SAGE has acknowledged that its terrifying Omicron hospital admission projections were off the mark — and it is now warning of a ‘long tail’ of infections as the UK comes out of the fourth wave.
As recently as December 23, modelling by the Government’s scientific advisory group said there could be up to 10,000 daily Covid hospitalisations by mid-January. In reality, daily admissions peaked at just over 2,000 across the UK and are already falling in England, which has given the Prime Minister confidence to lift Plan B restrictions next week.
At SAGE’s most recent meeting last Thursday, chaired by Sir Chris Whitty and Sir Patrick Vallance, the group admitted the anticipated surge in hospitalisations had ‘not been seen so far’.
The panel put this down to a combination of the country’s ‘highly immunised population’, vaccine protection waning slower than expected and ‘precautionary behaviours’ in vulnerable people.
In the minutes, which were made public today, members also acknowledged that official projections of more than a million daily Omicron cases had also not come to fruition. SAGE said that behavioural changes, this time among younger age groups, may have ‘led to lower modelled numbers of infections of infections over recent weeks’.
A slew of international studies and mobility data over the last two years of the pandemic have shown that people change how they act and who they meet in the face of rising cases.
Professor Paul Hunter, an infectious disease expert at the University of East Anglia, told MailOnline that failing to factor in more accurate behavioural changes seen throughout the pandemic was one of the biggest reasons the models are ‘overly pessimistic’.
As well as leaving out behavioural changes, a number of the projections published in December failed to adjust for Omicron’s reduced severity — despite real-world South African clearly showing the variant caused milder illness.
In a separate document published today, the SPI-M modelling group that feeds into SAGE also said the Omicron wave of infections had not peaked due to natural immunity but rather down to people being cautious. It warned this means there are still swathes of people who have avoided the virus over the last eight weeks and therefore remain susceptible to getting infected.
As recently as December 23, modelling by the Government’s scientific advisory group said there could be up to 10,000 daily Covid hospitalisations by mid-January. The doomsday scenario was presented in a model by the London School of Hygiene and Tropical Medicine
Warwick University’s infection, hospitalisation and death projections on December 30: The group warned of up to 1.4million daily infections, 10,000 hospital admissions and nearly 3,000 deaths based on various level of restrictions and Omicron being 50 per cent less severe than Delta
LSHTM’s estimates based on the degree of immunity escape that Omicron might show and booster effectiveness
Acknowledging the collapsing Omicron rates, the SAGE minutes read: ‘The increase in hospitalisations, which is anticipated following the observed increase in cases in older age groups, has not been seen so far.
‘This may be due to higher vaccine levels of protection against hospitalisation, slower waning of vaccine protection, or the impact of precautionary behaviours amongst the most vulnerable and those around them.
‘Analysis from Bristol shows that intended behaviour change over December 2021 has led to lower modelled numbers of infections over recent weeks (compared to no such risk mitigation).’
SAGE added there was still ‘uncertainty about what may happen to hospital admissions over the coming weeks’ with case rates still high — around 90,000 Britons are testing positive every day.
Professor Robert Dingwall, a sociologist and former Government Covid adviser, told MailOnline that advisers must be ‘quite careful this doesn’t just become a sort of simplistic excuse for “it’s all down to behaviour, and we can’t predict that”.’
He accepted it was difficult and makes modelling more complicated when factoring in nuanced elements like how often someone leaves the house, uses public transport or interacts with others.
But he added: ‘But the [SAGE] modellers don’t seem to have had a serious discussion with people in other fields. Sociologists and economists do modelling, there are people out there who do understand this stuff.
‘People are beginning to realise that these models are [done by] the very narrow respiratory disease community… so their models haven’t really incorporated things others people know about.’
In SPI-M’s consensus statement, made last Wednesday but only published today, the group claimed Omicron infections had not peaked naturally.
‘As yet, there is no sign of a purely immunity-driven peak occurring in either the case data or the CIS for the UK or England.
‘Peaks of infections have often been asymmetric in nature during Covid with many more than half of infections happening during the population decline stage and so a long tail may still need managing, even after the peak.’
But SPI-M expressed more optimism about what will happen in hospitals in the coming weeks, highlighting that there has been a ‘much lower case fatality rate than those seen in previous waves of the epidemic’.
The statement adds: ‘This is highly likely a result of the combination of omicron’s decreased intrinsic severity and high vaccine effectiveness.’
Professor Hunter told MailOnline that SAGE ‘should have’ been able to factor in some extra behavioural changes because there is ‘a lot of information on behavioural changes in response to rising infections out there’.
But Professor Hunter said he suspected natural immunity was not being properly factored into the models either.
He referenced Professor Lockdown Neil Ferguson’s forecast of 250,000 Covid deaths without a lockdown in 2020 and said it was ‘not that unrealistic’.
But Professor Hunter believes the projections have become worse over time because we are not properly accounting for protection from natural immunity.
He added: ‘Models worked well at start of the pandemic. I think a lot of that stick [aimed at Professor Ferguson’s 250,000 deaths model] was unfounded and over the top.
‘But modelling endemic infections is more complicated than modelling epidemics. [SAGE is] Not good at modelling immunity.
‘They need to look at assumptions around immunity and talk to people who have a track record in modelling immunity better.’
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