title: Influenza infection risk and predominate exposure route: uncertainty analysis.
abstract: An effective nonpharmaceutical intervention for influenza interrupts an exposure route that contributes significantly to infection risk. Herein, we use uncertainty analysis (point-interval method) and Monte Carlo simulation to explore the magnitude of infection risk and predominant route of exposure. We utilized a previously published mathematical model of a susceptible person attending a bed-ridden infectious person. Infection risk is sensitive to the magnitude of virus emission and contact rates. The contribution of droplet spray exposure to infection risk increases with cough frequency, and decreases with virus concentration in cough particles. We consider two infectivity scenarios: greater infectivity of virus deposited in the upper respiratory tract than virus inhaled in respirable aerosols, based on human studies; and equal infectivity in the two locations, based on studies in guinea pigs. Given that virus have equal probability of infection throughout the respiratory tract, the mean overall infection risk is 9.8 × 10⁻² (95th percentile 0.78). However, when virus in the upper respiratory tract is less infectious than inhaled virus, the overall infection risk is several orders of magnitude lower. In this event, inhalation is a significant exposure route. Contact transmission is important in both infectivity scenarios. The presence of virus in only respirable particles increases the mean overall infection risk by 1-3 orders of magnitude, with inhalation contributing ≥ 99% of the infection risk. The analysis indicates that reduction of uncertainties in the concentration of virus in expiratory particles of different sizes, expiratory event frequency, and infectivity at different sites in the respiratory tract will clarify the predominate exposure routes for influenza.
authors.affiliation: School of Public Health, University of Illinois at Chicago, 2121 W Taylor St, Chicago, IL 60612, USA. rjones25@uic.edu
authors.forename: Rachael M
authors.initials: RM
authors.lastname: Jones
authors.forename: Elodie
authors.initials: E
authors.lastname: Adida
mesh_terms: D006801:Humans; D007251:Influenza, Human / Q000453:epidemiology / Q000635:transmission*; D008390:Markov Chains; D009010:Monte Carlo Method; D011336:Probability; D018570:Risk Assessment; D035501:Uncertainty