Explaining the Leicester COVID-19 Outbreak

Full playlist of BBC Interviews here

The Home Secretary, when questioned on the BBC Andrew Marr show announced on Sunday 28 June

‘there is going to be a Leicester lockdown?’
‘So, there will be support going into Leicester … with local flare-ups, it’s right that we have a local solution’

But looking at the public data from coronavirus.data.gov on Covid infections, Leicester does not have a significant problem:

It is only when you look at the Public Health England surveillance report, you notice something awry.

(Leicester is the red area inside the orange Leicestershire at the centre of the country.) Source:
National COVID-19 surveillance report: 25 June 2020 (week 26)

https://www.gov.uk/government/publications/national-covid-19-surveillance-reports

Why the dispartity? This comes from the difference in how tests are reported. Coronavirus.data.gov only reveals so-called ‘Pillar 1’ tests (those in the NHS), wheres the PHE maps include both Pillar 1 and Pillar 2, the latter being conducted under the auspices of NHS Test and Trace and other commercial partners.

Data from Pillar 2 tests is only just getting through to Directors of Public Health. And the number of people tested is still not disclosed (the number of people tested is still ‘unavailable’).

As of 9am 28 June, there have been 9,195,132 tests, with 127,709 tests on 27 June. 

311,151 people have tested positive. 

As of 5pm on 27 June, of those tested positive for coronavirus, across all settings, 43,550 have sadly died.

Test data are as of 9am, 28 June. Deaths data are as of 5pm, 27 June.

Notes: Reporting on the number of people tested has been temporarily paused to ensure consistent reporting across all pillars. Due to revisions to historical data, the cumulative total for tests is 154 lower than if you added the daily figure to yesterday’s total.

Public Health England only report publicly the level of outbreaks at the Upper Tier Local Authority level (mostly county councils, unless there are large cities such as Leicester where the are unitary authorities).

So, how do we know that there isn’t an outbreak in our local area? Basically, we don’t. But the PHE surveillance report is the best we have for now. Also worth examining the cluster of outbreaks around Manchester (which may be outbreaks in schools or hospitals)

PHE Surveillance Report week 26

What appears to be unusual about the Leicester outbreak is that it does not appear to have been traced back to care homes, hospitals, or schools. It appears to be community transmission, and is the first real test of the Government’s policy of preventing a resurgence of COVID-19

Muddling Through Does Not Work for Pandemics: COVID-19 Letter Published in The Financial Times

In 1959, Charles Lindblom wrote The Science of “Muddling Through”, advocating an incremental approach to public policy and management. “Muddling through” does not work for pandemics. The science of pandemics is dominated by epidemiology, not behavioral science. The delay between policy decisions (or indecisions) and the resultant high UK death rate needs tracing back from the prime minister and his advisers to Cobra, the chief scientific adviser, and the Scientific Advisory Group for Emergencies. However, this is one form of contact tracing that can be delayed until the inevitable public inquiry.

Dr Duncan Robertson
Fellow in Management Studies,
St Catherine’s College,
University of Oxford, UK

Charley Says Social Distancing

Charley was a character in UK Public Information Films in the 1970s. Here he is in ‘Charley Says Social Distancing’


“Treat everyone else as if they’re about to catch fire and you’re a lit match.”


Charley: Miaoweeaawwwoa [I can’t believe I’m writing this]

Narrator: This is you. You’re a match. And these are your friends. You catch the virus and you’re on fire. You’re too close – now all your friends are alight – you’ve infected them with the virus.

Tony, the Boy: Charley says that if ever you see a box of matches lying around, tell mummy because they can hurt you.

Narrator: We’d like the virus to spread slowly so to match the capacity of the health service. It takes a few days before your friends get ill, so you can’t see it spreading.

The virus is spreading rapidly so we need to slow it down. If you’re older or have an underlying medical condition, you need to stay apart.

That’s better. Keep apart. Treat everyone else as if they’re about to catch fire and you’re a lit match.

Charley: Awoooarwah.

