What’s air conditioning got to do with COVID-19?
By now, we are used to making adjustments to help prevent the spread of COVID-19. But how does air flow come into the equation and how can we use information about the airflow in venues to mitigate risk?
It appears that COVID-19 is able to spread in diverse environments
COVID-19 is understood to be mainly transmitted person-to-person via large respiratory droplets containing the virus. This could be caused by breathing or sneezing, direct contact with an infected subject, or indirect contact from contaminated surfaces. Determining particular places linked to clusters of cases could reveal settings and factors responsible for amplifying the diversity in reported transmissions: it’s thought that potentially 80% of transmission is being caused by only 10% of infected individuals.
Multiple outbreaks and clusters of COVID-19 have been observed in a variety of indoor settings. The main potential factors contributing to outbreaks in occupational settings are:
● Working in confined indoor spaces
● Close/direct contact with COVID-19 cases, eg essential workers
● Insufficient or incorrect use of protective personal equipment (PPE)
● “Presenteeism”- impossibility to work remotely coupled with financial constraints leading to continued commuting and working when infected
● Transmission from asymptomatic people- either presymptomatic or those who never experience symptoms
Air condition has been identified as a contributing factor in the spread of COVID-19
For the same type of setting and identical number of people, the air condition may influence viral transmission of COVID-19 by affecting how droplets/aerosols move and their rate of decay. Therefore, the use of heating, ventilation and air-conditioning systems (HVACs) may have a complementary role in decreasing potential airborne transmission of COVID-19. It’s also important to note that HVACs can increase the spread of COVID-19 as both droplets and aerosols spread significantly further when assisted by air streams without filtering.
Humidity could affect the rate of COVID-19 transmission
Research has shown that because humidity affects how droplets and aerosols move, and their rate of decay, it may influence peoples’ susceptibility to infection:
● Droplets are usually categorised as larger entities (>5 μm) that rapidly drop to the ground due to gravity. Droplets can travel further in low-temperature and high-humidity environments.
● Aerosols are smaller particles (≤ 5 μm) that rapidly evaporate in the air. Aerosols leave behind droplet nuclei that are small enough and light enough to remain suspended in the air for hours. The number of aerosol particles increases in warm, dry environments.
In addition to the influence on the spread of the droplets, a lower ambient humidity impacts our respiratory immunity significantly by diminishing cilia’s capability to expel viral aerosols. The human ear, nose and throat areas are more effective as virus fighters at higher ambient humidity values rather than when room air is very dry.
Using HVACs to prevent risk in closed spaces
Air quality (including humidity and flow) can be controlled in a variety of ways using HVACs. Studies have shown that it’s important to improve ventilation in multi-occupant spaces to mitigate the risk of the virus spreading. This is especially important if the temperature and humidity are low (risks of higher far-field aerosols as explained before) or activities that generate high levels of aerosol (like singing or physical exercise) are taking place.
A simple way for users to provide valuable airflow data for research
While assessing precisely the quality of airflow in a given setting requires a lot of time and expert knowledge, it is possible to assess it by proxy, by leveraging large-scale user-contributed observational data coupled with exposure investigations carried out by the track and trace teams. This approach enables the collection of data that would otherwise be extremely lengthy and costly to collect.
The Moai track and trace app achieves this by using a short and targeted multiple choice questionnaire to collect data from users, such as nature of the building, density of people, ventilation type(if any), length of exposure and activity. It enables answers to the questionnaire to be submitted by both the app users and venue owners anonymously. The final exposure data contains 22 fields that forms the basis for the training of the machine learning algorithm.
See the full Moai research paper and all associated references here