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Four household-based, randomized clinical trials, two each of zanamivir and oseltamivir, were designed primarily to estimate the effect of postexposure prophylaxis on preventing influenza illness in household contacts. However, the effect of influenza antivirals on infectiousness as well as on the ability of the virus to cause disease—the pathogenicity—have important public health consequences. The authors show how such studies can provide estimates of pathogenicity, antiviral efficacy for pathogenicity, and the antiviral effect on infectiousness. Analysis of the four studies confirmed the high prophylactic efficacy against illness of both zanamivir (75%, 95% confidence interval (CI): 54, 86) and oseltamivir (81%, 95% CI: 35, 94). The effect on reducing infectiousness was 19% (95% CI: −160, 75) for zanamivir and 80% (95% CI: 43, 93) for oseltamivir. Pathogenicity in controls ranged from 44% (95% CI: 33, 55) to 66% (95% CI: 48, 72). Efficacy in reducing pathogenicity for zanamivir was 52% (95% CI: 19, 72) and 56% (95% CI: 14, 77) in the two studies; for oseltamivir, it was 56% (95% CI: 10, 73) and 79% (95% CI: 45, 92). Studies of influenza antivirals in transmission units would be improved if randomization schemes were used that allow estimation of the antiviral effect on infectiousness from individual studies. [ABSTRACT FROM AUTHOR]

Antiviral agents are an important component in mitigation/containment strategies for pandemic influenza. However, most research for mitigation/containment strategies relies on the antiviral efficacies evaluated from limited data of clinical trials. Which efficacy measures can be reliably estimated from these studies depends on the trial design, the size of the epidemics, and the statistical methods. We propose a Bayesian framework for modeling the influenza transmission dynamics within households. This Bayesian framework takes into account asymptomatic infections and is able to estimate efficacies with respect to protecting against viral infection, infection with clinical disease, and pathogenicity (the probability of disease given infection). We use the method to reanalyze 2 clinical studies of oseltamivir, an influenza antiviral agent, and compare the results with previous analyses. We found significant prophylactic efficacies in reducing the risk of viral infection and infection with disease but no prophylactic efficacy in reducing pathogenicity. We also found significant therapeutic efficacies in reducing pathogenicity and the risk of infection with disease but no therapeutic efficacy in reducing the risk of viral infection in the contacts. [ABSTRACT FROM AUTHOR]

In this paper, the authors provide estimates of 4 measures of vaccine efficacy for live, attenuated and inactivated influenza vaccine based on secondary analysis of 5 experimental influenza challenge studies in seronegative adults and community-based vaccine trials. The 4 vaccine efficacy measures are for susceptibility (VES), symptomatic illness given infection (VEP), infection and illness (VESP), and infectiousness (VEI). The authors also propose a combined (VEC) measure of the reduction in transmission in the entire population based on all of the above efficacy measures. Live influenza vaccine and inactivated vaccine provided similar protection against laboratory-confirmed infection (for live vaccine: VES  = 41%, 95% confidence interval (CI): 15, 66; for inactivated vaccine: VES  = 43%, 95% CI: 8, 79). Live vaccine had a higher efficacy for illness given infection (VEP  = 67%, 95% CI: 24, 100) than inactivated vaccine (VEP  = 29%, 95% CI: −19, 76), although the difference was not statistically significant. VESP for the live vaccine was higher than for the inactivated vaccine. VEI estimates were particularly low for these influenza vaccines. VESP and VEC can remain high for both vaccines, even when VEI is relatively low, as long as the other 2 measures of vaccine efficacy are relatively high. [ABSTRACT FROM AUTHOR]

We developed a general procedure for estimating the transmission probability adjusting for covariates when susceptibles are exposed to several infectives concurrently and taking correlation within transmission units into account. The procedure is motivated by a study estimating efficacy of pertussis vaccination based on the secondary attack rate in a rural sub-Saharan community (Niakhar, Senegal) and illustrated with simulations. The procedure is also appropriate to estimate the pairwise transmission probability in transmission studies of live vaccine virus in a collection of transmission units, such as day-care centres or retirement centres. Previously, analyses either excluded transmission units with multiple infectives or ignored co-infectives. Excluding transmission units with multiple infectives is statistically less efficient and ignoring co-infectives can lead to biased estimation. Modelling is carried out by regressing the latent pairwise transmission probability from each infective to a susceptible on covariates and specifying a transmission linkage function linking the latent pairwise transmission probability to the overall transmission probability. Parameters are estimated using Markov chain Monte Carlo methods. Copyright © 2003 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]