title: A probability model for evaluating the bias and precision of influenza vaccine effectiveness estimates from case-control studies.
abstract: As influenza vaccination is now widely recommended, randomized clinical trials are no longer ethical in many populations. Therefore, observational studies on patients seeking medical care for acute respiratory illnesses (ARIs) are a popular option for estimating influenza vaccine effectiveness (VE). We developed a probability model for evaluating and comparing bias and precision of estimates of VE against symptomatic influenza from two commonly used case-control study designs: the test-negative design and the traditional case-control design. We show that when vaccination does not affect the probability of developing non-influenza ARI then VE estimates from test-negative design studies are unbiased even if vaccinees and non-vaccinees have different probabilities of seeking medical care against ARI, as long as the ratio of these probabilities is the same for illnesses resulting from influenza and non-influenza infections. Our numerical results suggest that in general, estimates from the test-negative design have smaller bias compared to estimates from the traditional case-control design as long as the probability of non-influenza ARI is similar among vaccinated and unvaccinated individuals. We did not find consistent differences between the standard errors of the estimates from the two study designs.
authors.affiliation: Department of Biostatistics and Bioinformatics,Rollins School of Public Health, Emory University,Atlanta,GA,USA.
authors.forename: M
authors.initials: M
authors.lastname: Haber
authors.affiliation: Department of Biostatistics and Bioinformatics,Rollins School of Public Health, Emory University,Atlanta,GA,USA.
authors.forename: Q
authors.initials: Q
authors.lastname: An
authors.affiliation: Influenza Division,Centers for Disease Control and Prevention,Atlanta,GA,USA.
authors.forename: I M
authors.initials: IM
authors.lastname: Foppa
authors.affiliation: Influenza Division,Centers for Disease Control and Prevention,Atlanta,GA,USA.
authors.forename: D K
authors.initials: DK
authors.lastname: Shay
authors.affiliation: Influenza Division,Centers for Disease Control and Prevention,Atlanta,GA,USA.
authors.forename: J M
authors.initials: JM
authors.lastname: Ferdinands
authors.affiliation: Department of Medicine,School of Medicine, Emory University,Atlanta,GA,USA.
authors.forename: W A
authors.initials: WA
authors.lastname: Orenstein
mesh_terms: D015982:Bias; D016022:Case-Control Studies; D006801:Humans; D009980:Influenza A virus / Q000276:immunology*; D007252:Influenza Vaccines / Q000276:immunology / Q000592:standards*; D007251:Influenza, Human / Q000517:prevention & control* / Q000821:virology; D008962:Models, Theoretical; D011336:Probability; D012107:Research Design; D014611:Vaccination / Q000592:standards*
chemical_list: D007252:Influenza Vaccines
keywords: statistics