AAAR 33rd Annual Conference
October 20 - October 24, 2014
Rosen Shingle Creek
Orlando, Florida, USA
Abstract View
Development and Application of a Markov Chain Model for Predicting Influenza Risk and Control in an Office Environment
PARHAM AZIMI, Brent Stephens, Illinois Institute of Technology
Abstract Number: 73 Working Group: Linking Aerosols with Public Health in a Changing World
Abstract Exposure to airborne pathogens such as influenza remains a significant threat to public health. However, influenza transmission and control in indoor environments remains poorly understood, as it is not clear which routes of transmission (fomite, inhalation, inspiration or direct spray) are dominant. The transmission risk associated with each route in indoor environments is a function of many variables, including, ventilation rates, the number of infector individuals and their cough and breath frequency, the concentration and distribution of pathogens in exhaled air, human activities, and infectious particles deposition, inactivation, transfer and removal rates. To improve our knowledge of predominate pathways of influenza transmission, we developed and applied a Markov chain model to estimate the intake dose of influenza viruses in the respiratory tract and mucous membrane of 24susceptible individuals in a 500 meter square hypothetical office environment assuming one infector and 8 hours exposure time. We explore the sensitivity of intake dose to each variable using existing ranges from the literature. In addition, this work develops a Monte-Carlo uncertainty analysis to predict the statistical distribution of some reported data and infection risk using a dose-respond model. The results show the direct spray is likely the dominant transmission pathway of influenza in the office. Therefore, human activity patterns and the number concentrations and distribution of infectious particles in exhaled breath and cough have the largest impact on influenza infection risk. The median infection risk was estimated to be ~11.5%, which interestingly, yielded an equivalent quanta generation rate in a transient Wells-Riley model of 125 per hour, which is generally in line with assumptions from the literature. Overall, the model can be used to further explore dominant pathways for influenza transmission in indoor environments under a variety of assumptions and to investigate the effectiveness of control strategies such as filtration, ventilation, and UVGI.