Simulation to assess the efficacy of US airport entry screening of passengers for pandemic influenza

We present our methodology and stochastic discrete-event simulation developed to model the screening of passengers for pandemic influenza at the US port-of-entry airports. Our model uniquely combines epidemiology modelling, evolving infected states and conditions of passengers over time, and operational considerations of screening in a single simulation. The simulation begins with international aircraft arrivals to the US. Passengers are then randomly assigned to one of three states – not infected, infected with pandemic influenza and infected with other respiratory illness. Passengers then pass through various screening layers (i.e. pre-departure screening, en route screening, primary screening and secondary screening) and ultimately exit the system. We track the status of each passenger over time, with a special emphasis on false negatives (i.e. passengers infected with pandemic influenza, but are not identified as such) as these passengers pose a significant threat as they could unknowingly spread the pandemic influenza virus throughout our nation.

Keywords: epidemiology modelling, false negatives, pandemic influenza, flu pandemics, passenger screening, detection probability, process simulation, United States, USA, discrete-event simulation, airport screening, infectious diseases, biological security, risk assessment, biological threats, biosecurity, aircraft passengers