On the bias of estimates of influenza vaccine effectiveness from test–negative studies

Abstract

Estimates of the effectiveness of influenza vaccines are commonly obtained from a test-negative design (TND) study, where cases and controls are patients seeking care for an acute respiratory illness who test positive and negative, respectively, for influenza infection. Vaccine effectiveness (VE) estimates from TND studies are usually interpreted as vaccine effectiveness against medically-attended influenza (MAI). However, it is also important to estimate VE against any influenza illness (symptomatic influenza (SI)) as individuals with SI are still a public health burden even if they do not seek medical care. We present a numerical method to evaluate the bias of TND-based estimates of influenza VE with respect to MAI and SI. We consider two sources of bias: (a) confounding bias due to a (possibly unobserved) covariate that is associated with both vaccination and the probability of the outcome of interest and (b) bias resulting from the effect of vaccination on the probability of seeking care. Our results indicate that (a) VE estimates may suffer from substantial confounding bias when a confounder has a different effect on the probabilities of influenza and non-influenza ARI, and (b) when vaccination reduces the probability of seeking care against influenza ARI, then estimates of VE against MAI may be unbiased while estimates of VE against SI may be have a substantial positive bias.

Influenza epidemiology in patients admitted to sentinel Australian hospitals in 2017: the Influenza Complications Alert Network (FluCAN)

“…Estimates of vaccine effectiveness may be biased if an unmeasured confounder disproportionately affects the probability of influenza, compared to non-influenza respiratory illnesses. 31 In summary, we detected a large number of hospital admissions with laboratory-confirmed influenza in a national observational study in 2017, which was much larger than in any previous season under surveillance since 2010. A consistent finding over several years is that a high proportion of patients with severe influenza, and almost all deaths, occurred in patients with chronic comorbidities.…”

Influenza Vaccine Effectiveness: New Insights and Challenges

“…VE estimates can be generalized to the entire study population as long as VE does not vary by health-care-seeking behavior (Jackson and Nelson 2013). However, VE against medically attended influenza may overestimate VE against symptomatic influenza if vaccination reduces both influenza severity and the probability of seeking care for ILI (Ainslie et al 2017).…”

“…Bias can occur if disease or symptom severity is associated with vaccination status, and symptom severity is different for influenza cases and test-negative participants (Ainslie et al 2017;Lewnard et al 2018). The TND has other potential sources of bias that may be important.…”

Cost of inappropriate antimicrobial use for upper respiratory infection in Japan

“…The Japanese healthcare system generally secures 'free access' to healthcare services, regardless of facility level, and there is no limitation on the frequency of ambulatory care visit [18]. This implies that a larger number of URI patients tends to visit ambulatory care although URI is basically a self-limited disease and there are substantial numbers of URI patients amongst patients admitted to healthcare facilities [19,20]. This fact makes it more difficult to compare the proportion of URI cases prescribed antibiotics prescribed.…”