COVID-19 policy in the UK: The role of SAGE and science advice to government

This post is part 2 of COVID-19 policy in the UK: Did the UK Government ‘follow the science’? Reflections on SAGE meetings

The issue of science advice to government, and the role of SAGE in particular, became unusually high profile in the UK, particularly in relation to four factors:

  1. Ministers described ‘following the science’ to project a certain form of authority and control.
  2. The SAGE minutes and papers – including a record of SAGE members and attendees – were initially unpublished, in line with the previous convention of government to publish after, rather than during, a crisis.

‘SAGE is keen to make the modelling and other inputs underpinning its advice available to the public and fellow scientists’ (13.3.20: 1)

When it agrees to publish SAGE papers/ documents, it stresses: ‘It is important to demonstrate the uncertainties scientists have faced, how understanding of Covid-19 has developed over time, and the science behind the advice at each stage’ (16.3.20: 2)

‘SAGE discussed plans to release the academic models underpinning SAGE and SPI-M discussions and judgements. Modellers agreed that code would become public but emphasised that the effort to do this immediately would distract from other analyses. It was agreed that code should become public as soon as practical, and SPI-M would return to SAGE with a proposal on how this would be achieved. ACTION: SPI-M to advise on how to make public the source code for academic models, working with relevant partners’ (18.3.20: 2).

SAGE welcomes releasing names of SAGE participants (if willing) and notes role of Ian Boyd as ‘independent challenge function’ (28.4.20: 1)

SAGE also describes the need for a better system to allow SAGE participants to function effectively and with proper support (given the immense pressure/ strain on their time and mental health) (7.5.20: 1)

  1. There were growing concerns that ministers would blame their advisers for poor choices (compare Freedman and Snowdon) or at least use science advice as ‘an insurance policy’, and
  2. There was some debate about the appropriateness of Dominic Cummings (Prime Minister Boris Johnson’s special adviser) attending some meetings.

Therefore, its official description reflects its initial role plus a degree of clarification on the role of science advice mechanisms during the COVID-19 pandemic. The SAGE webpage on the gov.uk sites describes its role as:

provides scientific and technical advice to support government decision makers during emergencies … SAGE is responsible for ensuring that timely and coordinated scientific advice is made available to decision makers to support UK cross-government decisions in the Cabinet Office Briefing Room (COBR). The advice provided by SAGE does not represent official government policy’.

Its more detailed explainer describes:

‘SAGE’s role is to provide unified scientific advice on all the key issues, based on the body of scientific evidence presented by its expert participants. This includes everything from latest knowledge of the virus to modelling the disease course, understanding the clinical picture, and effects of and compliance with interventions. This advice together with a descriptor of uncertainties is then passed onto government ministers. The advice is used by Ministers to allow them to make decisions and inform the government’s response to the COVID-19 outbreak …

The government, naturally, also considers a range of other evidence including economic, social, and broader environmental factors when making its decisions…

SAGE is comprised of leading lights in their representative fields from across the worlds of academia and practice. They do not operate under government instruction and expert participation changes for each meeting, based on the expertise needed to address the crisis the country is faced with …

SAGE is also attended by official representatives from relevant parts of government. There are roughly 20 such officials involved in each meeting and they do not frequently contribute to discussions, but can play an important role in highlighting considerations such as key questions or concerns for policymakers that science needs to help answer or understanding Civil Service structures. They may also ask for clarification on a scientific point’ (emphasis added by yours truly).

Note that the number of participants can be around 60 people, which is more like an assembly with presentations and a modest amount of discussion, than a decision-making function (the Zoom meeting on 4.6.20 lists 76 participants). Even a Cabinet meeting is about 20 and that is too much for coherent discussion/ action (hence separate, smaller, committees).

Further, each set of now-published minutes contains an ‘addendum’ to clarify its operation. For example, its first minutes in 2020 seek to clarify the role of participants. Note that the participants change somewhat at each meeting (see the full list of members/ attendees), and some names are redacted. Dominic Cummings’ name only appears (I think) on 5.3.20, 14.4.20, and two meetings on 1.5.20 (although, as Freedman notes, ‘his colleague Ben Warner was a more regular presence’).

