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Quantitative Microbial Risk Assessment for Workers Exposed to Bioaerosol in Wastewater Treatment Plants Aimed at the Choice and Setup of Safety Measures

Biological risk assessment in occupational settings currently is based on either qualitative or semiquantitative analysis. In this study, a quantitative microbial risk assessment (QMRA) has been applied to estimate the human adenovirus (HAdV) health risk due to bioaerosol exposure in a wastewater tr...

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Detalles Bibliográficos
Autores principales: Carducci, Annalaura, Donzelli, Gabriele, Cioni, Lorenzo, Federigi, Ileana, Lombardi, Roberto, Verani, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069154/
https://www.ncbi.nlm.nih.gov/pubmed/30011925
http://dx.doi.org/10.3390/ijerph15071490
Descripción
Sumario:Biological risk assessment in occupational settings currently is based on either qualitative or semiquantitative analysis. In this study, a quantitative microbial risk assessment (QMRA) has been applied to estimate the human adenovirus (HAdV) health risk due to bioaerosol exposure in a wastewater treatment plant (WWTP). A stochastic QMRA model was developed considering HAdV as the index pathogen, using its concentrations in different areas and published dose–response relationship for inhalation. A sensitivity analysis was employed to examine the impact of input parameters on health risk. The QMRA estimated a higher average risk in sewage influent and biological oxidation tanks (15.64% and 12.73% for an exposure of 3 min). Sensitivity analysis indicated HAdV concentration as a predominant factor in the estimated risk. QMRA results were used to calculate the exposure limits considering four different risk levels (one illness case per 100, 1.000, 10.000, and 100.000 workers): for 3 min exposures, we obtained 565, 170, 54, and 6 GC/m(3) of HAdV. We also calculated the maximum time of exposure for each level for different areas. Our findings can be useful to better define the effectiveness of control measures, which would thus reduce the virus concentration or the exposure time.