SOCIAL DISTANCING. DON’T GET TOO CLOSE

For advice on COVID-19, see:HM Government NHS (UK National Health Service) WHO (World Health Organization) US CDC (Centers for Disease Control and Prevention) US NIH (National Institutes of Health)

YouTube Link: https://www.youtube.com/watch?v=4YmN0iV3f0I

Twitter Link: https://twitter.com/Dr_D_Robertson/status/1241307225626423296

I am concerned about the UK Government’s approach to social distancing

The real problem with Coronavirus Covid-19 is that when the health service becomes overloaded, the death rate goes up significantly. So, it is imperative that we keep the number of cases at any one time below or as near as possible to NHS capacity.

The Government’s model relies on shifting the peak. I am not clear that we are doing this fast enough. We are an outlier compared to other countries in our social distancing policy response.

There is a tension between epidemiologists – those who study how diseases spread (a very established science started around the time of the Spanish Flu 100 years ago), and behavioural scientists who study how people behave and react.

Epidemiologists have models validated against past pandemics. Behavioral scientists do not.

There are economic and social costs of social distancing. But if you delay social distancing too much, there are potentially very real human costs in increased mortality. Doctors will need to make very difficult moral decisions on who to treat and who not to treat.

I do not understand why, if the intention is to create herd immunity, why we are not isolating our vulnerable population, especially those in care homes.

Behavioral insights are great when you are trying to get people to pay their tax bills on time. And if people don’t, it doesn’t really matter. With a pandemic, if you get the timing wrong, more people die unnecessarily. Then you look back from your computer and say, yes, we got that behavioral model wrong while doctors and nurses on the front line are exposed to extra cases that could put their own lives at risk.

Here’s a video to show what we should be trying to do:

Social Distancing using Play-Doh and Matches

There has been much talk about using social distancing as a response to the Coronavirus outbreak. Here’s a video of how social distancing can be used:

  • Close Contact, where the population is infected very rapidly. This is not A Good Thing – the national health service is overwhelmed, and the death rate goes up as a result
  • Extreme Distancing, where the viral spread takes too long. This is not A Good Thing – the social and economic costs are huge
  • Optimal Distancing, where the spread is controlled and the human, social, and economic costs are optimized. This is A Good Thing. It is also very tricky to get right.

Coronavirus: The First Big Test of Behavioral Science

The United Kingdom is at a crossroads, an ideological battle between natural science and behavioral science. Let’s hope for all our sakes we get this one right.

Boris Johnson, the UK Prime Minister, is facing a dilemma. When do we go from the so-called containment phase for controlling Covid-19 Coronavirus, to the delay phase.

In the medical / natural science corner, is the Chief Medical Officer, Professor Chris Whitty, who has presented himself calmly, reassuringly, as completely on top of his brief. He is a physician and an epidemiologist (as well as a lawyer, and an MBA). His evidence at the newly formed House of Commons Coronavirus Committee was calm, frank, precise. He is exactly the sort of advisor that any government would be proud to have. Flatten the peak. Delay the virus spread. Keep the height of the peak low. Save lives.

Mitigation efforts like social distancing help reduce the disease caseload on any given date, and can keep the healthcare system from becoming overwhelmed.
Image: New York Times adapted from CDC/Economist https://www.nytimes.com/2020/03/11/science/coronavirus-curve-mitigation-infection.html

In the behavioral science corner is, well, I am not sure who. Maybe it’s the Chief Scientific Advisor, who highlighted the need to take account of behavioral science. Yes, please do. It’s a wicked problem, and please include more complex social modelling.

But what we are now seeing is what the Director General of the World Health Organization (up until now also criticised for its seemingly political response to the issue) could be referring to as ‘alarming levels of inaction’.

I do hope, however, that Boris Johnson is being guided by the science, both behavioral and epidemiological, and not by advisors who profess to be superforecasters. You don’t have to be a superforecaster to forecast that if we get this wrong, many will die unnecessarily.

