Modern transportation offers conveniences unimaginable in previous eras, shrinking the world in ways few would have imagined not long ago. With the speed humans are able to travel long distances, it enables disease to hitch a ride and travel equally fast. In particular, aircraft have the potential to aid in the spread of disease. Because of that, we need to continually look at methods to control the transmission of disease and infection.
The potential for international airline passengers to transport infectious diseases from country to country is a reason for concern. The 2003 severe acute respiratory syndrome (SARS) was found to be spread largely by air travelers, becoming a global epidemic that involved 774 fatalities and cost billions. Other viruses and even deliberate infection pose threats, too. Finding a tool to detect airborne infectious pathogens accurately and rapidly before passengers and crew leave the aircraft would be valuable.
Validation for CFD Prediction of Mass Transport in an Aircraft Passenger Cabin was published by the Federal Aviation Administration (FAA) in 2006. The abstract says: A joint project was established to validate computational fluid dynamics (CFD) as a quantitative methodology for prediction of the distribution of pathogens released into the environmental control system (ECS)-generated ventilation flowfield of an aircraft passenger cabin. Acquisition of the requisite experimental databases for three-dimensional velocity and contaminant distributions was accomplished in the FAA Civil Aerospace Medical Institute’s (CAMI’s) Aircraft Environmental Research Facility (AERF). The associated CFD simulations were conducted by the University of Tennessee CFD Laboratory staff, on the resident Beowulf PC cluster and/or the University of Tennessee Innovative Computing Laboratory SiNRG cluster, using both commercial and proprietary CFD computer codes. It is noted that “the CAMI AERF is an exceptionally valuable research facility to support research on the fate of pathogens introduced into aircraft cabin ventilation flowfields. The requirements are clearly delineated for the acquisition of quality velocity and mass transport experimental data to support CFD validation requirements. The astute use of CFD methodology can certainly generate precise design guidance for such experiments, effectively and efficiently reducing the size of the data matrix required to serve the validation requirement. The results of this steadily growing knowledge base will predict estimation of optimal opportunities for onboard sensor locations, hence will support associated hypotheses for examining potential damage mitigation strategies, should a cabin release event be detected.”
To understand contaminant transport and airflow patterns inside an aircraft cabin, previous researchers have used computational fluid dynamics (CFD) models to predict airflows with and without simulated passengers. An Analysis on the Detection of Biological Contaminants Aboard Aircraft considers “exhaled particles from regular breathing, coughing and sneezing. (Because) infectious airborne particles are typically under 20 microns, here we restrict our simulation and analysis to expellants with diameters under 20 microns. . . . Three scenarios of infectious “super spreader” passengers were investigated, consisting of states of extreme coughing, extreme sneezing, and regular breathing. Our principal finding was that the steady-state bacteria concentrations in aircraft would be high enough to be detected in the case where seven infectious passengers are exhaling under scenarios 1 (breathing and coughing) and 2 (breathing and sneezing), and where one infectious passenger is actively exhaling in scenario 2. Breathing alone failed to generate sufficient bacterial particles for detection, and none of the scenarios generated sufficient viral particles for viral detection to be feasible.” Related: State-of-the-Art Methods for Studying Air Distributions in Commercial Airliner Cabins.
Researchers Study How Microbes Travel Through the Air: Engineers and biologists are steering their efforts towards a new aerobiological modeling technique, one they think may assist farmers in the future by providing an early warning system for high-risk plant pathogens. It will also provide the basis for more effective management strategies to address the spread of infectious diseases affecting plants, domestic animals, and humans.
Previously at our blog, researchers at Technical University of Denmark studied the poop siphoned from airplane toilets from flights arriving from around the world: AIRLINE POOP STUDIED TO TRACK GLOBAL SPREAD OF AMR IN BACTERIAL PATHOGENS.