LSHTM

Just Say No, Prime Minister

This feels like a pivotal moment.

Boris could listen to the doom-mongers urging him to impose tighter rules after Christmas, just as Nicola Sturgeon and Mark Drakeford have done. The modelling team at the London School of Hygiene and Tropical Medicine predicts the number of daily Covid hospital admissions will rise to 7,190 in January, but that’s far from the most apocalyptic scenario. Not to be outdone, Neil Ferguson and his team at Imperial College have estimated that Covid deaths are likely to rise to 5,000 a day without further restrictions. Hardly surprising, given the virus’s “exponential growth”. According to the Prime Minister’s scientific advisors, the number of daily Omicron infections is doubling every two-to-three days. Or is it every two days? Or every one-and-a-half days? They’re certainly growing very, very quickly. And it isn’t just Chris Whitty screaming in Boris’s ear demanding he do something – anything! – to stop this tidal wave engulfing our beloved NHS. Health Secretary Sajid Javid told Parliament earlier this month that the number of new cases could exceed one million a day by the end of December. That’s in a week’s time. Crikey Moses!

Or Boris could look at the actual data, as several members of his Cabinet have been urging him to do. The data from South Africa suggesting Omicron is 80% milder than Delta. The data suggesting that, far from doubling every couple of days, the number of daily infections is plateauing. The data suggesting that, for whatever reason, the link between Covid infections and hospitalisations has been broken, with Covid hospital admissions remaining largely flat over the past two weeks in spite of the uptick in daily infections. The data on the length of time Omicron patients stay in hospital, with one South African study showing the average hospital stay had been reduced from 8.5 days to 2.8 days. The data – endlessly reproduced on this site – showing that non-pharmaceutical interventions do little or nothing to suppress Covid infections, with every wave following exactly the same trajectory, regardless of the severity of the restrictions, or whether any containment measures are imposed at all.

The reason this is such a momentous decision is because it will set the pattern for every subsequent response of the Government to the emergence of a new variant, of which there will be many. If Boris can hold his nerve over the next week or so and the Omicron fire shows signs of burning itself out without the need for any further measures, that will leave the gloomsters of SAGE looking very silly indeed. It will be obvious to everyone, even the most fanatical lockdown zealot, that they’ve been crying wolf. It might even permanently break the spell they’ve cast over the nation for the past 22 months.

Latest Modelling on Omicron Ignores All Evidence of Lower Severity, Among Numerous Other Problems

We’re publishing a guest post today by former Google software engineer Mike Hearn about the shortcomings of the London School of Hygiene and Tropical Medicine’s alarmist Omicron modelling which has spooked the Government.

Today the Telegraph reported that:

Experts from the London School of Hygiene and Tropical Medicine (LSHTM) predict that a wave of infection caused by Omicron – if no additional restrictions are introduced – could lead to hospital admissions being around twice as high as the previous peak seen in January 2021.

Dr Rosanna Barnard, from LSHTM’s Centre for the Mathematical Modelling of Infectious Diseases, who co-led the research, said the modellers’ most pessimistic scenario suggests that “we may have to endure more stringent restrictions to ensure the NHS is not overwhelmed”.

As we’ve come to expect from LSHTM and epidemiology in general, the model forming the basis for this ‘expert’ claim is unscientific and contains severe problems, making its predictions worthless. Equally expected, the press ignores these issues and indeed gives the impression that they haven’t actually read the underlying paper at all.

The ‘paper’ was uploaded an hour ago as of writing, but I put the word paper in quotes because not only is this document not peer reviewed in any way, it’s not even a single document. Instead, it’s a file that claims it will be continually updated, yet which has no version numbers. This might make it tricky to talk about, as by the time you read this it’s possible the document will have changed. Fortunately, they’re uploading files via GitHub, meaning we can follow any future revisions that are uploaded here.

Errors

The first shortcoming of the ‘paper’ becomes apparent on page 1:

Due to a lack of data, we assume Omicron has the same severity as Delta.

In reality, there is data and so far it indicates that Omicron is much milder than Delta:

Early data from the Steve Biko and Tshwane District Hospital Complex in South Africa’s capital Pretoria, which is at the centre of the outbreak, showed that on December 2nd only nine of the 42 patients on the Covid ward, all of whom were unvaccinated, were being treated for the virus and were in need of oxygen. The remainder of the patients had tested positive but were asymptomatic and being treated for other conditions.

The pattern of milder disease in Pretoria is corroborated by data for the whole of Gauteng province. Eight per cent of Covid-positive hospital patients are being treated in intensive care units, down from 23% throughout the Delta wave, and just 2% are on ventilators, down from 11%.

Financial Times, December 7th

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.

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.