We would like to have at least 80% power to detect a 30% reduction (i.e. r=0.7) in the relative risk between intervention 2 (or intervention 3) and intervention 1 (anticipated P=0.2), with a 5% type I error rate. Using the formula given above we calculate that we would require the randomization of 840 household contacts into each arm of the study. Allowing for a 25% dropout rate following randomization, we would require the randomization of 840 household contacts into each study arm corresponding to a total study requirement of 2,520 household contacts in 900 households. Thus we will recruit a total of 3,420 individuals including 900 index cases with positive results on the QuickVue rapid diagnostic test, and 2,520 household contacts. The specified sample size would also have high statistical power to detect larger relative risk reductions if the observed secondary attack ratio were lower (Table 1) . To achieve this sample size, we would need to recruit approximately 6,000 suspected influenza cases and follow-up those who meet the specific criteria (in the majority of recruited subjects this would be a positive result on the QuickVue Influenza A+B rapid diagnostic test), and our reasoning is as follows. During the peak season we would conservatively anticipate that 50% of subjects with ILI symptoms, as we have defined these above, are infected with influenza rather than another virus (3,000 of the 6,000 tested). Recent international oseltamivir trials found that during the influenza peak season the proportion of subjects with influenza-like-illness who had confirmed influenza was 60% [29] and 66% [30] . Allowing for a sensitivity of 79% for the QuickVue test, only 2,370 index cases would be correctly identified (the remainder would be misclassified as false negatives). Given the estimated specificity of the QuickVue test of 92%, testing the 3,000 non-influenza index cases would result in misclassification of 240 subjects without influenza (false positives), and their households would also be visited. While the specificity of the symptom-based definition in 4(d) is likely to be lower, the sensitivity may be higher and with symptom-based recruitment only occurring in a small number of sites the approximate calculation above is appropriate. Thus we anticipate that we would need to recruit approximately 6,000 index cases with ILI symptoms and apply the specific criteria (typically the rapid diagnostic test), of who 1,477 (2,370+240) would meet our criteria and be subject to randomization and follow-up. Given the intention-to-treat approach, randomization and follow-up of some non-influenza cases is an expected consequence of the speed required by this study.