10th International Aerosol Conference September 2 - September 7, 2018 America's Center Convention Complex St. Louis, Missouri, USA
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Strategies for the Deployment of a Bioaerosol Air Sampling Network Following a Wide Area Attack
JONATHAN THORNBURG, Paul Mobley, Jean Kim, Prakash Doraiswamy, Timothy Boe, John Archer, M. Worth Calfee, Leroy Mickelsen, Sang Don Lee, RTI International
Abstract Number: 1549 Working Group: Infectious Bioaerosol
Abstract Following the wide area release of a biological agent, like Bacillus anthracis, one source of uncertainty confronting decision makers is the degree to which reaerosolized organisms present a public health hazard. Bioaerosol sampling methods deployed as individual samplers or as an integrated network may provide federal agencies, like the U.S. Environmental Protection Agency, another option for responding to a wide area biological incident. This study assessed whether a bioaerosol sampling network could cost-effectively detect spores reaerosolized from urban surfaces.
We performed the air sampling network assessment in two phases. Both phases incorporated publicly available information on bioaerosol sampler performance, spore emission rates, meteorology, and estimated cost. The first phase used Excel models to assess the types of bioaerosol samplers that should be considered for the more detailed assessment. In the second phase, we developed a system performance model (SPM) in MATLAB to optimize the bioaerosol sampling network design for detection probability and minimize cost. We evaluated four different bioaerosol network strategies deployed in two cities, Denver, CO and New York City.
Phase 1 results determined that current commercially available point and stand-off, real-time bioaerosol sensors do not have the sensitivity to detect resuspended spores. Calculated bioaerosol concentrations, even near the point of resuspension, were always less than 1000 agent containing particles per liter. Therefore, we developed four bioaerosol network strategies based on 1) low flow filter samplers, 2) high flow filter samplers, 3) native samples like building ventilation filters, and 4) a combination of the three. Preliminary Phase 2 results using the SPM found that a ratio of 1:4 high flow to low flow samplers, 80 total, detected bioaerosol concentrations less than 10 colony forming units per cubic meter for up to 30 days following an attack. A significantly higher density network comprised solely high flow or low flow samplers provided equivalent detection capability but also doubled the period of detection. These results were based on a limited range of spore resuspension rates, human activity levels, and meteorological conditions. Further work will expand the range of data inputs and include strategy 3. The outcome will be an optimized network design for each city to provide the highest probability of bioaerosol detection for the maximum time period balanced against the cost of the network.