Oral: Development and Optimization of a UVC Disinfection Device for Hospital Use
ORAL
Abstract
Candida auris has emerged as a serious global health threat due to its resistance to antifungal treatments and the challenges of eradication it in hospitals. Outbreaks have been reported in Brazil, the United States, and Europe, where its rapid spread poses significant risks, particularly for immunocompromised patients. To address this issue, we developed a portable UVC disinfection chamber operating at a wavelength of 254 nm, which effectively eliminates 98% of C. auris in 5 minutes.
The device’s efficacy was validated through rigorous lab testing, with performance enhanced by computational simulations modeling UVC light interactions on different surfaces. These simulations were crucial for optimizing parameters like light intensity and incidence angle, ensuring uniform coverage, and reducing shadowed areas that could hinder disinfection. We developed an efficient and safe system that minimizes operator exposure to harmful radiation by integrating optical modeling with experimental data.
We are refining the device and expanding tests to target additional pathogens, including the COVID-19 virus and multidrug-resistant bacteria, broadening its potential applications in healthcare settings.
The device’s efficacy was validated through rigorous lab testing, with performance enhanced by computational simulations modeling UVC light interactions on different surfaces. These simulations were crucial for optimizing parameters like light intensity and incidence angle, ensuring uniform coverage, and reducing shadowed areas that could hinder disinfection. We developed an efficient and safe system that minimizes operator exposure to harmful radiation by integrating optical modeling with experimental data.
We are refining the device and expanding tests to target additional pathogens, including the COVID-19 virus and multidrug-resistant bacteria, broadening its potential applications in healthcare settings.
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Presenters
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Elyson L Ramos
Universidade de Pernambuco
Authors
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Elyson L Ramos
Universidade de Pernambuco
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Heitor D Costa
University of Pernambuco
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Isabella N Wanderley
University of Pernambuco
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André M Vilela
University of Pernambuco, Universidade de Pernambuco, Data Science and Analytics, SUNY Polytechnic Institute, Utica, NY 13502, USA
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Gilvania L. S. Vilela
Universidade de Pernambuco, University of Pernambuco