COVID-19 risk at mass gatherings successfully assessed using data linkage
Population Data Science methods have great potential for informing policy in relation to the risk of infectious disease at large scale events, as demonstrated in a new study published in the International Journal of Population Data Science (IJPDS).
In summer 2021, as rates of COVID-19 decreased and social restrictions were relaxed in Wales, live entertainment and sporting events were resumed. Researchers in Wales used data linkage methods to assess the potential increased risks of spreading COVID-19 at large events in order to inform policy on the safe re-introduction of spectator events.
Two football matches were used as test events showed that only a small number of attendees had confirmed COVID-19 following each event, and there was no evidence of significantly increased risk of COVID-19 at either event. Event attendees agreed to share their personal ticket application data for the purposes of public health protection, to which the research team assigned unique NHS numbers. The NHS numbers were then used to link the attendees to routine SARS-CoV-2 PCR test data, to identify any cases in attendees over the following 14 days.
A comparison group of people who hadn’t attended either event was also established to compare for any significant differences between the two groups during the 14 days.
Using data linkage methods, the researcher team established that only a small number of attendees had confirmed COVID-19 after the events, and they identified no evidence of significantly increased risk of COVID-19 at either event.
As well as informing the these particular test events in Wales, the research team demonstrated that, with appropriate safeguards to protect personal information, data linkage methods have great potential for assessing COVID-19 risk at mass gatherings, including large sporting events.
Mark Drakesmith, lead author of the paper commented further “this is a unique dataset that allows us explore infection risk at large events in way not previously possible, and has opened doors to develop improved methods to assess infection risk in similar scenarios.”
Mark Drakesmith, Epidemiological Data Scientist, Communicable Disease Surveillance Centre, Public Health Wales, Cardiff