Contagion: How to Model It and What R-nought (R0) Actually Means

The 2011 film Contagion, starring the spectacularly ill-fated Gwyneth Paltrow, is a dramatization of a viral pandemic starting in pretty analagous circumstances to the current Wuhan Coronavirus (2019-nCoV) outbreak. It’s a good film, and is a great introduction to the work of Centers for Disease Control (CDCs) that monitor the spread – the epidemiology – of the disease. There are two scenes where R-nought, or R0, are described:

Despite the blogger character in the clip describing the spread, using a R0 of 2, as being a problem you can do on a napkin, it takes a little more thinking about. He also seems a bit confused about R0, talking about growth from 2 to 4 to 16, to 256, to 65,536 each day. That’s not what R0 is – it is not a rate, and actually if the rate was 2, this would mean 2 to 4 to 8 to 16 to 32 etc., each time doubling the number. It is possible that he is thinking that there are two generations each per day, but that’s not whatR0 is.

So, on to the professionals:

The CDC epidemiologist in the clip is more on point (despite having sloppy notation with no subscripts). This is better – it shows the reproduction number for the infection – note again, this is not a rate – no time dimension is involved – it basically shows the number of cases on average each case generates.

This population modelling – so called SIR (Susceptible, Infected, Recovered) system dynamics modelling – is just one of several approaches that can be used to model contagion across a population. My recent paper ‘Spatial Transmission Models: A Taxonomy and Framework’ sets out a review of what they are and the advantages and disadvantages of each. In brief, we can model the population numbers, the individual agents that carry the virus, the network of contacts between infected individuals, or the regions or cells in which individuals are located (city districts, for example). The paper is available to read by clicking on the link here.

Speech given at a meeting of Congregation of the University of Oxford, 7 May 2019

Dr Duncan Robertson, Fellow of St Catherine’s

Vice-Chancellor, members of Congregation. I look around this room and see privilege.  Every one of us here in the Sheldonian Theatre is privileged; every member of Congregation reading the Gazette is privileged.  We are privileged not by our past but by our present: we all have the power to share in the democratic self-governance of the institution that is the Collegiate University of Oxford.

But democratic self-governance is hard.  It is time-consuming and troublesome, and is most easily left to specialists.  Specialists with a track record of delivering strategic plans at high speed.

The Vice Chancellor warned us of the dangers of high speed in her 2017 Oration, and I quote: Over 2,000 years ago Tacitus pointed out that ‘Truth is confirmed by inspection and delay; falsehood by haste and uncertainty’.

It is tempting to react quickly to short term opportunities in order to gain transient rewards, but this is, as my strategic management colleagues will confirm, often at the expense of more attractive opportunities foregone.  We must, at the very least, be able to give ad hoc proposals the service of being fully inspected.  The proposal to establish a new Society – or is it a College? – is a significant one, particularly when it is to have a distinctive culture as was the case with Templeton College before it.

The reason that an ‘education priority’ within the Strategic Plan has abruptly become a press release announcing Parks College, without the knowledge of Congregation, is that such proposals are now increasingly made without such scrutiny.  While the Strategic Plan was put to Congregation for approval, the Implementation Plan referred to within the Strategic Plan was not.  This ‘Plan within a Plan’ is administered by Programme Boards whose agenda and minutes are secret.  In short, Congregation does not know what is going on, and its ability to give informed consent is subverted.

One of the strengths of Oxford that sets it apart from its ‘competitors’ is its self-governance.  This has allowed the University to evolve and adapt to a changing environment, and mercifully not be suffocated by the latest management fads and fashions.  It is bewildering that ‘Senior Managers’ do not appear to recognize the capabilities available to them within Congregation, preferring to operate in a more comfortable ‘command and control’, top-down fashion.  If strategy is imposed, we as a University lose the ability to adapt and to take advantage of opportunities that may emerge – opportunities that may not be visible from the board room but are visible from the diversity of perspectives that each one of us holds as a unique member of Congregation.

The combined organizational capabilities of Congregation – all members of Congregation, experts in their own fields whatever they may be – are truly awe-inspiring.  It is not always easy to find consensus, but that does not mean that this University should give up and follow the lowest common denominator of managerial hubris.

