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Background Candida auris is an emerging pathogen responsible for several outbreaks within healthcare facilities. It can be found on hospital surfaces and patient care devices. UV- C sanitisation may constitute an effective adjunct to routine room cleaning to prevent the spreading of this yeast. Previous findings with this technology suggest to investigate different sources of variability in the study of the biocidal effect of UV devices on C. auris. In this study we develop a computer simulation of surface distribution of microorganisms on a stainless steel carrier, to optimize UV-device experiments. Methods Based on the literature about C. auris studies and its estimated average size (about 5 μm diameter), several Matlab simulations have been performed to include as many microorganisms as possible to be ideally placed on a 20 cm2 stainless steel support, avoiding cell overlapping. This was done in order to maximize the effectiveness of UV exposure. Results Two initial simulations were performed to evaluate a random arrangement of a very large number of microorganisms (8x107 CFU) on the steel support, widely overlapped. In this case, due to the poor UV-C penetrability, we would not exceed two log10 reduction. By randomly distributing 1x106 CFU, the probability of overlapping was about 1.3%, but even a partial overlap limits the log10 reduction. By randomly distributing 1x105 CFU, the overlaps were at least 10 times less likely. Conclusions The simulation results allowed us to evaluate the most appropriate microorganism distribution model able to optimize the biocidal effects of UV-C devices. The overlapping of microorganisms reduces UV-C penetrability. Our simulated study is consistent with literature results where we observed a lower log-reduction by increasing the concentration of microorganisms and therefore the probability of overlapping. The resulting model would simulate any log-reduction scenario, at any distance and any concentration, with and without overlapping. Key messages The complete or partial microorganism overlapping plays a relevant role in the outcome of UV-C biocidal experiments. To identify the exponential CFU reduction curve and estimate accurately the inactivation rate constant, simulated experiments should be performed to assess the real effectiveness of UV devices.

A simulation model of microbe overlapping for the correct estimation of UV-C device log-reduction