Work

Airborne SARS-CoV-2 in aircraft cabins: new inactivation data significantly influences infection risk predictions

Year: 2025

Type: article

Abstract: We predict the SARS-CoV-2 infection risk in aircraft cabins by simulating the aerosol transport with computational fluid dynamics and taking medical parameters into account. A recently presented new measurement technique allows us to measure the rapid virus inactivation after exhalation with high temporal resolution. In addition, much higher airborne SARS-CoV-2 inactivation rates than in previous studies were obtained. This raises the question of how the new knowledge of SARS-CoV-2 stability affects the prediction of infection risk. To answer this question, we evaluated 70 Lagrangian particle simulations with an index person sitting in all possible seats in an aircraft cabin. We then estimated the infection risk for the other passengers based on the old and new SARS-CoV-2 stability data. For typical transmission events, we found that the predicted infection risk is reduced by about 50% for the new stability data at low CO $$_2$$ 2 (500 ppm). However, elevated ambient CO $$_2$$ 2 concentrations of 3000 ppm protect the virus from inactivation and increase infection risk by about 50% compared to low CO $$_2$$ 2 . In addition, a high relative humidity of the ambient air, e.g., from exhaled breath, delays the rapid inactivation by a few seconds, increasing the risk of infection for immediate neighbors.

Source: CEAS Aeronautical Journal

DOI: 10.1007/s13272-025-00822-5

Authors: Florian Webner, Andrei Shishkin, Daniel Schmeling, Claus Wagner

Institutions: Technische Universität Ilmenau, Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

Language: English

Topic: Infection Control and Ventilation

Subfield: Pulmonary and Respiratory Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,190