Researchers have proposed a model to support the safe return of crowds to live events, while reducing the risk of COVID-19 transmission.
Under the proposal, from researchers at Imperial College London and the University of Tartu in Estonia, event organisers could manage a pre-event testing and surveillance scheme for entry to events. The scheme would be combined with predictive risk modelling to inform ticket holders and public health authorities of the risk of attending.
The team, says that their model offers a first step towards society learning to live with Covid-19 in a fully re-opened economy, whilst also protecting people attending live events. The work is outlined in a paper published in the Journal of the Royal Society of Medicine.
Dr Matthew Harris, from the School of Public Health at Imperial College London and lead author, said: “Mass events, such as the Olympics, routinely use live streamed testing control officers for anti-doping measures and so the workforce and the technology is already in place to facilitate these processes.”
‘Ticket and test’
Explaining the model, the authors say that once an event is announced, the customer purchases a ticket which would become valid only after they complete a questionnaire and a coronavirus test (such as a lateral flow test) at home shortly before the event. The test would be videoed or live streamed to a professionally trained testing control officer, allowing for near-real time assessment of the ticket holder’s identity and test validity.
According to Dr Harris, ticket holders with a negative test would receive a scannable certificate, such as a QR code, to gain access to the event and would follow any measures put in place by the event organisers for distancing, mask-wearing and good hygiene practices.
If a ticket holders has a positive COVID-19 test result they would receive an automatic full refund of the ticket price, their ticket would become invalid, and a notification of the positive test will be given to public health authorities. The ticket would then be released to people living in areas with lower COVID-19 prevalence to ensure full capacity at the event.
Through predictive risk modelling based on who is attending the event, background infection and vaccination rates and the features of the venue, each ticket holder will receive information about their personalised risk score so they can make an informed decision about whether or not to attend the event. Public health authorities would be able to assess the overall risk of the event taking place.
After the event ticket holders would be asked to follow a five-day ‘best efforts’ self-isolation protocol and, following the same process, complete a home test for event-acquired infection to assess the effectiveness of the protocol, and so that they can be reassured that they can stop self-isolating after a negative result is obtained. Testing may be rationalised as vaccination and immunity status becomes reliable and accessible.
The researchers stress that events will never be completely ‘safe’ but the process they propose would enable us to understand how ‘safe’ they actually are.
Dr Harris added: “Several steps need to be tested in the model and different scenarios should be explored, including acceptability to customers and the price point for ticket sales that would support a return to profitability for the live events industry. However, because this model allows for events to be held at full capacity, it potentially meets the needs of industry, consumers, the health system and public health and could also be relevant to other mass events including educational conferences and sports events.”
This article is based on materials from the Journal of the Royal Society of Medicine
‘Safe management of full-capacity live/mass events in COVID19 will require mathematical, epidemiological and economic modelling’ by Harris, M. et al. has been accepted for publication by the Journal of the Royal Society of Medicine.
Article text (excluding photos or graphics) © Imperial College London.
Photos and graphics subject to third party copyright used with permission or © Imperial College London.
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