American Association for Aerosol Research - Abstract Submission

AAAR 34th Annual Conference
October 12 - October 16, 2015
Hyatt Regency
Minneapolis, Minnesota, USA

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Development of a Sampling Strategy for Detecting Infectious Ebola Virus Aerosols

SHANNA RATNESAR-SHUMATE, Michael Schuit, Jill Matus, Stewart Wood, Kristin Bower, Paul Dabisch, NBACC

     Abstract Number: 616
     Working Group: Environmental Fate of Infectious Aerosols

Abstract
The potential for Ebola virus to be spread via aerosols is not well understood. Current best practices for preventing the spread of the virus in health care settings may be insufficient if aerosols containing the virus are being mechanically generated by manipulation of virus contaminated materials. Additionally, there is a concern that the Makona variant of Zaire Ebola virus associated with the current outbreak may be more stable in the environment than previous variants, potentially increasing the risk of infection via inhalation of mechanically generated aerosols. To assess the risk associated with Ebola virus containing aerosols in a laboratory or field setting, the best methods for detecting infectious aerosols need to be identified. NBACC is performing a study to assess the ability of a range of aerosol sampling technologies to preserve Ebola virus infectivity during aerosol collection. Ebola virus containing aerosols are being generated and delivered to two categories of samplers for evaluation – personal air samplers and high-volume air samplers. The sampling efficiency and concentration factors for each sampler are being evaluated using fluorescent microspheres prior to testing with virus. The retention of viral infectivity during sampling are being evaluated for each sampler as a function of time and collection media. Preliminary results of this study will be presented. The results of this study will aid in the development of an optimized sampling strategy for Ebola virus containing aerosols, which will be useful to inform future studies with the virus, including potential field sampling, and identify limitations in previous data generated with other sampling devices.