Warwick University

The SAGE Models are Already Wrong

In a recent article, we considered the implications of the U.K.’s spring rise in infections, given that before now the assumption has been that coronaviruses are seasonal at northern temperate latitudes. Do we have to dismiss that hypothesis in light of the ‘Third Wave’?

Here we argue that, contrary to Government claims, the British summer is indeed finally impacting viral transmission, with sharp falls in positives reported across the U.K. In England, reported cases have more-or-less halved in a week, from 50,955 to 25,434.

This sharp fall runs counter to all three of the most recent SAGE models driving Government policy, which predict rising infections leading to peaks in hospital admissions in high summer – and by implication falsifies the assumptions upon which these models are based.

Parsimony predicts the summer troughs and winter peaks evident for SARS-CoV-2

In spring and summer 2020 and winter 2020-1, SARS-CoV-2 infections parsimoniously followed the pattern of seasonal respiratory viruses, falling away in the summer months and rising again in the autumn, with peaks in deaths occurring between mid-November 2020 and mid-April 2021 in different northern temperate countries.

Although falling infection levels were sometimes prolonged into early summer or began to rise again in late summer, there were no peaks in fatalities in summer or early autumn 2020. 

Most notably, while cases in Sweden rose in a pattern close to the European average in early 2020, they persisted much later, continuing to a plateau in late spring and early summer, before falling away sharply from the end of June. Hospitalisations and deaths fell more smoothly from the mid-April peak, however, and showed no corresponding rise in late spring and early summer.

Similarly, while infections began to rise in late summer in some countries – such as France – there was no substantial increase in deaths before mid-autumn. Summer 2020 appears to have broken the link between infections and serious illness in the absence of vaccination. 

Sweden has so far emerged relatively unaffected by the Delta variant. Although this variant was detected in Sweden – as it was in most other European countries – infections in Sweden nevertheless fell with the onset of summer. As Sweden’s State Epidemiologist Anders Tegnell remarked in an interview on June 18th, 2021 (at about 8 minutes 25 seconds), “the number of cases in Sweden are falling rapidly, very rapidly I would say, much more rapidly than we ever thought was possible”. Tegnell also makes some sceptical points about asymptomatic transmission and mass testing, so beloved of the U.K.’s SAGE committees.

Recent peaks attributable to the Delta variant have occurred in countries such as Denmark, Belgium and the Netherlands, but these outbreaks too may have peaked as they appear to have in the U.K.

SAGE scenarios – anything can happen in the next eight weeks…?

Turning to the latest (July 6th) scenarios of the SAGE’s SPI-M-O modelling groups, we find hospitalisations could be between 50 and 10,000 per day by August 31st depending on the R value. SPI-M-O note these scenarios are not forecasts or predictions, leaving open to question their purpose with regard to Government formulation of policy. 

Previous over-estimations of hospitalisations are attributed to: 1) the cancellation of ‘Freedom Day’ on June 21st permitting more vaccinations to be administered and transmission to be delayed due to restrictions; 2) less than anticipated mixing between adults since late April to mid-May; and 3) the effectiveness of vaccines against the Delta variant.

There appears to be no suggestion of an emphatic effect of spring and summer on behaviour, the virus or viral transmission, which would have been considered conventional wisdom until mid-March 2020.

Warwick University

The Warwick models predict the current rise in hospitalisations will persist to peak in late summer or early autumn, which may or may not be accompanied by a small wave – based on the mean estimates – from late December 2021 or early February 2022 depending on supposed “precautionary behaviour”.

None of the Warwick models predict a fall in hospitalisations in summer 2021 nor – by implication – a fall in infections.

Imperial College London

Imperial College offers two models, based on optimistic (upper figure) and central (lower figure) estimates of vaccine effectiveness, adjusted according to estimates of the speed of change in behaviour and the R value. 

Both models predict peaks in the early autumn, possibly delayed to mid-autumn if changes in behaviour are slow. Using these assumptions, the mean estimates presented for hospitalisations are higher than in the Imperial models. 

Central estimates of vaccine effectiveness with sudden relaxation in precautionary behaviour appears to predict mean daily hospitalisations of about 2,500 to about 12,000 per day by the end of September depending on the R value. Imperial have produced a further model based on pessimistic estimates of vaccine effectiveness (not shown).

Of the Imperial models, only the gradual relaxation of restrictive behaviour scenarios indicate a fall in hospitalisations, but in both instances this simply delays a peak in hospitalisations and – by implication – infections until the early autumn. Neither model anticipates an imminent fall continuing into summer, nor a winter peak between December and February.

London School of Hygiene and Tropical Medicine (LSHTM)

LSHTM present similar models based on a further set of assumptions and predict a peak in hospitalisations in mid-summer, varying in size according to the extent of reduction in transmission (five to 20% reduction at medium mobility is shown in the figure).

