Airflow Dynamics of Coughing in Healthy Human Volunteers by Shadowgraph Imaging: An Aid to Aerosol Infection Control

Abstract

Cough airflow dynamics have been previously studied using a variety of experimental methods. In this study, real-time, non-invasive shadowgraph imaging was applied to obtain additional analyses of cough airflows produced by healthy volunteers. Twenty healthy volunteers (10 women, mean age 32.2±12.9 years; 10 men, mean age 25.3±2.5 years) were asked to cough freely, then into their sleeves (as per current US CDC recommendations) in this study to analyze cough airflow dynamics. For the 10 females (cases 1–10), their maximum detectable cough propagation distances ranged from 0.16–0.55 m, with maximum derived velocities of 2.2–5.0 m/s, and their maximum detectable 2-D projected areas ranged from 0.010–0.11 m2, with maximum derived expansion rates of 0.15–0.55 m2/s. For the 10 males (cases 11–20), their maximum detectable cough propagation distances ranged from 0.31–0.64 m, with maximum derived velocities of 3.2–14 m/s, and their maximum detectable 2-D projected areas ranged from 0.04–0.14 m2, with maximum derived expansion rates of 0.25–1.4 m2/s.These peak velocities were measured when the visibility of the exhaled airflows was optimal and compare favorably with those reported previously using other methods, and may be seen as a validation of these previous approaches in a more natural setting. However, the propagation distances can only represent a lower limit due to the inability of the shadowgraph method to visualize these cough airflows once their temperature cools to that of the ambient air, which is an important limitation of this methodology.The qualitative high-speed video footage of these volunteers coughing into their sleeves demonstrates that although this method rarely completely blocks the cough airflow, it decelerates, splits and redirects the airflow, eventually reducing its propagation. The effectiveness of this intervention depends on optimum positioning of the arm over the nose and mouth during coughing, though unsightly stains on sleeves may make it unacceptable to some.

Airborne spread of expiratory droplet nuclei between the occupants of indoor environments: A review

“…A similar large difference is to be found in the reports of human subject studies. Tang et al found that the peak coughing speed was 5.0 m/s, which was very similar to the peak sneezing speed of 4.5 m/s . Some other studies reported a much higher peak coughing speed of 6‐22 m/s (>10 m/s on average), and even a very high sneezing speed, up to 100 m/s …”

Breathing and Breathlessness in Clinic and Culture: Using Critical Medical Humanities to Bridge an Epistemic Gap

“…The person whose breath is visualised stands in front of the mirror and images are obtained when refl ected light from the mirror is refracted to different degrees as it passes from the warmth of the mouth to the cooler surrounding air. 49 The image that results looks like the surface of the moon, billowing out in particular patterns. Measurements can be made of the breath cloud relating to distance travelled, exhaled velocity, expansion rate and direction of fl ow.…”

Simplified models for exhaled airflow from a cough with the mouth covered

“…Smokers may suffer from chronic obstructive pulmonary disease (COPD) so that their respiratory patterns may be different from non‐smokers (Decramer et al., ). Typically, a smoker may generate a larger volume of cough air than a non‐smoker (Tang et al., ). Therefore, this study recruited ‘healthy’ smokers who reported no COPD in their consent forms to minimize this influence, although the experimental results may still be somewhat biased.…”

“…To avoid the influence of smokers as human subjects, Tang et al. proposed to use the real‐time schlieren and shadowgraph imaging method to visualize the exhaled airflow (Tang and Settles, ; Tang et al., , , , ). This method does not require the introduction of visualization media such as tobacco smoke.…”