Statistical analysis
Data were collected electronically, with laboratory results pushed onto the database once they were available. Data collection tablets included range and consistency checks. Statistical analyses were done according to an a priori statistical analysis plan by means of R version 4.0.2 (R Development Core Team, Vienna, Austria) and GraphPad Prism version 9.0.0 (Graph-Pad Software, San Diego, CA, USA). Non-normally distributed quantitative measurements are summarised by the median (IQR). Exact binomial CIs are reported for estimated proportions. For the primary analysis, the binary response of experimental carriage was compared between study groups by means of a log-binomial model adjusting for inoculation dose group.Our revised power calculation assumed the overall carriage proportions to be 5% (on the basis of observed, masked data at the time of protocol amendment) in the 20 000 CFUs per naris inoculation dose group, 27% in the 80 000 CFUs per naris dose group, and 48% in the 160 000 CFUs per naris dose group. We planned to detect a relative reduction of 60% in the percentage of PCV13 randomly assigned participants becoming experimental carriers compared with the saline randomly assigned individuals. With a total sample size of 200 individuals we calculated (using simulation) that we had 74% power to detect this difference. The code for the The log-binomial model provides a direct estimation of the relative risk (RR) associated with the different predictor variables and, as such, has been recommended for use in randomised clinical trials.Categorical variables were compared by means of Fisher's exact test. A p value of less than 0·05 was considered significant; all p values are two tailed. The 