Dropping Covid-19 isolation requirement in England could lead to epidemic growth: Advisers

There is a potential for transmission to increase by around 25 per cent - 80 per cent if the population were to return to pre-pandemic behaviour with no mitigations. PHOTO: EPA-EFE

LONDON (REUTERS) - Scrapping Covid-19 tests and isolation periods in England could lead to rapid epidemic growth as people's behaviour changes more swiftly than at previous times in the coronavirus pandemic, government advisers said in a document published on Friday (Feb 18).

Prime Minister Boris Johnson will outline his plans for living with Covid-19 on Monday and has said that he aims to scrap the legal requirement to self-isolate for people who test positive for the coronavirus.

Health leaders have urged him not to be too gung-ho, with a survey showing most believed he should not scrap the requirement to self-isolate or end free testing.

The government's advisory pandemic modelling group SPI-M-O echoed that caution in easing the rules any further.

"While behaviour change following the lifting of restrictions has previously been gradual, a sudden change, such as an end to testing and isolation, has the scope to lead to a return to rapid epidemic growth," SPI-M-O said in a document dated Feb 2 but released on Friday, citing work done at the University of Warwick.

The estimates said the combination of measures and behavioural change since before the pandemic, such as testing, self-isolation and mask wearing, were reducing transmission by around 20 per cent - 45 per cent.

The estimates indicate there is a potential for transmission to increase by around 25 per cent - 80 per cent if the population were to return to pre-pandemic behaviour with no mitigations.

Britain has recorded 160,000 deaths from Covid-19, but Mr Johnson has lifted lockdown restrictions as vaccination and the lower severity of the Omicron variant break the link between cases and deaths.

SPI-M-O said that waning immunity and new variants could act to increase or decrease transmission, and that the growth advantage of the BA.2 subvariant of Omicron could mean modelling underestimates the trajectory for hospitalisations.

In SPI-M-O's central scenarios, which are not predictions, hospital admissions were not modelled to rise above their peak at the start of the year.

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