Aerosolization of a Human Norovirus Surrogate, Bacteriophage MS2, during Simulated Vomiting

Human noroviruses (NoV) are the leading cause of acute gastroenteritis worldwide. Epidemiological studies of outbreaks have suggested that vomiting facilitates transmission of human NoV, but there have been no laboratory-based studies characterizing the degree of NoV release during a vomiting event. The purpose of this work was to demonstrate that virus aerosolization occurs in a simulated vomiting event, and to estimate the amount of virus that is released in those aerosols. A simulated vomiting device was constructed at one-quarter scale of the human body following similitude principles. Simulated vomitus matrices at low (6.24 mPa*s) and high (177.5 mPa*s) viscosities were inoculated with low (108 PFU/mL) and high (1010 PFU/mL) concentrations of bacteriophage MS2 and placed in the artificial “stomach” of the device, which was then subjected to scaled physiologically relevant pressures associated with vomiting. Bio aerosols were captured using an SKC Biosampler. In low viscosity artificial vomitus, there were notable differences between recovered aerosolized MS2 as a function of pressure (i.e., greater aerosolization with increased pressure), although this was not always statistically significant. This relationship disappeared when using high viscosity simulated vomitus. The amount of MS2 aerosolized as a percent of total virus “vomited” ranged from 7.2 x 10-5 to 2.67 x 10-2 (which corresponded to a range of 36 to 13,350 PFU total). To our knowledge, this is the first study to document and measure aerosolization of a NoV surrogate in a similitude-based physical model. This has implications for better understanding the transmission dynamics of human NoV and for risk modeling purposes, both of which can help in designing effective infection control measures.


Determining π Groups
The first step in determining the π groups is to list all the dimensional parameters that affect fluid flow in the fluid mechanics problem; the number of dimensional parameters in this list is denoted by the term n. Flow through the human body esophagus and scaled model esophagus was treated as flow through a smooth pipe. Dimensional parameters that affect fluid flow through a smooth pipe are: ∆ (pressure change), (pipe diameter), (fluid velocity), (fluid density), and (fluid dynamic viscosity); thus n = 5 (Munson & Okiishi, 2002).
The second step is to list all of the primary dimensions that are found in the dimensional parameters; the number of primary dimensions is noted by the term m. The primary dimensions found in the dimensional parameters include: M (mass), L (length), and T (time); thus m = 3.
The dimensional parameters are listed below followed by the form of their primary dimensions in parentheses: The third step is to select a group of repeating dimensional parameters that will appear in all of the π groups for subsequent steps. One requirement for a repeating dimensional parameter is that it cannot have dimensions that are a power of another dimensional parameter. For instance, in this situation and cannot be repeating dimensional parameters because they have dimensions !! !! and ( !! !! ), respectively. Thus , and are repeating dimensional parameters. Next, the Buckingham π theorem is used to determine the number of π groups needed for dynamic similarity. The theorem states that n-m dimensionless groups are needed; in this case two π groups are needed for this fluid mechanics problem.
The 1 st π group should follow the functional form shown in Equation S.1, and include all of the repeating dimensional parameters and one of the two non-repeating dimensional parameters. Equation S.2 lists the elements of the 1 st π group in terms of its dimensions; for this equation to be dimensionless, Equation S.2 must hold true for the values of the exponents: To The 2 nd π group includes all of the repeating dimensional parameters and , the second of the two non-repeating dimensional parameters, seen in Equation S.7. For the 2 nd π group to be dimensionless, Equation S.8 must hold true for the values of , , . 2 To solve for the exponents of the dimensional parameters in Equation S.8, each dimension is balanced on both sides of the equation as shown in Equations S.9, S.10 and S.11.
Substituting the exponents into Equation S.7 yields the 2 nd π group, shown in Equation S.12.
Recall that dynamic similarity is achieved when the π groups have the same value in the model and in the human body. Note that the 1 st π group is closely related to a common dimensionless parameter used in fluid mechanics, known as the Euler number or pressure coefficient. The relationship between the 1 st π group and the pressure coefficient is shown in Equation S.13. Additionally, the 2 nd π group is similar to a common dimensionless parameter known as the Reynolds number; its relationship is shown in Equation S.14 (Fox Robert et al., 2004). Since the Reynolds number and pressure coefficient are common dimensionless parameters and are easy to work with mathematically, they will be used as the dimensionless groups to achieve dynamic similarity in the scaled model (Fox Robert et al., 2004

Achieving Similitude
Using the dimensions of the human body, outlined in In some cases, the scaled model dimensions were rounded to the nearest available dimension offered by product manufacturers, as shown in Table 2.  The governing dimensional parameter of our scaled model will be pressure. The pressure coefficient will be more of concern than Reynolds number when proving dynamic similarity because the pressure coefficient has a pressure term in its π group. Under the assumption that the