Again, the LSHTM model precludes the current reduction to a baseline as in summer 2020.

The ZOE Symptom Study, which provides invaluable independent comparator to reported positives figures, appears to show infections to be rising to July 20th, but only since the method of estimation was revised. Comparators such as ONS and REACT-1 are out of date.

Implications of the models

None of the SAGE models predict a sharp fall and summer lull in infections. Rather, the SAGE report states “the prevalence of infection will almost certainly remain extremely high for at least the rest of the summer”.

We are left with two competing hypotheses:

SAGE predict a continued rise in infections, accompanied by hospitalisations and deaths, peaking in mid-summer or early autumn. There may be a further small wave from late December or early February, or none at all.

Parsimony predicts cases will fall to baseline as summer advances, much as occurred in Sweden last year – a late spring or early summer cold that does not cause significant morbidity or mortality. The summer disappearance will be followed by a resumption in the autumn rising to a peak in infections and deaths in winter proper.

Are the SAGE models already wrong?

Although summer peaks in infections in seasonal respiratory viruses are rare, they are not unknown, particularly in novel varieties and, it may be noted that – unlike in Sweden in 2020 – the spring rise in infections in the U.K. arose from a low base and involved a new variant – the Delta variant – and was preceded by the vaccine roll-out.

While vaccination is argued to be the key factor in keeping hospitalisations and deaths figures low, these measures were also low in the late spring 2020 wave of infections in Sweden. It is possible that nosocomial and care-home outbreaks have also been prevented, in part due to the seasonal fall in general demand for hospital beds in the spring and summer. The most recent ONS report shows overall excess deaths in England and Wales to be higher at home than in care homes or hospitals. Nevertheless, it is striking that reported positives in Scotland have been falling since the end of June.

Hospitalisations in Scotland are also falling from a peak approximately a week later.

The rest of the U.K. is now following the trend in Scotland, which showed a rapid fall in infections from the end of spring and beginning of summer, as Sweden did in 2020. Are we simply experiencing a late impact of seasonality on suppression of spread, which has finally taken effect?

Reported positives peaked just prior to ‘Freedom Day’ in England and about three weeks earlier in Scotland. There is no sign of any stall in the falling trajectory of infections in either country, as could be attributed to the relaxation of restrictions on ‘Freedom Day’. This would be not at all surprising to those who observed the lack of impact of ‘opening up’ in Texas and Florida some months ago.

On the basis of current infection data, the SAGE models are already wrong.

So must be the assumptions of virus transmission and effects of Non-Pharmaceutical Interventions – and lack of effect of nature – on which they are based.

It begs the question as to why the Government and media have again so enthusiastically engaged with consistently disappointing predictions leading to such damaging public health policy.

None of this should be a distraction from the point that lockdowns cause a good deal of harm to physical and mental health and to the economy, far outweighing any presumed benefit – if any can be shown. The models, NPIs and lockdowns are about politics, not science.

The co-authors are a PhD epidemiologist trained at a Russell Group University and a retired former Professor of Forensic Science and Biological Anthropology.

With Its Latest Model of Doom, Predicting 10,000 Hospital Admissions a Day in Mid-July, SAGE’s Connection to Reality Has Finally Snapped

SAGE’s claim that the Indian variant could mean 10,000 hospital admissions a day in July assumes that between 30% and 60% of the U.K. population could become infected with the new variant in one week. Glen Bishop, the second year maths student at Nottingham who has buried himself in the epidemiological models SAGE is relying on, has looked at this latest scare story and concluded it is completely and utterly bonkers.

What makes it flat out insane is that the Warwick modelling team that came up with this projection have assumed that the vaccines are as effective against the Indian variant as they are agains the Kent variant – that is, 80% and 90% efficacy against severe illness and death for one and two doses respectively. The only variable they’ve changed to reach their conclusion is to increase the transmissibility. And yet, the team still thinks a plausible scenario – if the Indian variant is 50% more transmissible – is that 10,000 people could be admitted to hospital per day in mid-July if we proceed with steps three and four of the reopening. As Glen says, “Crazy how they got those numbers from their model and took it seriously!” Here’s an extract from his guest post:

To reach admissions three times the January peak, as the model projects, with a vaccinated population, this would mean that between three tenths and three fifths of the population would need to be infected – all in one week in mid-July – just to reach the central estimate projected. Then, the upper confidence interval, shaded in blue on the graph where hospitalisations reach 20,000 per day, would require between six fifths(!) and six tenths (120% and 60%) of the UK population, to be infected in one week. In other words, everybody in the UK would need to be infected and some twice, in one week in July, for the upper bound of Warwick’s projected doomsday scenario to be realised.

