Filters from taxis air conditioning system: A tool to characterize driver's occupational exposure to bioburden?

Carla Viegas, Ana Monteiro, Mateus dos Santos, Tiago Faria, Liliana Aranha Caetano, Elisabete Carolino, Anita Quintal Gomes, Geneviève Marchand, Nancy Lacombe, Susana Viegas

Index: 10.1016/j.envres.2018.03.032

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Abstract

Bioburden proliferation in filters from air conditioning systems of taxis represents a possible source of occupational exposure. The aim of this study was to determine the occurrence of fungi and bacteria in filters from the air conditioning system of taxis used for patient transportation and to assess the exposure of drivers to bioburden. Filters from the air conditioning systems of 19 taxis and 28 personal vehicles (used as controls) operating in three Portuguese cities including the capital Lisbon, were collected during the winter season. The occurrence and significance of bioburden detected in the different vehicles are reported and discussed in terms of colony-forming units (CFU) per 1 m2 of filter area and by the identification of the most frequently detected fungal isolates based on morphology. Azole-resistant mycobiota, fungal biomass, and molecular detection of Aspergillus species/strains were also determined. Bacterial growth was more prevalent in taxis (63.2%) than in personal vehicles (26.3%), whereas fungal growth was more prevalent in personal vehicles (53.6%) than in taxis (21.1–31.6%). Seven different azole-resistant species were identified in this study in 42.1% taxi filters. Levels of fungal biomass were above the detection limit in 63% taxi filters and in 75% personal vehicle filters. No toxigenic species were detected by molecular analysis in the assessed filters. The results obtained show that bioburden proliferation occurs widely in filters from the air conditioning systems of taxis, including the proliferation of azole-resistant fungal species, suggesting that filters should be replaced more frequently. The use of culture based-methods and molecular tools combined enabled an improved risk characterization in this setting.