Garten R, Blanton L, Elal AIA, Alabi N, Barnes J, Biggerstaff M, Brammer L, Budd AP, Burns E, Cummings CN, et al. Update: influenza activity in the United States during the 2017-18 season and composition of the 2018-19 influenza vaccine. MMWR Morb Mortal Wkly Rep. 2018;67(22):634–42.CrossRef
12.
go back to reference Gaglani M, Pruszynski J, Murthy K, Clipper L, Robertson A, Reis M, Chung JR, Piedra PA, Avadhanula V, Nowalk MP, et al. Influenza vaccine effectiveness against 2009 pandemic influenza A(H1N1) virus differed by vaccine type during 2013-2014 in the United States. J Infect Dis. 2016;213(10):1546–56.CrossRef Gaglani M, Pruszynski J, Murthy K, Clipper L, Robertson A, Reis M, Chung JR, Piedra PA, Avadhanula V, Nowalk MP, et al. Influenza vaccine effectiveness against 2009 pandemic influenza A(H1N1) virus differed by vaccine type during 2013-2014 in the United States. J Infect Dis. 2016;213(10):1546–56.CrossRef
13.
go back to reference Jackson ML, Nelson JC. The test-negative design for estimating influenza vaccine effectiveness. Vaccine. 2013;31(17):2165–8.CrossRef Jackson ML, Nelson JC. The test-negative design for estimating influenza vaccine effectiveness. Vaccine. 2013;31(17):2165–8.CrossRef
14.
go back to reference Dobson AJ. An introduction to generalized linear models. London: Chapman and Hall; 1990.CrossRef Dobson AJ. An introduction to generalized linear models. London: Chapman and Hall; 1990.CrossRef
15.
go back to reference Gilks WR, Richardson S, Spiegelhalter DJ. Markov chain Monte Carlo in practice. London: Chapman & Hall; 1996. Gilks WR, Richardson S, Spiegelhalter DJ. Markov chain Monte Carlo in practice. London: Chapman & Hall; 1996.
16.
go back to reference Gilks WR, Best NG, Tan KKC. Adaptive rejection metropolis sampling with Gibbs sampling. Appl Stat. 1995;44:455–72.CrossRef Gilks WR, Best NG, Tan KKC. Adaptive rejection metropolis sampling with Gibbs sampling. Appl Stat. 1995;44:455–72.CrossRef
17.
go back to reference Spiegelhalter DJ, Myles JP, Jones DR, Abrams KR. Methods in health service research. An introduction to bayesian methods in health technology assessment. BMJ. 1999;319(7208):508–12.CrossRef Spiegelhalter DJ, Myles JP, Jones DR, Abrams KR. Methods in health service research. An introduction to bayesian methods in health technology assessment. BMJ. 1999;319(7208):508–12.CrossRef
18.
go back to reference Belongia EA, Kieke BA, Donahue JG, Greenlee RT, Balish A, Foust A, Lindstrom S, Shay DK. Effectiveness of inactivated influenza vaccines varied substantially with antigenic match from the 2004-2005 season to the 2006-2007 season. J Infect Dis. 2009;199(2):159–67.CrossRef Belongia EA, Kieke BA, Donahue JG, Greenlee RT, Balish A, Foust A, Lindstrom S, Shay DK. Effectiveness of inactivated influenza vaccines varied substantially with antigenic match from the 2004-2005 season to the 2006-2007 season. J Infect Dis. 2009;199(2):159–67.CrossRef
19.
go back to reference Darvishian M, Bijlsma MJ, Hak E, van den Heuvel ER. Effectiveness of seasonal influenza vaccine in community-dwelling elderly people: a meta-analysis of test-negative design case-control studies. Lancet Infect Dis. 2014;14(12):1228–39.CrossRef Darvishian M, Bijlsma MJ, Hak E, van den Heuvel ER. Effectiveness of seasonal influenza vaccine in community-dwelling elderly people: a meta-analysis of test-negative design case-control studies. Lancet Infect Dis. 2014;14(12):1228–39.CrossRef
20.
go back to reference Woodcock J. FDA introductory comments: clinical studies design and evaluation issues. Clin Trials. 2005;2(4):273–5.CrossRef Woodcock J. FDA introductory comments: clinical studies design and evaluation issues. Clin Trials. 2005;2(4):273–5.CrossRef
21.
go back to reference Centers for Disease C, Prevention. Prevention and control of seasonal influenza with vaccines. Recommendations of the advisory committee on immunization practices--United States, 2013–2014. MMWR Recomm Rep. 2013;62(RR-07):1–43. Centers for Disease C, Prevention. Prevention and control of seasonal influenza with vaccines. Recommendations of the advisory committee on immunization practices--United States, 2013–2014. MMWR Recomm Rep. 2013;62(RR-07):1–43.
22.
go back to reference Grohskopf LA, Sokolow LZ, Broder KR, Olsen SJ, Karron RA, Jernigan DB, Bresee JS. Prevention and control of seasonal influenza with vaccines. MMWR Recomm Rep. 2016;65(5):1–54.CrossRef Grohskopf LA, Sokolow LZ, Broder KR, Olsen SJ, Karron RA, Jernigan DB, Bresee JS. Prevention and control of seasonal influenza with vaccines. MMWR Recomm Rep. 2016;65(5):1–54.CrossRef
23.
go back to reference Caspard H, Mallory RM, Yu J, Ambrose CS. Live-attenuated influenza vaccine effectiveness in children from 2009 to 2015–2016: a systematic review and meta-analysis. Open Forum Infect Dis. 2017;4(3):ofx111.CrossRef Caspard H, Mallory RM, Yu J, Ambrose CS. Live-attenuated influenza vaccine effectiveness in children from 2009 to 2015–2016: a systematic review and meta-analysis. Open Forum Infect Dis. 2017;4(3):ofx111.CrossRef
Metadata
Title
Differences between Frequentist and Bayesian inference in routine surveillance for influenza vaccine effectiveness: a test-negative case-control study
Authors
Michael L. Jackson
Jill Ferdinands
Mary Patricia Nowalk
Richard K. Zimmerman
Burney Kieke
Manjusha Gaglani
Kempapura Murthy
Joshua G. Petrie
Emily T. Martin
Jessie R. Chung
Brendan Flannery
Lisa A. Jackson
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2021
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-021-10543-z

Other articles of this Issue 1/2021

BMC Public Health 1/2021 Go to the issue