A space–time model for carbapenemase-producing Klebsiella pneumoniae (KPC) cluster quantification in a high-complexity hospital

Abstract

SUMMARYA retrospective space–time permutation model with non-Euclidean distance criteria was applied within a high-complexity hospital setting to quantitatively explore cluster patterns of 273 patients infected with or colonized by carbapenemase-producing Klebsiella pneumoniae during 4 years. Results were compared to standard nosocomial active-surveillance methods. Two clusters were identified in the period, suggesting that space–time strategies for cluster quantification within confined environments may be useful.