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
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.