What SAGE got wrong

On March 16 Boris Johnson held his daily COVID briefing and for the first time introducing tentative social distancing measures. That same day Neil Ferguson had formally  published his simulation of how the UK epidemic would unfold and which suppression measures were needed – Household Quarantine, Place Closure, Case Isolation and Social Distancing (Report 9).  The paper must have been circulated within SAGE far earlier than that.  A full lockdown was finally introduced a week later on March 23. Unfortunately Fergusson’s  timing was about a  month out of date and the real situation was far worse than even he assumed. The real number of cases and rate of infection by March 16 in the UK was in reality far higher. However  no-one knew this at the time because there was no community wide testing amid what now appears to be an air of complacency by PHE.

We can now look back and compare what actually occurred with the original Report 9 simulations which I have rerun. This is shown in Figure 1.

Figure 1. Neil Ferguson’s COVID simulation results (Report 9) as compared to actual COVID deaths as recorded in English Hospitals. The peak in English deaths occurred on April 10. This is compared to the Report9 green lockdown simulations and  a one month delay (solid black) of the model.

The peak in infections and deaths occurred one month earlier than he or anyone else had anticipated. Fergusson had predicted in report 9 that the peak would occur much later  around mid May. That was probably because he was using the Chinese data for R0 (2.4) and used an optimistic estimate of  the number of current UK infections. When the report was published there had been very few confirmed deaths.  However we now know there were probably  tens of thousands of infections. SAGE  now estimate that R0 in early March was 3 and that the number of infections was doubling every 3 days.

If the UK had locked down a week earlier the resultant number of deaths would have been much lower with at least 20,000 fewer deaths and we would be exiting lockdown by now (June 7). However at the time no-one knew the full extent of infection due to the total lack of community testing.

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Report 9

On March 16th Neil Ferguson’s team published “Report 9” which changed government policy and triggered a “lockdown” a week later. The results of his simulation showed that the number of COVID  patients would soon overwhelm the ~4000 ICU bed capacity in the NHS. The code that produced his results has now been made available and I have spent the last few days struggling to get it working. Here are the first results I get after running Ferguson’s “Report 9″model.

COVID simulation for UK if left “unmitigated”

and in yet more detail.

Predicted “unmitigated” deaths using R0=2.4 IFR = 0.9% as used in report 9.

I was surprised to see the date of the peak predicted by the model because in reality the epidemic  occurred about a month earlier (starting March 1). So it looks like Ferguson originally thought that we had much more time to prepare for this emergency than in reality we did have.

The main impact of this report were the  measures he proposed to suppress the epidemic thereby avoiding “overwhelming the NHS” and “save lives”. I have spent the last 3 days struggling to get his code working and it has been a bit of a nightmare. The released procedure as was published on GITHUB could only really be run on a supercomputer,  while instead I have an iMac! There are 4 types of suppression interventions.

  1. PC – School and University closures, restaurants, bars, non-essential shops etc.
  2. CI – case isolation (7 days)
  3. HQ – Household quarantine (14 days)
  4. SD – Social distancing (at various levels)

The newly released “report9” process proposes to run the Covid-Sim model 10 times (multi-threaded) and then take the average. (The main reason to run it 10 times is because you get slightly different values each time).  In addition to this there are an additional 45 combinations of intervention strength and 4 different values of R0  (2.0, 2.2, 2.4, 2.6 ) to run. This makes a grand total of 180  CovidSim batch jobs, which is equivalent to 1800 single threaded runs! This can only really be run on a supercomputer. The full suite of combinations is basically impossible to run on my iMAC. So instead I decided  to restrict all my combinations to a single run (instead of 10) and to use only R0=2.4 because this was used in his original paper.  This produces a more reasonable set of 60 sequential runs which still took me about 2 days to finally finish while getting a headache. Here are the results I get for one  typical 4 level intervention scenario, more or less  corresponding to those shown in report 9.

Impact of 4 suppression scenarios on predicted deaths. The green curve more or less represents the lockdown measures the UK consequently adopted. Note that the dates are  a month later than what actually occurred. The maximum peak in deaths/day reached in the green scenario is ~ 400

Intervention detail. I am not yet quite sure why the second peaks appear yet !

The full lockdown measure finally adopted is shown in green resulting in a smaller peak in deaths after about 28 days followed by a long tail. So how do these prediction compare to what actually happened in reality. UK lockdown measures were introduced on March 23rd a month earlier than envisaged above. Here are the daily deaths in hospitals (excluding care homes) as reported by the NHS.

UK Hospital deaths by actual date

This indeed shows the same shape but twice as many deaths occurred than expected, yet at no time were ICU beds overwhelmed. The outbreak occurred a month earlier than Ferguson predicted. This  seems to be because there were far more infections in the community than were originally thought. It is now estimated that R0 was actually 3 instead of 2.4.

Hindsight is a wonderful thing, but it seems pretty clear that the UK  should probably have locked down a week earlier, and as a result total deaths probably would have been halved.

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Update: (27/5) If you compare Sweden with a lockdown imposed on the same date as UK (March 23) then Sweden is apparently doing much better.

Everyone is watching Sweden where the chief epidemiologist Anders Tegnell has resisted lockdown. Cafes, schools and restaurants have all remained open throughout. Their policy of voluntary social distancing measures while protecting the elderly seems to be working.

I ran Ferguson’s model for Sweden after finally working out how he normalises to different populations. Basically he normalises model death predictions to those actually recorded for a specific date. For the UK this date is April 10 (10,000 deaths). This is how the model compares to Sweden if I use the same date (400 deaths). First with lockdown on 23 March.

Swedish deaths are less than predicted under a March23 lockdown scenario

Now with lockdown a week earlier on 16th March

ICL model compared to deaths in Sweden. The blue curve is a UK style lockdown beginning 16th March ( a week earlier than UK). The red curve is unmitigated deaths. The green curve are recorded deaths.

Accumulated deaths then appear to be about 1000 higher than they would have been had they applied a UK style lockdown on the 16th March. However the UK figures also show an overshoot of about 5000 deaths even with the 23rd March lockdown.

Different ICL lockdown timing simulations. The green and cyan graphs follow what actually occurred.

So in general Sweden and the UK are in a similar state currently. However the Swedish trend is showing a smaller decline implying that R is around or slightly above 1. If the goal in Sweden is to reach herd immunity while protecting the elderly, then it seems to be working. Everything will depend on whether a vaccine becomes available in September. If not then Sweden’s strategy could well pay off.

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