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INTRODUCTION: Mobile phones act as fomites that pose a global public health risk of disseminating microorganisms, including highly pathogenic strains possessing antimicrobial resistances. The use of ultraviolet-C (UV-C) to sanitise mobile phones presents an alternative means to complement basic hand hygiene to prevent the cross-contamination and dissemination of microorganisms between hands and mobile phones. AIM: This study aimed to evaluate the germicidal efficacy of the Glissner CleanPhone UV-C phone sanitiser (Glissner) device. METHODS: Two experimental trials were performed for the evaluation of the CleanPhone (Glissner). The first was a controlled trial, where the germicidal efficacy of the CleanPhone was evaluated against six different microorganism species that were inoculated onto mobile phones. The second was a field trial evaluating the germicidal efficacy of the CleanPhone on 100 volunteer mobile phones. Efficacy was determined based on colony counts of microorganisms on Columbia sheep blood agar before and after UV-C treatment. RESULTS: In the controlled trial, reduction in growth was observed for all microorganisms after UV-C treatment with ST131 Escherichia coli showing the highest growth reduction at 4 log10 CFU/mL followed by C. albicans and ATCC E. coli at 3 log10 CFU/mL. An overall reduction in microorganism growth after UV-C treatment was also observed for the field trial, with an average growth reduction of 84.4% and 93.6% in colony counts at 24 h and 48 h post-incubation, respectively. CONCLUSION: The findings demonstrated the capability of the CleanPhone (Glissner) to rapidly sanitise mobile phones, thereby providing a means to reduce the potential dissemination of microorganisms, including highly pathogenic strains with antimicrobial resistance.
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Success in the global fight against antimicrobial resistance (AMR) is likely to improve if surveillance can be performed on an epidemiological scale. An approach based on agars with incorporated antimicrobials has enormous potential to achieve this. However, there is a need to identify the combinations of selective agars and key antimicrobials yielding the most accurate counts of susceptible and resistant organisms. A series of experiments involving 1,202 plates identified the best candidate combinations from six commercially available agars and five antimicrobials, using 18 Escherichia coli strains as either pure cultures or inocula-spiked feces. The effects of various design factors on colony counts were analyzed in generalized linear models. Without antimicrobials, Brilliance E. coli and CHROMagar ECC agars yielded 28.9% and 23.5% more colonies, respectively, than MacConkey agar. The order of superiority of agars remained unchanged when fecal samples with or without spiking of resistant E. coli strains were inoculated onto agars with or without specific antimicrobials. When antimicrobials were incorporated at various concentrations, it was revealed that ampicillin, tetracycline, and ciprofloxacin were suitable for incorporation into Brilliance and CHROMagar agars at all defined concentrations. Gentamicin was suitable for incorporation only at 8 and 16 µg/ml, while ceftiofur was suitable only at 1 µg/ml. CHROMagar extended-spectrum ß-lactamase (ESBL) agar supported growth of a wider diversity of extended-spectrum-cephalosporin-resistant E. coli strains. The findings demonstrate the potential for agars with incorporated antimicrobials to be combined with laboratory-based robotics to deliver AMR surveillance on a vast scale with greater sensitivity of detection and strategic relevance. IMPORTANCE Established models of surveillance for AMR in livestock typically have a low sampling intensity, which creates a tremendous barrier to understanding the variation of resistance among animal and food enterprises. However, developments in laboratory robotics now make it possible to rapidly and affordably process large volumes of samples. Combined with modern selective agars incorporating antimicrobials, this forms the basis of a novel surveillance process for identifying resistant bacteria by chromogenic reactions, including accurately detecting and quantifying the presence of bacteria even when they are present at low concentrations. Because Escherichia coli is a widely preferred indicator bacterium for AMR surveillance, this study identifies the optimal selective agar for quantifying resistant E. coli strains by assessing the growth performance on agars with antimicrobials. The findings are the first step toward exploiting laboratory robotics in an up-scaled approach to AMR surveillance in livestock, with wider adaptations in food, clinical microbiology, and public health.
