Analysis of surfaces for characterization of fungal burden

• Autor(a) principal: Viegas, Carla
• Data de Publicação: 2016
• Outros Autores: Faria, Tiago, Meneses, Márcia, Carolino, Elisabete, Viegas, Susana, Gomes, Anita Quintal, Sabino, Raquel
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://doi.org/10.13075/ijomeh.1896.00562
• topic: Air samples; Fungal burden assessment; High fungal load settings; Low fungal load settings; Occupational environments; Surface samples; Public Health, Environmental and Occupational Health; SDG 3 - Good Health and Well-being

Objectives: Mycological contamination of occupational environments can be a result of fungal spores' dispersion in the air and on surfaces. Therefore, it is very important to assess it in both types of the samples. In the present study we assessed fungal contamination in the air and in the surface samples to show relevance of surfaces sampling in complementing the results obtained in the air samples. Material and Methods: In total, 42 settings were assessed by the analysis of air and surfaces samples. The settings were divided into settings with a high fungal load (7 poultry farms and 7 pig farms, 3 cork industries, 3 waste management plants, 2 wastewater treatment plants and 1 horse stable) and a low fungal load (10 hospital canteens, 8 college canteens and 1 maternity hospital). In addition to culture-based methods, molecular tools were also applied to detect fungal burden in the settings with a higher fungal load. Results: From the 218 sampling sites, 140 (64.2%) presented different species in the examined surfaces when compared with the species identified in the air. A positive association in the high fungal load settings was found between the presence of different species in the air and surfaces. Wastewater treatment plants constituted the setting with the highest number of different species between the air and surface. Conclusions: We observed that surfaces sampling and application of molecular tools showed the same efficacy of species detection in high fungal load settings, corroborating the fact that surface sampling is crucial for a correct and complete analysis of occupational scenarios.