SAGE minutes 1 addendum 22.1.20

More importantly, the minutes from late February begin to distinguish between three types of potential science advice:

  1. to describe the size of the problem (e.g. surveillance of cases and trends, estimating a reasonable worst case scenario)
  2. to estimate the relative impact of many possible interventions (e.g. restrictions on travel, school closures, self-isolation, household quarantine, and social distancing measures)
  3. to recommend the level and timing of state action to achieve compliance in relation to those interventions.

SAGE focused primarily on roles 1 and 2, arguing against role 3 on the basis that state intervention is a political choice to be taken by ministers. Ministers are responsible for weighing up the potential public health benefits of each measure in relation to their social and economic costs (see also: The relationship between science, science advice, and policy).

Example 1: setting boundaries between advice and strategy

  • ‘It is a political decision to consider whether it is preferable to enact stricter measures at first, lifting them gradually as required, or to start with fewer measures and add further measures if required. Surveillance data streams will allow real-time monitoring of epidemic growth rates and thus allow approximate evaluation of the impact of whatever package of interventions is implemented’ (Meeting paper 26.2.20b: 1)

This example highlights a limitation in performing role 2 to inform 3: SAGE would not be able to compare the relative impact of measures without knowing their level of imposition and its impact on compliance. Further, the way in which it addressed this problem is crucial to our interpretation and evaluation of the timing and substance of the UK government’s response.

In short, it simultaneously assumed away and maintained attention to this problem by stating:

  • ‘The measures outlined below assume high levels of compliance over long periods of time. This may be unachievable in the UK population’ (26.2.20b: 1).
  • ‘advice on interventions should be based on what the NHS needs and what modelling of those interventions suggests, not on the (limited) evidence on whether the public will comply with the interventions in sufficient numbers and over time’ (16.3.20: 1)

The assumption of high compliance reduces the need for SAGE to make distinctions between terms such as mitigation versus suppression (see also: Confusion about the language of intervention and stages of intervention). However, it contributes to confusion within wider debates on UK action (see Theme 1. The language of intervention).

Example 2: setting boundaries between advice and value judgements

  • ‘SAGE has not provided a recommendation of which interventions, or package of interventions, that Government may choose to apply. Any decision must consider the impacts these interventions may have on society, on individuals, the workforce and businesses, and the operation of Government and public services’ (Meeting paper 4.3.20a: 1).

To all intents and purposes, SAGE is noting that governments need to make value-based choices to:

  1. Weigh up the costs and benefits of any action (as described by Layard et al, with reference to wellbeing measures and the assumed price of a life), and
  2. Decide whose wellbeing, and lives, matter the most (because any action or inaction will have unequal consequences across a population).

In other words, policy analysis is one part evidence and one part value judgement. Both elements are contested in different ways, and different questions inform political choices (e.g. whose knowledge counts versus whose wellbeing counts?).

[see also:

  • ‘Determining a tolerable level of risk from imported cases requires consideration of a number of non-science factors and is a policy question’ (28.4.20: 3)
  • ‘SAGE reemphasises that its own focus should always be on providing clear scientific advice to government and the principles behind that advice’ (7.5.20: 1)]

Future reflections

Any future inquiry will be heavily contested, since policy learning and evaluation are political acts (and the best way to gather and use evidence during a pandemic is highly contested).  Still, hopefully, it will promote reflection on how, in practice, governments and advisory bodies negotiate the blurry boundary between scientific advice and political choice when they are so interdependent and rely so heavily on judgement in the face of ambiguity and uncertainty (or ‘radical uncertainty’). I discuss this issue in the next post, which highlights the ways in which UK ministers relied on SAGE (and advisers) to define the policy problem.

