Using simulation to assess the potential effectiveness of implementing screening at national borders during international outbreaks of influenza, SARS, Ebola virus disease and COVID-19

The effectiveness of screening travellers for signs of infection during times of international disease outbreak is contentious, especially as the reduction of the risk of disease importation can be very small. Border screening typically consists of arriving individuals being thermally scanned for signs of fever and/or completing a survey to declare any possible symptoms, and while more thorough testing typically exists, these would generally prove more disruptive to deploy. In this paper, we utilise epidemiological data and Monte Carlo simulation to calculate the potential success rate of deploying border screening for a range of diseases (including the current COVID-19 pandemic) in varying outbreak scenarios. We negate the issue of testing precision by assuming a perfect test is used; our outputs then represent the best-case scenario. We then use these outputs to briefly explore the types of scenarios where the implementation of border screening could prove most effective. Our models only considers screening implemented at airports, due to air travel being the predominant method of international travel. Primary results showed that in the best-case scenario, screening has the potential to detect 46.4%, 12.9% and 4.0% of travellers infected with influenza, SARS and ebola respectively, while screening for COVID-19 could potentially detect 12.0% of infected travellers. We compare our results to those already in the published literature.