Chasing Corona - GRS scientists simulate the spread of SARS-CoV-2 in aerosoles

29.12.2020

In recent months, it has become clear that the ingestion of virus-contaminated aerosols via the air is one of the main causes of Covid-19 infections. Unlike the relatively large droplets (> 5 µm) in classic droplet infection, which rapidly sink shortly after exhalation, aerosols (< 5 µm) and with them the virus remain airborne for longer. Recent research suggests that this form of infection is a major reason why the vast majority of people contract the virus indoors.

Therefore, it is important to understand as clearly as possible how infectious aerosols spread and what measures can be taken to prevent infections via the air that we breathe. In order to make a contribution here, a team of researchers at GRS has used simulation software from nuclear engineering to calculate the dispersion of Cobid-19 aerosols in rooms. This makes it possible to understand the influence of various factors on the dispersion of aerosols in closed rooms and to evaluate the effect that measures such as ventilation or wearing a face mask have on the risk of infection.

COCOSYS: Simulation software for the dispersion of aerosols in nuclear power plants

The COCOSYS (Containment Code System) code system of GRS is normally used to calculate the dispersion of radioactive substances in the form of aerosols or gases in nuclear power plants. In addition to the complex room arrangements, the aerosol dynamics (e.g. suspension and resuspension, fusion and decay), technical systems such as filters, ventilation systems or time-dependent opening and closing processes at room interconnections (e.g. doors) are also taken into account.

Since its release in 1999, COCOSYS has been continuously developed, validated and applied to new problem areas. For example, the simulation software has recently been used to calculate radon concentrations in buildings.

Scientists at GRS have arrived at the conclusion that COCOSYS is also suitable for calculating the spread of SARS-CoV-2 viruses through aerosols. In addition to the previously described properties (complex spatial arrangements, technical and time-dependent features), the code system can take into account essential factors that have an influence on the aerosol spectrum present. These include, for example:

  • humidity
  • temperature
    • in the interior
    • of the inflowing air during ventilation
  • location-dependent concentration (urban, rural or industrial site) of other aerosol particles in the air (fine dust, soot etc.)
  • changes in the aerosol particles.

But most importantly, COCOSYS is able to deliver results promptly due to comparatively short computation times. In particular, the simulation software can calculate the physical processes of aerosol transport and the aerosol particle spectrum in complex, arbitrarily networked room layouts with comparatively little effort. According to the researchers, this makes it more suitable for dispersion analyses of SARS-CoV-2 aerosols than the CFD (computational fluid dynamics) codes usually used for this purpose.

In a first step, tests were carried out applying the models to individual rooms.

Verification using the example of a pharmacy

To this end, the research team first compiled the essential properties of SARS-CoV-2 that are relevant for the further description of the bioaerosol release in COCOSYS simulations. They then fed the software with the necessary input variables to be able to take human respiration and release processes into account. These input variables included, for example, breathing volume and frequency, oxygen/carbon dioxide turnover, or humidity of the exhaled air. In order to be able to fully adapt and adjust COCOSYS to the new task, additions to the characteristic properties of bioaerosols in general and SARS-CoV-2 aerosols in particular were also necessary.

The first test case was an Italian pharmacy for which corresponding data from the research literature was available. For this 75-m³ pharmacy, the potential infection risks were calculated for two exposure scenarios (A: before lockdown, B: after lockdown). The difference between the two scenarios is that after the lockdown, the door of the pharmacy was always open, resulting in an air exchange rate increased by a factor of about 10. In both scenarios (A, B), an infected person was the first customer to enter the pharmacy and leaving it again after ten minutes. During the time of stay, virus-containing bioaerosols were introduced into the room volume of the pharmacy, remaining airborne and viable for up to three hours. For a realistic result, it was assumed that a standardised conversation took place in addition to breathing, since more aerosols are exhaled when speaking. The simulation with COCOSYS not only allows the temporally changing aerosol concentration but also the potential risk of infection during a stay in the room to be represented under different boundary conditions. As a result, it was shown that the risk of infection in scenario B was about 20 % lower, which agreed very well with the data from the literature. This shows that COCOSYS is able to calculate infection risks.

Application using the example of a room in a nursing home

In a second test case, the scientists created a model of a resident's room in a nursing home. For the simulation, it was assumed that there was an infected person in the furnished en-suite single room whose breathing (and associated aerosol emission) was calculated using the parameters described above. In addition to room geometry, furniture, and aerosol exposure from the infected person, the baseline scenario also included parameters such as room temperature, particle size spectrum, and relative humidity.

There then followed a large number of calculations resulting from typical daily processes in a care facility. These include, for example, regular visits by the nursing staff: even opening the door had an effect on the air exchange rate of the room; subsequently, the window was either fully opened or tilted. Parameters such as the temperature outside, wind direction and humidity were also included in these calculations. The results can be used to understand the influence of various factors in enclosed spaces on aerosol dispersion. These include the influence of

  • possible measures such as ventilation or wearing a face mask
  • the deposition of aerosols on surfaces
  • interactions between the individuals involved

on the risk of infection.

Among other things, it could be shown that

  • the CO2 concentration is a good indicator of the aerosol concentration, and
  • community masks do not provide sufficient protection for carers because the diameter of the aerosol particles decreases due to evaporation.

Results in the form of a research report and an app

In a follow-up study, a home for the elderly or a hospital is to be modelled in order to determine infection-relevant processes and to provide clues for optimised processes with regard to the risk of infection in such facilities. In order to obtain more precise results for different possible scenarios, the influence of further parameters will be investigated.

The results obtained so far will soon be published in the form of a research report in the GRS publications database. In addition, a team of developers is working on making them usable by means of an app that will be made available to the public free of charge. This app is intended to create a better understanding of the situations and conditions that lead to an increased risk of infection and how this can be influenced by one's own behaviour.