The full list of SAGE posts:

COVID-19 policy in the UK: yes, the UK Government did ‘follow the science’

Did the UK Government ‘follow the science’? Reflections on SAGE meetings

The role of SAGE and science advice to government

The overall narrative underpinning SAGE advice and UK government policy

SAGE meetings from January-June 2020

SAGE Theme 1. The language of intervention

SAGE Theme 2. Limited capacity for testing, forecasting, and challenging assumptions

SAGE Theme 3. Communicating to the public

COVID-19 policy in the UK: Table 2: Summary of SAGE minutes, January-June 2020

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COVID-19 policy in the UK: Did the UK Government ‘follow the science’? Reflections on SAGE meetings

SAGE explainer

SAGE is the Scientific Advisory Group for Emergencies. The text up there comes from the UK Government description. SAGE is the main venue to coordinate science advice to the UK government on COVID-19, including from NERVTAG (the New and Emerging Respiratory Virus Threats Advisory Group, reporting to PHE), and the SPI-M (Scientific Pandemic Influenza Group on Modelling) sub-groups on modelling (SPI-M) and behavioural public policy (SPI-B) which supply meeting papers to SAGE.

I have summarized SAGE’s minutes (41 meetings, from 22 January to 11 June) and meeting/ background papers (125 papers, estimated range 1-51 pages, median 4, not-peer-reviewed, often produced a day after a request) in a ridiculously long table. This thing is huge (40 pages and 20000 words). It is the sequoia table. It is the humongous fungus. Even Joey Chestnut could not eat this table in one go. To make your SAGE meal more palatable, here is a series of blog posts that situate these minutes and papers in their wider context. This initial post is unusually long, so I’ve put in a photo to break it up a bit.

Did the UK government ‘follow the science’?

I use the overarching question Did the UK Government ‘follow the science’? initially for the clickbait. I reckon that, like a previous favourite (people have ‘had enough of experts’), ‘following the science’ is a phrase used by commentators more frequently than the original users of the phrase. It is easy to google and find some valuable commentaries with that hook (Devlin & Boseley, Siddique, Ahuja, Stevens, Flinders, Walker, , FT; see also Vallance) but also find ministers using a wider range of messages with more subtle verbs and metaphors:

  • ‘We will take the right steps at the right time, guided by the science’ (Prime Minister Boris Johnson, 3.20)
  • ‘We will be guided by the science’ (Health Secretary Matt Hancock, 2.20)
  • ‘At all stages, we have been guided by the science, and we will do the right thing at the right time’ (Johnson, 3.20)
  • ‘The plan is driven by the science and guided by the expert recommendations of the 4 UK Chief Medical Officers and the Scientific Advisory Group for Emergencies’ (Hancock, 3.20)
  • ‘The plan does not set out what the government will do, it sets out the steps we could take at the right time along the basis of the scientific advice’ (Johnson, 3.20).

Still, clearly they are saying ‘the science’ as a rhetorical device, and it raises many questions or objections, including:

  1. There is no such thing as ‘the science’.

Rather, there are many studies described as scientific (generally with reference to a narrow range of accepted methods), and many people described as scientists (with reference to their qualifications and expertise). The same can be said for the rhetorical phrase ‘the evidence’ and the political slogan ‘evidence based policymaking’ (which often comes with its notionally opposite political slogan ‘policy based evidence’). In both cases, a reference to ‘the science’ or ‘the evidence’ often signals one or both of:

  • a particular, restrictive, way to describe evidence that lives up to a professional quality standard created by some disciplines (e.g. based on a hierarchy of evidence, in which the systematic review of randomized control trials is often at the top)
  • an attempt by policymakers to project their own governing competence, relative certainty, control, and authority, with reference to another source of authority

2. Ministers often mean ‘following our scientists

PM_press_conference Vallance Whitty 12.3.20

When Johnson (12.3.20) describes being ‘guided by the science’, he is accompanied by Professor Patrick Vallance (Government Chief Scientific Adviser) and Professor Chris Whitty (the UK government’s Chief Medical Adviser). Hancock (3.3.20) describes being ‘guided by the expert recommendations of the 4 UK Chief Medical Officers and the Scientific Advisory Group for Emergencies’ (Hancock, 3.3.20).

