Journal
EPIDEMIOLOGY AND INFECTION
Volume 143, Issue 7, Pages 1417-1426Publisher
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0950268814002179
Keywords
Influenza vaccines; mathematical modelling; statistics
Funding
- National Institute of Allergies and Infectious Diseases of the National Institutes of Health (NIH) [R01AI110474]
- Centers for Disease Controls and Prevention (CDC)
- IPA [1110376-05]
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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.
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