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The sudden emergence and rapid spread of COVID-19 has had a devastating effect on the health of millions of people, with over 1.4 million deaths and reports of long-term health consequences for some people who survive the infection.
In the absence of a safe and effective vaccine and with limited treatment options, governments across the world have instigated a range of non-pharmaceutical measures to try to reduce the infection rate of the pandemic.
These include maintaining distance from other people, regularly washing hands, wearing face masks, limiting contact with others to specific bubbles of people, and working from home.
While reducing the number of people with a SARS-CoV-2 infection and therefore the number of those who have died or become seriously ill, these measures have also significantly disrupted global economies, cultures, and societies.
One reason for this is that, because of the novelty of the virus, governments have had little information to go on when deciding where and when to implement measures. Also, experts are still trying to understand which methods are likely to be most effective depending on the circumstance.
As time has gone on, more information about how the virus spreads has come to light. This has enabled the researchers behind the present study to analyze reported cases of the spread of COVID-19 at a variety of event types.
As a consequence, the researchers were able to develop an equation that may help people estimate the likely number of infections resulting from one person with the virus attending an event.
After studying various reported events where SARS-CoV-2 was transmitted — including a choir practice where 52 of 60 people contracted the virus, and a bus journey during which five people acquired the virus from a fellow passenger — the researchers gathered enough data to make estimations of various key factors that govern rates of infection at events.
These factors included the duration of the event, transmission intensity, proximity of individuals, and degree of mixing.
The researchers were then able to look at what effect various interventions would have on the rate of infection at the event. These interventions included social distancing, wearing a face mask, or strictly staying part of a social bubble.
The researchers found that across all venues, maintaining social distance was effective at reducing the rate of infection.
Social bubbles proved to be effective at events with a high probability of transmission and mixing of participants, such as busy workplaces, bars, clubs, and schools.
The researchers found that while masks were generally effective at reducing the rate of infection, this effect decreased in high transmission settings, such as parties, choirs, and clubs. Even though masks decrease transmission rates, the transmission probabilities at these events were so high that the overall effectiveness of masks was reduced.
The authors of the study suggest that further information on transmission events would continue to help researchers determine what the most effective interventions are for specific venue types.
Prof. Caroline Colijn, Canada 150 Research Chair in Mathematics for Evolution, Infection, and Public Health at Simon Fraser University, Burnaby, BC, Canada, and a co-author of the study, says, “It would be great to start collecting information from exposures and outbreaks: the number of attendees, the amount of mixing, the levels of crowding, the noise level, and the duration of the event.”
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