In other words, following ‘the science’ means ‘following the advice of our scientific advisors’, via mechanisms such as SAGE.

As the SAGE minutes and meeting papers show, government scientists and SAGE participants necessarily tell a partial story about the relevant evidence from a particular perspective (note: this is not a criticism of SAGE; it is a truism). Other interpreters of evidence, and sources of advice, are available.

Therefore, the phrase ‘guided by the science’ is, in practice, a way to:

  • narrow the search for information (and pay selective attention to it)
  • close down, or set the terms of, debate
  • associate policy with particular advisors or advisory bodies, often to give ministerial choices more authority, and often as ‘an insurance policy’ to take the heat off ministers.
  1. What exactly is ‘the science’ guiding?

Let’s make a simple distinction between two types of science-guided action. Scientists provide evidence and advice on:

  1. the scale and urgency of a potential policy problem, such as describing and estimating the incidence and transmission of coronavirus
  2. the likely impact of a range of policy interventions, such as contact tracing, self-isolation, and regulations to oblige social distancing

In both cases, let’s also distinguish between science advice to reduce uncertainty and ambiguity:

  • Uncertainty describes a lack of knowledge or a worrying lack of confidence in one’s knowledge.
  • Ambiguity describes the ability to entertain more than one interpretation of a policy problem.

Put both together to produce a wide range of possibilities for policy ‘guided by the science’, from (a) simply providing facts to help reduce uncertainty on the incidence of coronavirus (minimal), to (b) providing information and advice on how to define and try to solve the policy problem (maximal).

If so, note that being guided by science does not signal more or less policy change. Ministers can use scientific uncertainty to defend limited action, or use evidence selectively to propose rapid change. In either case, it can argue – sincerely – that it is guided by science. Therefore, analyzing critically the phraseology of ministers is only a useful first step. Next, we need to identify the extent to which scientific advisors and advisory bodies, such as SAGE, guided ministers.

The role of SAGE: advice on evidence versus advice on strategy and values

In that context, the next post examines the role of SAGE.

It shows that, although science advice to government is necessarily political, the coronavirus has heightened attention to science and advice, and you can see the (subtle and not subtle) ways in SAGE members and its secretariat are dealing with its unusually high level of politicization. SAGE has responded by clarifying its role, and trying to set boundaries between:

  • Advice versus strategy
  • Advice versus value judgements

These aims are understandable, but difficult to do in theory (the fact/value distinction is impossible) and practice (plus, policymakers may not go along with the distinction anyway). I argue that it also had some unintended consequences, which should prompt some further reflection on facts-versus-values science advice during crises.

The ways in which UK ministers followed SAGE advice

With these caveats in mind, my reading of this material is that UK government policy was largely consistent with SAGE evidence and advice in the following ways:

  1. Defining the policy problem

This post (and a post on oral evidence to the Health and Social Care Committee) identifies the consistency of the overall narrative underpinning SAGE advice and UK government policy. It can be summed up as follows (although the post provides a more expansive discussion):

  1. coronavirus represents a long term problem with no immediate solution (such as a vaccine) and minimal prospect of extinction/ eradication
  2. use policy measures – on isolation and social distancing – to flatten the first peak of infection and avoid overwhelming health service capacity
  3. don’t impose or relax measures too quickly (which will cause a second peak of infection)
  4. reflect on the balance between (a) the positive impact of lockdown (on the incidence and rate of transmission), (b) the negative impact of lockdown (on freedom, physical and mental health, and the immediate economic consequences).

While SAGE minutes suggest a general reluctance to comment too much on the point 4, government discussions were underpinned by 1-3. For me, this context is the most important. It provides a lens through which to understand all of SAGE advice: how it shapes, and is shaped by, UK government policy.

  1. The timing and substance of interventions before lockdown, maintenance of lockdown for several months, and gradual release of lockdown measures

This post presents a long chronological story of SAGE minutes and papers, divided by month (and, in March, by each meeting). Note the unusually high levels of uncertainty from the beginning. The lack of solid evidence, available to SAGE at each stage, can only be appreciated fully if you read the minutes from 1 to 41. Or, you know, take my word for it.