Clearly, to anyone who can do back-of-a-fag-packet calculations and type “ONS” into google, these projections are ridiculous and epidemiologically impossible. Yet there were 39 “scientific experts” attending SAGE meeting 89 at which these predictions were rubber stamped for the eyes of the Prime Minister. Is the groupthink so bad that none of them could do a few quick and simple calculations to verify the models were projecting things in the realm of what could be considered reasonable? Or do they not care? SPI-M are so attached to their modelling that they are not even testing it against basic numeracy to verify it.

Worth reading in full.

Stop Press: Prof Lawrence Young, a virologist at Warwick, has told the Mail on Sunday he doesn’t think the Indian variant should delay reopening. “Any rise in hospitalisations and deaths we see won’t be anywhere near previous waves because we have the vaccines now,” he says. “While it is still spreading we have to be cautious, but I don’t think variants should stop us getting back to some sort of normality.”

Not So SAGE After All: A Review of the Latest Models

Glen Bishop, the second year maths student at Nottingham who was the first to spot that none of the modelling teams feeding into SAGE had taken seasonality into account last February, has taken a look at the new, improved models from Imperial, Warwick and the London School of Hygiene and Tropical Medicine that led to headlines earlier this week saying SAGE was no longer predicting an apocalyptic ‘third wave’. (Yipee!) The good news is, the teams have corrected their seasonality mistake when modelling the likely impact of the lifting of restrictions and now graciously allow that summer sunshine will ameliorate the spread of the virus – one of the reasons their latest projections are less gloomy. But there’s also plenty of bad news, as you’d expect.

Here is an extract:

A rational group of scientists would advise that risks are now within the normal accepted range and thus the end of restrictions is nigh and normal life will return. Unsurprisingly, that is not what these three modelling teams have done. Their models have failed to deliver the pessimism and danger craved by scientists clinging on to power, but a new obsession is taking over – the danger of variants. Imperial elaborates: “preventing the importation of variants of concerns (VOC) with moderate to high immune escape properties will be critical as these could lead to future waves orders of magnitude larger than the ones experienced so far.”

Previous Imperial models have made only passing reference to new variants and never tried to model them, yet Imperial’s latest paper, which shows (even with their modelling) the risk from covid to now be incredibly low, is half filled with predictions of theoretical super variants. The most pessimistic of the predictions entails an imaginary ‘high escape’ variant, which, if we stick to the current roadmap, would lead to a peak of over 4,500 deaths per day and a total of 225,000 deaths this summer. To put this into perspective, it would mean a death rate this summer of 3,300 per million, that is double the death rate in Florida since the pandemic began of 1,669 per million despite Florida being near fully open for the last eight months. It’s a higher total than anywhere in the world since the pandemic began. This is void of reality, but even if it weren’t, what is the proposal? Lockdown for another year until a vaccine for this new variant can be distributed, by which time even more variants will have appeared? One might as well include in the modelling a super infectious variant of Ebola or a new improved laboratory leak from our friends in the Wuhan Institute of Virology.

Worth reading in full.

SAGE Modelling From May Last Year Said Approach Recommended in Great Barrington Declaration Was Least Bad Alternative to Lockdown

We’re publishing an original piece today by Lockdown Sceptics regular Glen Bishop, a second year maths student at Nottingham University. Glen has read a paper released by the Warwick modelling team that is part of SAGE’s SPI-M group last May and uncovered some interesting facts. Not the least of these is that when the team modelled what the signatories of the Great Barrington Declaration refer to as “Focused Protection”, i.e. protecting the elderly and allowing those who aren’t vulnerable to the disease to go about their lives taking sensible precautions, as they would during a normal flu season, the projected loss of life between March 2020 and May 2021 was 138,000, only 11,000 more than the 127,000 that have supposedly died from Covid already, with the Government embracing the suppression strategy endorsed by SPI-M. The modelling team also acknowledges that of all the alternatives to an indiscriminate lockdown, shielding those aged 60 and over would have resulted in the least loss of life as well as the least socio-economic disruption. Here’s the key paragraph from the Warwick paper:

A completely uncontrolled outbreak is predicted to lead to around 200,000 deaths, approximately 2 million QALY losses but no lockdown impacts. If the current controls are maintained until the end of 2020, then we predict 39,000 deaths this year [2020], but a further 159,000 if controls were then completely removed. Regional switching and age-dependent strategies provide alternative exit strategies in the absence of pharmaceutical interventions. Of these, the age-dependent shielding of those age 60 or over generates the lowest mortality and also the lowest lockdown scale, thereby minimising socio-economic disruption. However, it is unclear if a protracted lockdown of this age-group would be practical, ethical or politically acceptable.

Glen’s article is worth reading in full.