Medicines

Predicting indoor transmission of SARS-CoV-2 far-field

In a recent preprint study researchers from the UK predicted the infection rate by far-field airborne transmission (that occurs at distances of greater than two meters) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) indoors – showing the probability of transmission increase with occupancy. The researchers observed that far-field transmission is likely to be a rare event.

The study recommends standard ventilation use or its equivalent and to increase the space volume per person, along with reductions in viral load and infection rate of the wider population.

Study: A population framework for predicting the proportion of people infected by the far-field airborne transmission of SARS-CoV-2 indoors. Image Credit: Aliaksandra Post/Shutterstock

A preprint version of the study is available on the medRxiv* server, while the article undergoes peer review.

Background

The ongoing coronavirus disease 2019 (COVID-19) pandemic is caused by the SARS-CoV-2 infection. The virus is rapidly transmitted as it is encapsulated in respiratory droplets and aerosols, which are inhaled by a susceptible person.

The virus is most concentrated in the exhaled puff of an infected person, with the subsequent transport happening differently in outdoor and indoor environments. While outside, the air movement dilutes it rapidly, and the UV light may render the virus biological inviable. The dynamics are different inside a finite space volume – lower ventilation rates concentrate the aerosols in the air, and there is less UV light. Epidemiological understanding shows that the virus is spread readily in close contact.

However, far-field airborne transmission, which occurs at distances of greater than two meters, is linked to several super spreading events and is often correlated with poor indoor ventilation, long exposure times, and respiratory activities that increase aerosol and viral emission.

To understand the relationship between the occupancy of space and the probability of infection, in an individual person and a population of people, a theoretical approach is undertaken in the present study.

Study findings

In this study, the researchers consider the risk of infection for a population of a large space and compare it to the same population distributed in smaller identical spaces. Applying mass-balance and dose-response models, the researchers tried to sub-divide a large reference space into identical smaller comparator spaces, where the transmission risk is reduced for an individual person and a population of people.

In this study, the reference space is an office with a volume of 1500 cubic meters occupied by 50 people over eight hours, with a ventilation rate of 101 s−1 per person.

Considering the infection risk for a person, the researchers predict the dose and the probability of infection. Then they considered the infection risk for two equal populations which are distributed evenly in either a  big space (Big Office) or several smaller spaces (Small Office), factoring in the community infection rate and the probability of infection from a dose.

The comparison of the dose received by an individual susceptible person in the comparator Small Office, when a single infected person is present, with the reference Big Office for the same circumstances, gives a relative exposure index (REI) with a value of 10 in the Small Office.

The researchers noted that,

this REI is a measure of the risk of space relative to the geometry, occupant activities, and exposure times of the reference scenario and not a measure of the probability of infection.”

While secondary transmissions (new infections) are likely to occur only when the viral load is high, the probabilities of this occurring in the Big Office and the Small Office are low – making it difficult to distinguish the route of transmission epidemiologically.

In general, the researchers noted that the viral load must be greater in the Big Office than in the Small Office for the same proportion of the population infected when the community infection rate is ≤ 1%. With the viable fraction at a value of unity, they found that the estimated doses and infection probabilities are small.

Therefore, it is likely that a far-field transmission is a rare event that requires a set of Goldilocks conditions that are just right,” 

the researchers concluded.

When the magnitude of the viral load is too low, then irrespective of the space geometry or the number of susceptible people, the dose is too small to lead to an infection.

Because the probability of infection and the ventilation rate are inversely related, the researchers recommended increasing effective ventilation in under-ventilated spaces than increasing ventilation rates above those prescribed by standards, using air cleaners in already well-ventilated spaces.

Notably, the researchers pointed out that in the study the general trends and the relationships described can be applied to other airborne pathogens as well at the population scale.

Conclusion

The researchers observed that the number of occupants in a space influences the risk of far-field airborne transmission that occurs at distances of greater than 2 meters. This is due to the likelihood of having infectious and susceptible people both scale within the number of occupants.

This study shows that while there are benefits of subdividing a population, it is prudent to consider their magnitudes against other factors, such as the overall working environment, labor, and material costs, and inadvertent changes to the ventilation system and strategy.

It is recommended that the advantages of partition are more likely cost-effective if designed from the beginning in new resilient buildings. In existing buildings, changes can be made, such as reducing the occupancy density of space, preserving the magnitude of the ventilation rate, reducing exposure times, and ensuring compliance with ventilation standards.

*Important notice

medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:

Christopher Iddon, Benjamin Jones, Patrick Sharpe, Muge Cevik, Shaun Fitzgerald. 2021. A population framework for predicting the proportion of people infected by the far-field airborne transmission of SARS-CoV-2 indoors. medRxiv. doi: https://doi.org/10.1101/2021.11.24.21266807 https://www.medrxiv.org/content/10.1101/2021.11.24.21266807v1

Content Source: https://www.news-medical.net/news/20211130/Predicting-the-far-field-transmission-of-SARS-CoV-2-indoors.aspx

Gemma Wilson

Gemma is a journalism graduate with keen interest in covering business news – specifically startups. She has as a keen eye for technologies and has predicted quite a few successful startups over the last couple of years.

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