Imperial’s Pessimistic Model

Boris has clearly been spooked by a new gloomy modelling study by the Imperial Group which puts his road map to normality in jeopardy. How is this possible when the UK’s case rate is falling and ~ 50% of the population are vaccinated ?

Well you can trace everything back to one crucial  parameter Imperial are using in their model.

We assume the vaccines prevents to a certain extent, an infected person who is vaccinated from transmitting the virus (optimistic, although only assumed in 1 sensitivity analysis). 30% after 2 jabs and 0% after 1 dose.

So according to Imperial, vaccination only has a minor effect on transmissibility. You can still get infected even if you have been vaccinated and then infect other people without ever noticing. If this were actually true then the pandemic would never end and we would remain in permanent semi-lockdown. If instead vaccinated people can’t catch covid and don’t transmit infection to others then the pandemic will soon be over, once 75% of the population are vaccinated. That is because they assume the Kent variant is now dominant with an R0 = 4. So once  3 out of 4 people are immune R falls below 1 permanently without any social distancing restrictions. This is Herd Immunity !

So where does their low value of 30% reduction in transmission come from? It is all based on this study of  care home workers and their family members:

Effect of vaccination on transmission of COVID-19: an observational study in healthcare workers and their households

The samples from that study were as follows :

194,362 Household members : 3,123 COVID cases
144,525 Healthcare workers : 4,343 COVID cases

The healthcare workers fell into two groups A) those vaccinated = 113,253  and B) those unvaccinated = 31,272

The study found: Household members of vaccinated healthcare workers had a lower risk of COVID-19 case compared to household members of unvaccinated healthcare worker (rate per 100 person-years 9·40 versus 5·93; HR 0·70, 95% confidence interval [CI] 0·63 to 0·78).   I make that a 37% reduction in infections in households with a vaccinated healthcare worker.  Imperial use this result as direct input to their model i.e. assuming that vaccination reduces transmission by just 30% but only after the 2nd dose, and 0% after the first dose of the vaccine ! There are 12 weeks between the 1st and second doses in the UK so this makes a huge difference on Reff.

The basic assumption Imperial makes is that health care workers alone can bring Covid home and then infect others within their household. Yet this is obvious nonsense because their partners and other household members also have jobs, go shopping, and attend school etc. Perhaps some of them even work as care home staff. Imperial ignores the fact that they can catch COVID from hundreds of other people outside the household. In early February 1 in 60 people had COVID in the community and infection rates were high everywhere. So in that context a 30% net reduction in household infection really is an impressively large effect.

We can also check this. The paper was published on March 21 so the data must have been collected over a period ending a couple of weeks earlier. ONS data shows that infection rates fell from  1 in 50 to about 1 in 200 by the end of February so a fair average over January to February would be ~1.0 %.

Therefore you would expect up to 2000 cases from community infection alone in Household members. So a 30% total reduction now translates into a  78% reduction in direct  healthcare worker transmission.

If you remove this baseline of community infections then the correct figure should be more like a 60% reduction in transmission by healthcare workers after the first dose and an 80%  reduction after the second dose. If they use these figures then their gloomy predictions disappear !

 

Posted in Covid-19 | 2 Comments

Net Zero by 2050

The 2008 Climate Change Act introduced by Ed Milliband committed the UK in law to cut CO2 emissions by 80% in 2050. This target was already difficult to achieve, but since then Theresa May went one better in the weeks before she left office, by enshrining  in law a commitment to reach net zero carbon emissions by 2050. Neither she nor Ed Milliband had really any idea just how to achieve such lofty moral goals, but in 2050 they would both be long retired, and their short term political legacy clearly benefited them. The  Climate Change Committee (CCC) with Lord Debben as long term chairman now smugly define our  allowed 5-yearly “carbon budgets”.

The UK acting alone makes no sense unless the rest of the world follows our example, and that is very unlikely to happen while the developing world strive to improve their living standards and population increases. So how feasible is it for the UK to reach net zero emissions and what are the implications?  A group of academics have been looking into exactly that question. How do you stop emitting any CO2?

Firstly everything has to be electrified – heating, transport, trade, food. Secondly we  have to somehow rely mainly on Renewable energy (an  expansion of Nuclear Power is not considered). This means drastically reducing our net per capita energy consumption and adapting  to living instead with variable seasonal power sources.  Thirdly we also have to decarbonise agriculture, industry and international trade. This means new steel production in blast furnaces is out, and only recycling scrap steel is allowed. Cement production is out because it generates large amounts of CO2. Aviation is out since  electrifying planes is not feasible any time soon. Likewise shipping, fishing and international trade is out because they depend on burning oil

“Key Message: In addition to reducing our energy demand, delivering zero emissions with today’s technologies requires the phasing out of flying, shipping, lamb and beef, blast-furnace steel and cement.”

The problem is that  shipping is currently crucial to our well-being – we import 50% of our food, and we don’t know how to build new buildings or install renewables without cement. Here is their roadmap

Click to expand

I am sure that if the UK public were made aware of all what is planned for their future there would be a public uproar.

  • No Flying after 2030 (except VIPs of course)
  • No gas central heating within ~12 years.  Heat pumps only allowed and colder houses.
  • Only electric cars post 2030 and a 40% reduction in traffic.
  • Vegetarian only diet and no imported food.
  • Shutdown of international trade and reduction in living standards
  • International travel curbed except by train.

Perhaps COVID lockdowns are simply preparing us for something far worse – what the Climate Scientists and Greenpeace all have in store for us to save the “climate”.

Boris says we must be led by the science, but such  stupidity could well lead us all down an infinite rabbit hole!

