Modelling and forecasting antimicrobial resistance and its dynamic relationship to antimicrobial use: a time series analysis

Abstract

To investigate the relationship between antimicrobial use and resistance in our hospital, we collected antimicrobial susceptibility and use data from existing microbiology laboratory and pharmacy databases for the period July 1st, 1991-December 31, 1998. The data was analyzed as time series and autoregressive integrated moving average (Box-Jenkins) and transfer function models were built. By using this method, we were able to demonstrate a temporal relationship between antimicrobial use and resistance, to quantify the effect of use on resistance and to estimate the delay between variations of use and subsequent variations in resistance. The results obtained for two antimicrobial-microorganism combinations: ceftazidime-gram-negative bacilli and imipenem-Pseudomonas aeruginosa, are shown as examples.