Oktober 21, 2020


The world is engulfed in a pandemic of the new coronavirus SARS-CoV2 and the respiratory illness COVID-19 it causes. The virus was first identified in Wuhan, China, and in three months spread throughout the entire world. To reduce the spread of the virus and prevent the overload of local health systems, most nations have introduced measures such as physical distancing, movement restrictions, and temporary lockdowns of both business and social activities. The global airline industry has been hit particularly hard by the pandemic. Revenue passenger kilometers have temporarily dropped by more than 90% in some regions and are only slowly recovering. Overall, the International Civil Aviation Organization (ICAO) expects an unprecedented drop in passenger demand and a crisis in the industry unseen before. Air travel should be considered critical, as this globally well-connected transport network could be part of new transmission chains to remote locations. The confined space conditions inside the aircraft require a small physical distance between passengers and may, therefore, encourage virus transmission. Current research and studies indicate that there is only a low probability of transmission in aircraft, but also point out that activities before and after the flight could also contribute significantly to the spread of disease.

Transmission model

The new coronavirus SARS-CoV2 has demonstrated high contagiousness even before infected people show any symptoms. Surface disinfection does not reduce the infection risk sufficiently as the majority of transmission is observed as droplet-based. However, the transmission probability during the flight itself is currently deemed low due to the airflow patterns in a cabin, the dry air, and the effectiveness of filtering systems in the aircraft. A developed transmission model is used to evaluate current concepts of passenger boarding with a focus on the transmission of SARS-CoV2 in the aircraft cabin. It is assumed that the transmission risk is dependent on the distance and direction between passengers (shown in the next figure). This model allows determining the individual transmission risk within an agent-based simulation environment addressing several standard boarding procedures, such as random or outside-in passenger boarding.

(Left) Shedding rate of an infected person. The increased rate is due to the relative positioning and increased physical activity. (Right) Virus load is depicted as a contour plot around a person as a function of distance.

Evaluation of standard boarding strategies

The boarding and deboarding simulation were performed using a single-aisle aircraft with 174 seats, representative of the majority of Airbus A320 and Boeing B737 family aircraft in service. Several different boarding strategies are applied. There is a single infected person among the passengers, its seat position and entry position are randomly set and the result averaged over 125,000 simulation runs (boarding model). The standard random boarding without additional distances and typical carry-on luggage results in about 5–6 critical contacts between passengers. Changing the boarding procedure reduces the number of contacts by more than half. Introducing a distancing of 1.6 m reduces the number of critical contacts for the random boarding to about 1–2. Hence, distancing alone does not eliminate these contacts. Carry-on luggage influences the time spent in the aisle at a high physical workload (high shedding rate). Reducing the luggage by 50% reduces the number of critical contacts to about 1 for random boarding. Boarding procedures like outside-in or reverse pyramid have a profound effect and reduce the number of critical contacts substantially below 1, even with normal carry-on luggage. Particularly, the use of the rear door will reduce the transmission probability significantly for all boarding strategies.

The transmission probability during deboarding is only slightly influenced since physical distancing is difficult if not impossible to impose. The number of contacts and the transmission probability remain at a high level, which indicates deboarding is a critical process in the aircraft cabin. To reduce the transmission probability, the timing of passengers entering the aisle during deboarding would need to be controlled (see also seatNow concept). Further measures like having active ventilation after engine shutdown should be discussed with experts on cabin ventilation.

Optimized group boarding

The physical distance between passengers ensures a minimal virus transmission risk during boarding, flight, and deboarding. Passenger groups are considered an important factor to derive an appropriate seat layout and boarding sequence. The main idea behind the group approach is that members of one group are allowed to be close to each other, as they are already in close contact with each other before boarding, while different groups should be separated as far apart as necessary. A new mathematical model is developed, which provides an optimized seat allocation while minimizing the amount of shedding rates that an infected passenger can cause. The model was used to evaluate the transmission risk of a seat allocation scheme and to solve this optimization problem with a genetic algorithm for three different scenarios of grouped passengers using 87, 115, and 174 passengers for boarding. The optimization of a standard scenario with a seat load of 50% (87 passengers) shows that the risk of transmission is significantly reduced by considering groups for seat allocation. In the second stage, an optimal boarding sequence is calculated to ensure a minimal transmission risk during the passenger movements in the cabin (walking the aisle, storing luggage, taking the seat). The simulation results show that the group-optimized seat allocation of groups performs significantly better than random boarding (under COVID constraints), taking into account both transfer risks and boarding time.

Optimized boarding of 31 groups considering a physical distance of 1.6 m between passengers of different groups


Using the already enhanced seat allocations for passenger groups (e.g., families or couples), the implementation of a genetic algorithm generates enhanced disembarkation sequences considering these groups. The selected use cases for seat loads of 50%, 66%, and 100% indicate a significant reduction in 40% disembarkation time when physical distances between passenger groups are mandatory to satisfy pandemic regulations. To inform passenger groups about the disembarkation sequences, we propose to activate the cabin lights at the seats in a dedicated way. That means that our developed methodology could already be applied to actual airline operations.

Optimized disembarkation of 31 groups considering a physical distance of 1.6 m between passengers of different groups


The following two videos show how passenger boarding performs without adjusted regulation (random) and how smoothly a boarding process can take place using the optimized sequence.

Random sequence

Optimized sequence


The complete list of publications can be found here: references.