The three treatment groups will be compared using logistic regression with covariates of study location, age, gender, antibiotic type and doses, hypoalbuminemia, and compromised immune system. Model selection based on the Akaike Information Criterion will be used to select covariates in final models. The treatment groups will also be compared without covariate adjustment. As needed, missing data will be handled using multiple imputation after assessment of missing at random considerations. Dependent and independent variables in planned analyses will be included in imputations along with any auxiliary variables thought to be potentially related to predicting the missing data. In addition, in order to include other auxiliary covariates in the imputations that are potentially related to missingness, logistic regression will be performed with the dependent variable missing/not missing. Only imputed values of independent variables will be used in the analyses. Multiple imputation will be performed with the R package mi.