Bacterial Transmission Dynamics Study

Overview

Infections with multiply antibiotic-resistant bacteria represent a major cause of preventable morbidity and mortality amongst hospitalized neonates worldwide. In Southeast Asia, where antibiotic-resistance is a major problem, Gram-negative bacteria account for the majority of such infections. The most common pathogens are Acinetobacter spp., Pseudomonas aeruginosa, Enterobacter spp., Escherichia coli and Klebsiella pneumonia. The great majority of infections with these pathogens represent asymptomatic carriage, though in the absence of routine screening for asymptomatic carriage reliable estimates of the prevalence, rates of transmission between patients, and rates of importation from the community are lacking. Moreover, current understanding of the degree and manner in which different antibiotics act to select for such resistant organisms is rudimentary.

Objectives: To quantify the prevalence of drug-resistant Gram-negative pathogens on admission to a neonatal intensive care unit and during subsequent days of hospital stay. To quantify rates of patient-to-patient transmission for key organisms, to characterize how patient antibiotic use impacts on the ward-level dynamics of such organisms. Methods: All infants admitted to the unit over a period of one year for whom the parent/guardian gives informed consent will be included. In addition to routine demographic and clinical data for included patients, full patient-level data on antibiotic use within the ward will also be recorded. Carriage of resistant Gram-negative organisms will be determined though rectal swabs, tracheal aspirates (for ventilated patients) and stool samples taken on admission and at twice weekly intervals. Antibiotic-resistant Gram-negative bacteria will be cultured and their resistant patterns determined. Selected environmental surfaces will also be sampled to detect contamination with such organisms. For the most important organisms (Acinetobacter spp. and Klebsiella spp.) whole genome sequencing will be used in conjunction with Bayesian data augmentation techniques to determine transmission pathways and the impact of antibiotic use on the transmission and persistence of such organisms within the hospital ward.

Conditions