In January, SAGE discusses uncertainty about human-to-human transmission and associates coronavirus strongly with Wuhan in China (albeit while developing initially-good estimates of R, doubling rate, incubation period, window of infectivity, and symptoms). In February, it had more data on transmission but described high uncertainty on what measures might delay or reduce the impact of the epidemic. In March, it focused on preparing for the peak of infection on the assumption that it had time to transition gradually towards a series of isolation and social distancing measures. This approach began to change from mid-March when it became clear that the number of people infected, and the rate of transmission, was much larger and faster than expected.

In other words, the Prime Minister’s declarations – of emergency on 16.3.20 and of lockdown on 23.3.20 – did not lag behind SAGE advice (and it would not be outrageous to argue that it went ahead of it).

It is more difficult to describe the consistency between UK government policy & SAGE advice in relation to the relaxation of lockdown measures.

SAGE’s minutes and meeting papers describe very low certainty about what will happen after the release of lockdown. Their models do not hide this unusually high level of uncertainty, and they use models (built on assumptions) to generate scenarios rather than estimate what will happen. In this sense, ‘following the science’ could relate to (a) a level of buy-in for this kind of approach, and (b) making choices when scientific groups cannot offer much (if any) advice on what to do or what will happen. The example of reopening schools is a key example, since SPI-M and SPI-B focused intensely on the issue, but their conclusions could not underpin a specific UK government choice.

There are two ways to interpret what happened next.

First, there will always be a mild gap between hesitant SAGE advice and ministerial action. SAGE advice tends to be based on the amount and quality of evidence to support a change, which meant it was hesitant to recommend (a) a full lockdown and (b) a release from lockdown. Just as UK government policy seemed to go ahead of the evidence to enter lockdown on the 23rd March, so too does it seem to go ahead of the cautious approach to relaxing it.

Second, UK ministers are currently going too far ahead of the evidence. SPI-M papers state repeatedly that the too-quick release of measures will cause the R to go above 1 (in some papers, it describes reaching 1.7; in some graphs it models up to 3).

  1. The use of behavioural insights to inform and communicate policy

In March, you can find a lot of external debate about the appropriate role for ‘behavioural science’ and ‘behavioural public policy’ (BPP) (in other words, using insights from psychology to inform policy). Part of the initial problem related to the lack of transparency of the UK government, which prompted concerns that ministers were basing choices on limited evidence (see Hahn et al, Devlin, Mills). Oliver also describes initial confusion about the role of BPP when David Halpern became mildly famous for describing the concept of ‘herd immunity’ rather than sticking to psychology.

External concern focused primarily on the argument that the UK government (and many other governments) used the idea of ‘behavioural fatigue’ to justify delayed or gradual lockdown measures. In other words, if you do it too quickly and for too long, people will tire of it and break the rules.

Yet, this argument about fatigue is not a feature of the SAGE minutes and SPI-B papers (indeed, Oliver wonders if the phrase came from Whitty, based on his experience of people tiring of taking medication).

Rather, the papers tend to emphasise:

  • There is high uncertainty about behavioural change in key scenarios, and this reference to uncertainty should inform any choice on what to do next.
  • The need for effective and continuous communication with citizens, emphasizing transparency, honesty, clarity, and respect, to maintain high trust in government and promote a sense of community action (‘we are all in this together’).

John and Stoker argue that ‘much of behavioural science lends itself to’ a ‘top-down approach because its underlying thinking is that people tend to be limited in cognitive terms, and that a paternalistic expert-led government needs to save them from themselves’. Yet, my overall impression of the SPI-B (and related) work is that (a) although SPI-B is often asked to play that role, to address how to maximize adherence to interventions (such as social distancing), (b) its participants try to encourage the more deliberative or collaborative mechanisms favoured by John and Stoker (particularly when describing how to reopen schools and redesign work spaces). If so, my hunch is that they would not be as confident that UK ministers were taking their advice consistently (for example, throughout table 2, have a look at the need to provide a consistent narrative on two different propositions: we are all in this together, but the impact of each action/inaction will be profoundly unequal).

