Airborne disease transmission has always been a topic of wide interests in various fields for decades. Cough is found to be one of the prime sources of airborne diseases as it has high velocity and large quantity of droplets. To understand and characterize the flow dynamics of a cough can help to control the airborne disease transmission. This study has measured flow dynamics of coughs with human subjects. The flow rate variation of a cough with time can be represented as a combination of gamma-probability-distribution functions. The variables needed to define the gamma-probability-distribution functions can be represented by some medical parameters. A robust multiple linear regression analysis indicated that these medical parameters can be obtained from the physiological details of a person. However, the jet direction and mouth opening area during a cough seemed not related to the physiological parameters of the human subjects. Combining the flow characteristics reported in this study with appropriate virus and droplet distribution information, the infectious source strength by coughing can be evaluated. Practical Implications There is a clear need for the scientific community to accurately predict and control the transmission of airborne diseases. Transportation of airborne viruses is often predicted using Computational Fluid Dynamics (CFD) simulations. CFD simulations are inexpensive but need accurate source boundary conditions for the precise prediction of disease transmission. Cough is found to be the prime source for generating infectious viruses. The present study was designed to develop an accurate source model to define thermo-fluid boundary conditions for a cough. The model can aid in accurately predicting the disease transmission in various indoor environments, such as aircraft cabins, office spaces and hospitals.

The exhaled air of infected humans is one of the prime sources of contagious viruses. The exhaled air comes from respiratory events such as the coughing, sneezing, breathing and talking. Accurate information on the thermo-fluid characteristics of the exhaled airflow can be important for prediction of infectious disease transmission. The present study developed a source model to provide the thermo-fluid conditions of the exhaled air from the breathing and talking processes. The source model is a set of equations obtained from the measurements of the flow rate, flow direction, and area of mouth/nose opening with human subjects. It was found that the exhaled flow rate over time can be represented as a sinusoidal function for breathing and a constant for talking. The flow rates can be calculated by physiological parameters of a subject. The direction of the exhalation jet did not vary much between subjects and the area of mouth/nose opening could be regarded as a constant. Though the mouth/nose opening size varied among subjects, they were not correlated with the physiological parameters of the subjects. If combined with appropriate virus and droplet distribution information, the model can be used to describe the disease source due to breathing and talking. Practical Implications Accurate prediction of airborne disease transmission, and the infection prone zones, can aid in identifying and implementing the control strategies. With the recent advancements, Computational Fluid Dynamics (CFD) has become a powerful tool in predicting the disease transmission. Accurate prediction of the transmission by these CFD simulations requires information on sources and sinks of infectious viruses and models for dispersion of these viruses. The exhaled air of an infected human is one of the prime sources of disease viruses. In the present study, measurements of the flow were conducted on human subjects to develop models for the flow boundary conditions for the exhalation and inhalation during breathing and talking.

The droplets exhaled by an index patient with infectious disease such as influenza or tuberculosis may be the carriers of contagious agents. Indoor environments such as the airliner cabins may be susceptible to infection from such airborne contagious agents. The present investigation computed the transport of the droplets exhaled by the index patient seated in the middle of a seven-row, twin-aisle, fully occupied cabin using the CFD simulations. The droplets exhaled were from a single cough, a single breath, and a 15-s talk of the index patient. The expiratory droplets were tracked by using Lagrangian method, and their evaporation was modeled. It was found that the bulk airflow pattern in the cabin played the most important role on the droplet transport. The droplets were contained in the row before, at, and after the index patient within 30 s and dispersed uniformly to all the seven rows in 4 minutes. The total airborne droplet fraction reduced to 48, 32, 20, and 12% after they entered the cabin for 1, 2, 3, and 4 min, respectively, because of the ventilation from the environmental control system. Practical Implications It is critical to predict the risk of airborne infection to take appropriate measures to control and mitigate the risk. Most of the studies in past either assume a homogenous distribution of contaminants or use steady-state conditions. The present study instead provides information on the transient movement of the droplets exhaled by an index passenger in an aircraft cabin. These droplets may contain active contagious agents and can be potent enough to cause infection. The findings can be used by medical professionals to estimate the spatial and temporal distribution of risk of infection to various passengers in the cabin.