The laboratory definition of influenza will be preferentially used as the primary outcome measure, but when this is unavailable we will use the clinical definition. In the pilot study, index cases and household contacts with missing data on important predictors will be excluded from analyses. In the main study, we will use multiple imputation [31] with 10 imputed datasets to replace missing values on outcome and predictor variables. If 10 imputed datasets are not sufficient to ensure stability of estimates we will use 20 imputed datasets. Multiple imputation makes maximum use of available data and maximises statistical power while requiring less strict theoretical assumptions than to a complete case analysis, or single imputation of mean values. We note that this is now one of the preferred (and standard) methods for analysing clinical trials data [32] .