Expanded themes in SAGE minutes

Throughout this period, I think that one – often implicit – theme is that members of SAGE focused quite heavily on what seemed politically feasible to suggest to ministers, and for ministers to suggest to the public (while also describing technical feasibility – i.e. will it work as intended if implemented?). Generally, it seemed to anticipate policymaker concern about, and any unintended public reactions, to a shift towards more social regulation. For example:

‘Interventions should seek to contain, delay and reduce the peak incidence of cases, in that order. Consideration of what is publicly perceived to work is essential in any decisions’ (25.2.20: 1)

Put differently, it seemed to operate within the general confines of what might work in a UK-style liberal democracy characterised by relatively low social regulation. This approach is already a feature of The overall narrative underpinning SAGE advice and UK government policy, and the remaining posts highlight key themes that arise in that context.

They include how to:

Delaying the inevitable

All of these shorter posts delay your reading of a ridiculously long table summarizing each meeting’s discussion and advice/ action points (Table 2, which also includes a way to chase up the referencing in the blog posts: dates alone refer to SAGE minutes; multiple meeting papers are listed as a, b, c if they have the same date stamp rather than same authors).

The full list of SAGE posts:

COVID-19 policy in the UK: yes, the UK Government did ‘follow the science’

Did the UK Government ‘follow the science’? Reflections on SAGE meetings

The role of SAGE and science advice to government

The overall narrative underpinning SAGE advice and UK government policy

SAGE meetings from January-June 2020

SAGE Theme 1. The language of intervention

SAGE Theme 2. Limited capacity for testing, forecasting, and challenging assumptions

SAGE Theme 3. Communicating to the public

COVID-19 policy in the UK: Table 2: Summary of SAGE minutes, January-June 2020

Further reading

It is part of a wider project, in which you can also read about:

  • The early minutes from NERVTAG (the New and Emerging Respiratory Virus Threats Advisory Group)
  • Oral evidence to House of Commons committees, beginning with Health and Social Care

I hope to get through all of this material (and equivalent material in the devolved governments) somehow, but also to find time to live, love, eat, and watch TV, so please bear with me if you want to know what happened but don’t want to do all of the reading to find out.

If you would rather just read all of this discussion in one document:

The whole thing in PDF

Table 2 in PDF

The whole thing as a Word document

Table 2 as a word document

If you would like some other analyses, compare with:

  • Freedman (7.6.20) ‘Where the science went wrong. Sage minutes show that scientific caution, rather than a strategy of “herd immunity”, drove the UK’s slow response to the Covid-19 pandemic’. Concludes that ‘as the epidemic took hold the government was largely following Sage’s advice’, and that the government should have challenged key parts of that advice (to ensure an earlier lockdown).
  • More or Less (1.7.20) ‘Why Did the UK Have Such a Bad Covid-19 Epidemic?’. Relates the delays in ministerial action to inaccurate scientific estimates of the doubling time of infection (discussed further in Theme 2).
  • Both Freedman and More or Less focus on the mishandling of care home safety, exacerbated by transfers from hospital without proper testing.
  • Snowden (28.5.20) ‘The lockdown’s founding myth. We’ve forgotten that the Imperial model didn’t even call for a full lockdown’. Challenges the argument that ministers dragged their feet while scientists were advising quick and extensive interventions (an argument he associates with Calvert et al (23.5.20) ‘22 days of dither and delay on coronavirus that cost thousands of British lives’). Rather, ministers were following SAGE advice, and the lockdown in Italy had a far bigger impact on ministers (since it changed what seemed politically feasible).
  • Greg Clark MP (chair of the House of Commons Science and Technology Committee) Between science and policy – Scrutinising the role of SAGE in providing scientific advice to government

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COVID-19 policy in the UK: yes, the UK Government did ‘follow the science’

In this post, ‘following the science’ describes UK ministers taking the advice of their scientific advisers and SAGE (the Scientific Advisory Group for Emergencies).

