Infection control for COVID-19 in hospital examination room

The results of this theoretical study clearly show that the aerosols emitted from a patient’s mouth or nose in an examination room, where masks must be removed, are strongly affected by the airflow in the room, and the risk of their deposition on the doctor and elsewhere in the room cannot be overlooked (Fig. 1). This finding is consistent with our previous report9. Additionally, the movement of aerosols was modeled assuming a patient coughs, and it was found that the number of aerosols deposited on the physician was comparable to that resulting from the patient’s normal exhalation, although small aerosols spread widely throughout the room (Fig. 2).

The effect of humidity was also examined in this study. Although humidity is an easily controllable environmental factor in the clinic, few previous studies have examined the impact of humidity on SARS-CoV-2 infection. Humidity affects the mucous membranes of the upper respiratory tract in infected and uninfected individuals, but small aerosols could have a greater impact. Our simulations show that the diameter of large aerosol particles is reduced in seconds at RH75, a humidity higher than that of New York City, USA, all year round14. This suggests that more attention may need to be paid to controlling smaller aerosols to limit airborne transmission of SARS-CoV-2.

Compared to RH100, the number of suspended, settled, and excluded particles was lower than RH75 because most particles evaporated in about 7 s, indicating that humidity has a marked effect on particle size.

The humidity in the exam room at our institution was relatively higher (74%; the weather was cloudy). Japan is a relatively humid environment, and lower humidity simulations should be considered globally. In our CFD model, the relative humidity is imposed on the air conditions of the whole room. First, simulations were performed at 100% relative humidity (RH100) to assess the highest risk of exposure to aerosols, since aerosols theoretically do not evaporate in RH100. The simulations were performed at RH75 because the actual humidity in the otolaryngology examination room at Chiba University Hospital is around 75% (74%). The simulation was also performed again at RH50 (Table 2). The results show that aerosols evaporate faster at RH50 than at RH100 and RH75, indicating a lower risk of aerosol exposure at lower humidity levels.

In the present simulation, the local temperature was not given because it was not considered to have a significant effect on the conclusions. However, in order to clarify the influence, we performed the analysis considering the actual local temperature. The results with real environmental considerations (mouth temperature, droplet temperature, body temperature and mouth humidity) of the analysis are compared to those without ambient humidity of RH50, ambient temperature of 25°C and 100 s. Based on a previous study, the setpoints were determined at 33°C for oral temperature and 31°C for body temperature15.16. The temperature of the droplets was set to the same temperature as that of the mouth. The humidity in the mouth was set at RH70. The simulation results are shown in Supplementary Table S.

According to the results, for 10 μm particles, the effect was 0.1%, even after detailed examination of the real environment. For particles of 80 μm, the effect was at most of the order of 1 to 2%. Therefore, these results suggest that the effect of local temperature is weak in this study.

For extremely low mass particles, it is possible to simulate their behavior by solving the coupled flux and particle equations. It is also possible to estimate their behavior without solving the particle equations by instead solving the flow equations and integrating the air velocity distribution from a suitable initial position, such as the mouth. In our simulations, we considered the random behavior of particles due to macroscopic turbulence rather than microscopic Brownian motion.

In terms of airborne infection by aerosols, the number of droplets aspirated into the body from a macroscopic point of view is probably more relevant than the behavior of microscopic particles (collision and deposition). Therefore, in this study, particles of negligible mass were replaced by streamlines.

Several physical barriers have been designed to protect healthcare workers during aerosol-generating activities, but these devices prevent direct contact with larger droplets and have not been shown to be effective against smaller aerosols, which are considered as more important.17.

A constant flow of 2.5 m/s was used to model normal patient expiration. Although the full respiratory waveform can also be used, this may not affect our conclusions regarding infection control as it would only reduce the aerosol released into the room.

To develop more effective and feasible countermeasures against SARS-CoV-2, we also simulated the efficiency of aerosol removal using a suction device. The results showed that aerosol scattering during normal exhalation (Fig. 1) and coughing (Fig. 2) can be removed more effectively by a suction device than relying on the maximum efficiency of the airflow in the room (data not shown).

In the clinical setting, respiratory events such as coughing or sneezing are likely to occur during otolaryngology consultations and nasal swab procedures for SARS-CoV-2 testing18.19. Although general common-sense measures have been recommended for these high-risk practice settings, no evaluation of suction devices has been reported to date.20. Our analysis showed that the particle removal efficiency of the suction device was lower in response to coughing compared to normal exhalation. Therefore, more effective infection control measures might be needed against more infectious mutants and diseases that lead to more frequent coughing and sneezing.

It is important that a suction device used in the exam room be stretchy and not interfere with the exam. The size and expandability of the device in this study was designed to be compatible with various examination and operating rooms in real clinical settings. The effectiveness of aerosol removal was studied as a function of the location of the device. The results suggest that it is important to place the vacuum inlet of the suction device in a “direction” facing the patient’s mouth rather than a “distance” in which it is closer to the patient exhaling pathogen aerosols. . The simulated diameter and suction speed of the device were 6 cm and 1.2 m3/min, respectively, and while it’s not necessary to use a higher suction speed, we haven’t looked at speeds lower than this.

A limitation of our model is that the number of aerosols that act as virus vectors is not known, so the risk can only be estimated from their distribution, which cannot be assessed quantitatively. Also, the doctor’s breathing is not considered because it is difficult to model the exhalation and inspiration of a doctor wearing a mask. Additionally, only three positions of the suction device have been studied, and these may not correspond to the optimal placement.

The simulation results were replicated in the verification experiment (Fig. 4). Regarding the optimization of the position of the suction machine, by placing the suction machine 15 cm from the mouth of the patient model, with the suction device facing the patient model side, no visible fogging n could be seen around the doctor model (Fig. 4). This position of the suction machine was confirmed by the otolaryngologist (TS) not to interfere with the examination.

In conclusion, we discussed the insufficient infection control measures, such as opening windows and doors, against aerosols in the examination room and the increased risk for health care providers of coughing . We have also shown that humidity significantly alters the behavior of aerosols, indicating that suction devices can increase safety in our limited clinical applications. By further refining the model parameters, our approach can guide the design of devices that can more effectively limit the spread of respiratory diseases, including COVID-19.

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