Congregation must be allowed to review and guide the Legislative Proposal to create Parks College prior to giving its approval. The Strategic Plan spoke of creating a new College by 2023, not a new Society in 2019.

The Nolan Committee on Standards in Public Life was established 25 years ago.  The principles of openness and accountability which it set out are as relevant now as they have ever been.  I urge you to vote against the Legislative proposal while we still have the right to exercise that privilege.

Mapping Brexit

Wednesday’s indicative votes in the House of Commons produced no definitive answer of the way forward.  By using social network analysis showing the size of each voting bloc and ‘Hamming distances’ (ironically usually used for error correction), we can map how close MPs are to each other, giving an indication of how a coalition could be made if each block of MPs flipped their vote in order to form a Parliamentary consensus.

Brexit is currently turning out to a failed experiment in direct democracy, something I pointed out nearly three years ago.

However, with the House of Commons opening up data, it does allow us a rare insight into the goings on of the population and the MPs that are our representatives.

One interesting data source is released by the UK Parliament showing the voting record of every MP for every ‘division’ (vote). One particularly interesting vote was that done on Wednesday 27 March, where MPs were able to cast their votes for 8 motions:

Mr Baron’s motion B (No deal) ,
Nick Boles’s motion D (Common market 2.0) ,
George Eustice’s motion H (EFTA and EEA) ,
Mr Clarke’s motion J (Customs union) ,
Jeremy Corbyn’s motion K (Labour’s alternative plan) ,
Joanna Cherry’s motion L (Revocation to avoid no deal) ,
Margaret Beckett’s motion M (Confirmatory public vote) , and
Mr Fysh’s motion O (Contingent preferential arrangements)

By making a so-called bipartite network, we can map individual MPs to the votes for which they voted yes. This results in a map of MPs shown below.

(c) Dr Duncan Robertson duncanrobertson.com

While this is interesting, it doesn’t really show the distance between MPs’ voting intentions.

We can redraw the map by using the distance between MPs according to the votes they cast. We can do this by constructing a binary string of their votes. For simplicity, we count only the ‘aye’ or yes votes, and ignore abstentions and nos.

For instance, if an MP voted yes, no, no, yes, no, yes, yes, no, they would be given a string of 10010110, whereas if another MP voted no, no, yes, no, yes, yes, no, yes, they would be given a string of 00101101. So, what is the ‘distance’ between 10010110 and 00101101? For this, we use the Hamming distance – count the number of locations where there is a difference. In this case, the Hamming distance between the MPs is 6.

By constructing a graph of Hamming distances of 1, we can construct neighbours of individual groups of MPs. This is shown in the graph below.

I have listed the votes in the following order:

Common Market 2.0
Confirmatory Public Vote
Contingent Preferential Arrangement
Customs union
EFTA and EEA
Labour’s Alternative Plan
No Deal
Revocation to Avoid No Deal

(c) Dr Duncan Robertson duncanrobertson.com

However, this isn’t very useful, as it doesn’t show the type of MP that voted for each of these. So we can relabel the nodes with a representative MP from that bloc.

From this, you can work out the number of intermediate MPs to get to any other MPs. What is quite interesting is that every MP was just one vote away from another – no-one is isolated. Which, in some little way, gives us hope.

(c) Duncan Robertson duncanrobertson.com

We can then weight the edges to show the possible coalition that could be made if these blocs were to join. And here it is:

The size of each circle represents the number of MPs that voted the same way as the representative MP named on the circle, and the thickness of the links shows how many MPs would join together if one vote were flipped.

If the linked blocs join up, you can see how there could be a path to a Parliamentary majority – for the blocs to join, it would mean switching one vote from ‘aye’ to ‘no’ or vice versa.

For completeness, the list of MPs and their associated binary string is linked here. You can find the MPs that are part of each bloc by searching for the MP name in the label on the network graph. The Hamming distance between each and every MP is available on request. I leave it to the reader to construct an affinity matrix – or what I would call currently describe as a ‘Matrix of Hate’ for each MP pair.