A Bennett1, S Parks. 1. Centre for Emergency Preparedness and Response, Health Protection Agency, Porton Down, Salisbury, UK. allan.bennett@hpa.org.uk
Abstract
AIM: To quantify microbial aerosols generated by a series of laboratory accidents and to use these data in risk assessment. METHODS AND RESULTS: A series of laboratory accident scenarios have been devised and the microbial aerosol generated by them has been measured using a range of microbial air samplers. The accident scenarios generating the highest aerosol concentrations were, dropping a fungal plate, dropping a large bottle, centrifuge rotor leaks and a blocked syringe filter. Many of these accidents generated low particle size aerosols, which would be inhaled into the lungs of any exposed laboratory staff. Spray factors (SFs) have been calculated using the results of these experiments as an indicator of the potential for accidents to generate microbial aerosols. Model risk assessments have been described using the SF data. CONCLUSIONS: Quantitative risk assessment of laboratory accidents can provide data that can aid the design of containment laboratories and the response to laboratory accidents. SIGNIFICANCE AND IMPACT OF THE STUDY: A methodology has been described and supporting data provided to allow microbiological safety officers to carry out quantitative risk assessment of laboratory accidents.
AIM: To quantify microbial aerosols generated by a series of laboratory accidents and to use these data in risk assessment. METHODS AND RESULTS: A series of laboratory accident scenarios have been devised and the microbial aerosol generated by them has been measured using a range of microbial air samplers. The accident scenarios generating the highest aerosol concentrations were, dropping a fungal plate, dropping a large bottle, centrifuge rotor leaks and a blocked syringe filter. Many of these accidents generated low particle size aerosols, which would be inhaled into the lungs of any exposed laboratory staff. Spray factors (SFs) have been calculated using the results of these experiments as an indicator of the potential for accidents to generate microbial aerosols. Model risk assessments have been described using the SF data. CONCLUSIONS: Quantitative risk assessment of laboratory accidents can provide data that can aid the design of containment laboratories and the response to laboratory accidents. SIGNIFICANCE AND IMPACT OF THE STUDY: A methodology has been described and supporting data provided to allow microbiological safety officers to carry out quantitative risk assessment of laboratory accidents.
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Authors: Nancy E Cornish; Nancy L Anderson; Diego G Arambula; Matthew J Arduino; Andrew Bryan; Nancy C Burton; Bin Chen; Beverly A Dickson; Judith G Giri; Natasha K Griffith; Michael A Pentella; Reynolds M Salerno; Paramjit Sandhu; James W Snyder; Christopher A Tormey; Elizabeth A Wagar; Elizabeth G Weirich; Sheldon Campbell Journal: Clin Microbiol Rev Date: 2021-06-09 Impact factor: 50.129