Document Detail

Validation and Application of Models to Predict Facemask Influenza Contamination in Healthcare Settings.
MedLine Citation:
PMID:  24593662     Owner:  NLM     Status:  Publisher    
Facemasks are part of the hierarchy of interventions used to reduce the transmission of respiratory pathogens by providing a barrier. Two types of facemasks used by healthcare workers are N95 filtering facepiece respirators (FFRs) and surgical masks (SMs). These can become contaminated with respiratory pathogens during use, thus serving as potential sources for transmission. However, because of the lack of field studies, the hazard associated with pathogen-exposed facemasks is unknown. A mathematical model was used to calculate the potential influenza contamination of facemasks from aerosol sources in various exposure scenarios. The aerosol model was validated with data from previous laboratory studies using facemasks mounted on headforms in a simulated healthcare room. The model was then used to estimate facemask contamination levels in three scenarios generated with input parameters from the literature. A second model estimated facemask contamination from a cough. It was determined that contamination levels from a single cough (≈19 viruses) were much less than likely levels from aerosols (4,473 viruses on FFRs and 3,476 viruses on SMs). For aerosol contamination, a range of input values from the literature resulted in wide variation in estimated facemask contamination levels (13-202,549 viruses), depending on the values selected. Overall, these models and estimates for facemask contamination levels can be used to inform infection control practice and research related to the development of better facemasks, to characterize airborne contamination levels, and to assist in assessment of risk from reaerosolization and fomite transfer because of handling and reuse of contaminated facemasks.
Edward M Fisher; John D Noti; William G Lindsley; Francoise M Blachere; Ronald E Shaffer
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-3-4
Journal Detail:
Title:  Risk analysis : an official publication of the Society for Risk Analysis     Volume:  -     ISSN:  1539-6924     ISO Abbreviation:  Risk Anal.     Publication Date:  2014 Mar 
Date Detail:
Created Date:  2014-3-5     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8109978     Medline TA:  Risk Anal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
© 2014 Society for Risk Analysis Published 2014. This article is a U.S. Government work and is in the public domain for the U.S.A.
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