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.

journal_name

Epidemiol Infect

authors

Haber M,An Q,Foppa IM,Shay DK,Ferdinands JM,Orenstein WA

doi

10.1017/S0950268814002179

subject

Has Abstract

pub_date

2015-05-01 00:00:00

pages

1417-26

issue

7

eissn

0950-2688

issn

1469-4409

pii

S0950268814002179

journal_volume

143

pub_type

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