This analysis demonstrates the feasibility of estimating 4 components of vaccine efficacy simultaneously by using existing influenza challenge study data. Detailed, accurate, and reliable outcome data are needed to calculate these measures of vaccine efficacy with precision, and steps should be taken to incorporate the necessary data collection into the design of vaccine field trials, as noted before (1
). In addition, our classification of vaccine efficacy measures from community-based vaccine trials highlights additional ranges of efficacy estimates observed and the importance of specifying the exact component of vaccine efficacy that is being reported, both to assess comparability between studies and to facilitate a more thorough understanding of the components of vaccine efficacy.
We do not know of any community-based influenza vaccine trial that has provided estimates of all 4 vaccine efficacy components or of VEI
. It would be beneficial to design future phase III vaccine trials and phase IV vaccine studies to estimate all 4 components of vaccine efficacy. Better infection outcome measures could be used to separately estimate VES
. Inclusion of transmission groups, such as households, in the design could enable estimation of VEI
. All 4 components of protection have been successfully estimated for influenza antiviral agents from randomized household clinical trials (22
). In addition, Preziosi and Halloran (23
) have successfully estimated VEI
for pertussis vaccines.
Our estimates based on challenge study data indicate that live, attenuated influenza vaccine, as well as inactivated influenza vaccine, protected against influenza infection, VES, in seronegative adult volunteers. In addition, the point estimates for the absolute efficacy of live vaccine were higher for efficacy against symptomatic illness given infection, VEP, than for the inactivated vaccine, which resulted in a higher VESP for the live vaccine.
The challenge studies did not yield particularly useful information for valid estimation of VEI for either of these vaccines. Because of the difficulty of directly measuring the probability that an infected individual will infect a susceptible individual, studies such as this one often must use potential surrogate measures of infectiousness. The VEI estimates drawn from the challenge studies may be low for this very reason. Presence or absence of viral shedding was used as a surrogate measure of infectiousness, but information is lacking regarding its validity as a surrogate in this context, and it is likely that the dichotomous outcome does not fully capture an infected individual's ability to infect a susceptible individual. Furthermore, viral shedding was a component of the definition of laboratory-confirmed infection. Because VEI is estimated for only those with laboratory-confirmed infection, these definitions overlap significantly. It may be that more detailed characteristics of viral shedding, including average number of days of shedding or peak mean titer, would provide better estimates of VEI, and it would be beneficial to explore the usefulness of these measures. Yet, in the context of these challenge studies, neither of these outcomes would eliminate the issue stemming from the fact that viral shedding is part of the definition of laboratory-confirmed infection.
Overall, the combined efficacy, VEC, was consistently higher for the live vaccine when compared with the inactivated vaccine. VEC can remain high for these vaccines, with relatively low VEI as long as the other 2 measures of vaccine efficacy are relatively high.
Although these results provide significant insight into the specific components of vaccine efficacy, more data are needed to assess additional factors key to estimating vaccine efficacy under other conditions. By combining the information from the challenge studies and the phase III community-based vaccine trials and observational studies, we find evidence that the VESP
for the live vaccine is consistently higher than that for inactivated vaccine in children, but not necessarily in adults (11
). This disparity is probably due to prior immunity in adults, which is not present in very young children. The challenge studies included here were conducted among adults with little or no prior immunity to the challenge strain, which indicates that these results may also be somewhat applicable to children. The effects may be larger in children given that even adults seronegative for specific influenza strains have had greater previous exposure to seasonal influenza than young children have. In the event of an influenza pandemic caused by a novel influenza strain, everyone in the population should be immunologically naïve to the emergent strain. Because the challenge study data used in this analysis challenged only those adult volunteers who were seronegative to the challenge strain, these vaccine efficacy results could be applicable to a pandemic situation, although, again, the effect may be larger given the novelty of the pandemic strain.
The challenge studies all administered homologous strains of influenza during the challenge. We were unable to identify influenza challenge studies that met our selection criteria in which the challenge strain was heterologous to the vaccine strain; therefore, it was not possible to estimate efficacy measures from experimental challenge study data when the vaccine was poorly matched for comparison. There is significant interest in estimating vaccine efficacy for poorly matched strains because the prepandemic vaccines currently being developed will likely be poorly matched to the pandemic strain when a pandemic strain emerges. On the other hand, data from community-based trials in years when poorly matched strains of influenza circulated in the community can provide insight into how well influenza vaccines protect against poorly matched strains.
In the absence of reliable estimates from vaccine trials, the vaccine efficacy values given in could be used as rough guides in planning potential vaccination strategies for seasonal influenza in children and pandemic influenza in the community at large. This task could be accomplished by using mathematical models (10
), a subject for further research (25