Modelling infectious disease transmission potential as a function of human behaviour

Mathematical modelling is an important public health tool for aiding understanding the spread of respiratory infectious diseases, such as influenza or COVID-19, and for quantifying the effects of behavioural interventions. However, such models rarely explicitly appeals to theories of human behaviour to justify model assumptions. Here we propose a novel mathematical model of disease transmission via fomites (luggage trays) at airport security screening during an outbreak. Our model incorporates the self-protective behaviour of using hand sanitiser gel in line with the extended parallel processing model (EPPM) of behaviour. We find that changing model assumptions of human behaviour in line with the EPPM gives qualitatively different results on the optimal placement of hand sanitiser gels within an airport compared to the model with naive behavioural assumptions. Specifically, that it is preferable to place hand sanitiser gels after luggage screening in most scenarios, however in situations where individuals perceive high threat and low efficacy this strategy may need to be reviewed. This model demonstrates how existing behavioural theories can be incorporated into mathematical models of infectious disease.

Visual search behavior and performance in luggage screening: effects of time pressure, automation aid, and target expectancy

Visual inspection of luggage using X-ray technology at airports is a time-sensitive task that is often supported by automated systems to increase performance and reduce workload. The present study evaluated how time pressure and automation support influence visual search behavior and performance in a simulated luggage screening task. Moreover, we also investigated how target expectancy (i.e., targets appearing in a target-often location or not) influenced performance and visual search behavior. We used a paradigm where participants used the mouse to uncover a portion of the screen which allowed us to track how much of the stimulus participants uncovered prior to their decision. Participants were randomly assigned to either a high (5-s time per trial) or a low (10-s time per trial) time-pressure condition. In half of the trials, participants were supported by an automated diagnostic aid (85% reliability) in deciding whether a threat item was present. Moreover, within each half, in target-present trials, targets appeared in a predictable location (i.e., 70% of targets appeared in the same quadrant of the image) to investigate effects of target expectancy. The results revealed better detection performance with low time pressure and faster response times with high time pressure. There was an overall negative effect of automation support because the automation was only moderately reliable. Participants also uncovered a smaller amount of the stimulus under high time pressure in target-absent trials. Target expectancy of target location improved accuracy, speed, and the amount of uncovered space needed for the search.Significance Statement Luggage screening is a safety–critical real-world visual search task which often has to be done under time pressure. The present research found that time pressure compromises performance and increases the risk to miss critical items even with automation support. Moreover, even highly reliable automated support may not improve performance if it does not exceed the manual capabilities of the human screener. Lastly, the present research also showed that heuristic search strategies (e.g., areas where targets appear more often) seem to guide attention also in luggage screening.