Combination of measures ‘shows greatest effect reducing Covid-19 transmission’
Researchers say that a comprehensive package of measures – similar to a lockdown – could reduce the R number by 52%.
A combination of measures such as a public events ban, school closures and stay-at-home requirements is more effective in reducing coronavirus transmission than individual interventions, according to research.
Scientists looked at the effect of non-pharmaceutical interventions (NPIs) on the Covid-19 reproduction (R) number.
R represents the average number of people each Covid-19 positive person goes on to infect. When the figure is above one, an outbreak can grow exponentially.
When looking at the measures individually, a ban on public events was associated with the greatest reduction in R, amounting to a 24% reduction after 28 days, the researchers said.
Meanwhile, the measures most strongly associated with an increase in R were lifting bans on gatherings of more than 10 people (25%) and reopening of schools (24%) after 28 days, they added.
Study author Harish Nair, a professor at the University of Edinburgh, said: “We found that combining different measures showed the greatest effect on reducing the transmission of Covid-19.
“As we experience a resurgence of the virus, policymakers will need to consider combinations of measures to reduce the R number.
“Our study can inform decisions on which measures to introduce or lift, and when to expect to see their effects, but this will also depend on the local context – the R number at any given time, the local healthcare capacity, and the social and economic impact of measures.”
Professor Nair said: “We found an increase in R after reopening schools but it is not clear whether the increase is attributable to specific age groups, where there may be substantial differences in adherence to social distancing measures within and outside classrooms.
“Furthermore, more data are needed to understand the specific role of schools in increased Sars-CoV-2 transmission through robust contact tracing.”
The study authors also did a secondary analysis using Google mobility data, modelling the total visits to workplaces and the total time spent in residential areas.
Results indicated that people took some time to adapt their behaviour to comply with workplace closures and stay-at-home requirements, which was similar to the delay between the measures and the effects seen on R – around one to three weeks.
The authors suggest the delay was possibly due to the population taking time to modify their behaviour to adhere to measures.
The researchers also said that some of the greatest effects on R were seen for measures that were more easily implementable by law, like school reopening and introduction of a public events ban.
They suggest this may have been because their effects were more immediate and compliance was easier to ensure.