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Road map to unlock the UK

The government’s roadmap to end lockdown is all  based on the modelling from Imperial College. Here we show why their report is too pessimistic and that lockdown can probably  be ended safely sooner.

The paper states

Current levels of transmissibility are based on our latest estimates for England at Reff (including immunity) =0.75 (translating to Rexcl_immunity =1.10 with an estimated 32% of the population currently protected via prior infection- and/or vaccine-induced immunity).

They are saying that without any vaccination R would be 1.1 even under the current strict lockdown and cases would still be increasing. Presumably this is because they think the Kent strain is now dominant in the UK (with a natural R0 = 3 to 4). They are assuming that as of 22nd February 21 million people are now “immune” from either vaccination  or from a previous infection. However their immunity is not 100% so to compensate for that they apply an efficacy factor for each vaccine (Pfizer, AZ)  and an age dependent “uptake factor” to account for those who refuse to be vaccinated.

The modelling always works in the standard R (no immunity) and then applies the vaccine effect to deduce the number of cases at each step in the proposed un-lockdown process. So this means they are not directly modelling the vaccination itself but are simply applying a correction factor to deduce what the actual  value – Reff actually is.

So for Astra Zeneka (AZ) their factor for protection against hospitalisation (severe disease) for over 50s  is ~ 0.8 * 0.85 = 0.68 and for the over 80s is 76%. This implies that vaccination only protects 68% of the over 50s! They assume deaths are also only reduced by 68%.  However, real life data tells another story. The recent Scottish survey found that 28 days after the first dose of AZ hospitalisations of the over 80s were reduced by 94%! This is a staggering difference. It means that we can probably simply reduce  all their figures by 20%.

Furthermore their calculations of Reff assumes that just 68% of the population are susceptible due to their low vaccine efficacy and hesitancy. This value evolves as  mass vaccination progresses but their low protection factor slows down its effect.  This is why unlocking the UK is so painfully slow.  However In about one weeks time all people over 65 will have been vaccinated (95%) with 94% effectiveness – 90% in all. This this would already  reduce the death rate by ~90% as shown by the Spectator tracker.

Modelling

Their modelling is really rather crude. It is essentially just  “best” guesses

We assume that going from level 7 to level 6 (opening schools) will increase R_excl_immunity by an average +0.5 (+0.25 if opening only primary schools). This is based on the consensus value from SPI-M accounting for the increase in transmission due to the B.1.1.7 variant. The impact of switching from level 6 to 5 is difficult to quantify but is likely to be small, and we assume an increase of on average +0.1 in R_excl_immunity.

To model the average change of transmission between level 5, 3 and 2, we used the analysis by Laydon et al. (unpublished, previously presented at SPI-M) which estimated level 3 and 4 as having respectively 94% and 74% of the level of transmission of level 2.

We modelled level 4 as an intermediate between levels 3 and 5 (i.e. tier 2 and tier 3), with an average R_excl_immunity taken as the mean of the values used for levels 3 and 5.

Lastly, the final baseline transmissibility once all NPIs are lifted is assumed to be on average R_excl_immunity = 3, consistent with an increased in transmissibility due to B.1.1.7 but with a slightly lower level of transmission due to baseline NPIs. Due to the uncertainty in predicting the behaviour of individuals after the lifting of most of the restrictions, we also consider a baseline R_excl_immunity of 4 as a sensitivity analysis.

Seasonality.

From late June until September there were very few cases in the UK. Boris Johnson removed nearly all restrictions in July and cases did not increase. The virus does not spread in Summer. This effect is even stronger in Italy which suffered worse at the beginning of the pandemic. Life returned to normal for July to September but cases did not rise. The outbreak seems to take off again once temperatures fall  in late summer/autumn.

The conclusion is that there is a natural seasonality effect with Covid-19 suppressing spread of the virus during summer months. Yet the Imperial modellers almost completely ignore this effect. This is what they write.

In our main analyses we assumed no seasonality in SARS-CoV-2 transmissibility. We performed a sensitivity analysis where we assumed seasonal patterns of transmission throughout the year was 20% in the UK measured as the relative peak to trough variation.

A tiny 20% variation in R between January and August is incompatible with the data both in Italy and the UK. Both countries had children back to school, relaxed NPIs during the summer and their citizens went on holidays at home and abroad, yet cases did not rise. They only rose again as summer ended.  Kenya has a population similar to the UK but has only seen 1839 deaths in total compared to nearly 122,000 in the UK (1.5%), yet there are no NPIs in Kenya. Anyone who has ever been to Nairobi will confirm how just how lively and chaotic it is. The reason for this is obvious. Kenya lies on the Equator and COVID-19 doesn’t like high ambient temperatures! This summer cases will naturally drop again in the UK. So the Imperial team always seem to verge on  pessimism.

  1. They assume R_excl_immunity = 4 without any restrictions (NPIs) reducing to 3.2 in summer.  Yet R was clearly around 1 during most of last summer as we all went on holidays both in the UK and Europe..
  2. They use a low estimate of vaccine effectivity and a pessimistic view of likely uptake. The Scottish study shows very high effectivity and uptake is high. The supply of vaccine is the only limiting factor.
  3. They assume the seasonal effect on R is tiny.
  4. It is full of other pessimistic dire warnings

Boris Johnson has been forced by this report to accept a  cautious step by step plan with lockdown ending by June 21 at the earliest. Imperial’s cautious (gradual) proposed date was August 2, nicely timed to ruin everyone’s summer!

I suspect that all restrictions can safely end in early June once everyone at risk has been vaccinated. Will SAGE try to stop  it happening  though ?

Posted in Covid-19, Health, Public Health | Tagged | 3 Comments