If so, were UK ministers ‘guided by the expert recommendations of the 4 UK Chief Medical Officers and the Scientific Advisory Group for Emergencies’?

The short answer is yes.

They followed advice in two profoundly important ways:

  1. Defining coronavirus as a policy problem.

My reading of the SAGE minutes and meeting papers identifies the consistency of the overall narrative underpinning SAGE advice and UK government policy. It can be summed up as follows:

  1. coronavirus represents a long term problem with no immediate solution (such as a vaccine) and minimal prospect of extinction/ eradication
  2. use policy measures – on isolation and social distancing – to flatten the first peak of infection and avoid overwhelming health service capacity
  3. don’t impose or relax measures too quickly (which will cause a second peak of infection)
  4. reflect on the balance between (a) the positive impact of lockdown (on the incidence and rate of transmission), (b) the negative impact of lockdown (on freedom, physical and mental health, and the immediate economic consequences).

If you examine UK ministerial speeches and SAGE minutes, you will find very similar messages: a coronavirus epidemic is inevitable, we need to ease gradually into suppression measures to avoid a second peak of infection as big as the first, and our focus is exhortation and encouragement over imposition.

  1. The timing and substance of interventions before lockdown

I describe a long chronological story of SAGE minutes and papers. Its main theme is unusually high levels of uncertainty from the beginning. The lack of solid evidence, available to SAGE at each stage, should not be dismissed.

In January, SAGE discusses uncertainty about human-to-human transmission and associates coronavirus strongly with Wuhan in China. In February, it had more data on transmission but described high uncertainty on what measures might delay or reduce the impact of the epidemic. In March, it focused on preparing for the peak of infection on the assumption that it had time to transition gradually towards a series of isolation and social distancing measures. This approach began to change from mid-March when it became clear that the number of people infected, and the rate of transmission, was much larger and faster than expected.

Therefore, the Prime Minister’s declarations – of emergency on 16.3.20 and of lockdown on 23.3.20 – did not lag behind SAGE advice. It would not be outrageous to argue that it went ahead of that advice, at least as recorded in SAGE minutes and meeting papers (compare with Freedman, Snowden, More or Less).

The long answer

If you would like the long answer, I can offer you 35280 words, including a 22380-word table summarizing the SAGE minutes and meeting papers (meetings 1-41, 22.1.20-11.6.20).

It includes:

The full list of SAGE posts:

COVID-19 policy in the UK: yes, the UK Government did ‘follow the science’

Did the UK Government ‘follow the science’? Reflections on SAGE meetings

The role of SAGE and science advice to government

The overall narrative underpinning SAGE advice and UK government policy

SAGE meetings from January-June 2020

SAGE Theme 1. The language of intervention

SAGE Theme 2. Limited capacity for testing, forecasting, and challenging assumptions

SAGE Theme 3. Communicating to the public

COVID-19 policy in the UK: Table 2: Summary of SAGE minutes, January-June 2020

Further reading

So far, the wider project includes:

  • The early minutes from NERVTAG (the New and Emerging Respiratory Virus Threats Advisory Group)
  • Oral evidence to House of Commons committees, beginning with Health and Social Care

I am also writing a paper based on this post, but don’t hold your breath.

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Policy Concepts in 1000 Words: Policy Change

Christopher M. Weible & Paul Cairney

Policy change is a central concern of policy research and practice. Some want to explain it. Some want to achieve it.

Explanation begins with the ‘what is policy?’ question, since we cannot observe something without defining it.  However, we soon find that: no single definition can capture all forms of policy change, the absence of policy change is often more important, and important changes can be found in the everyday application of rules and practices related to public policies.  Further, studies often focus on changes in public policies without a focus on societal outcomes or effects.

One pragmatic solution is to define public policies as decisions made by policymakers or policymaking venues such as legislatures, executives, regulatory agencies, courts, national and local governments (and, in some countries, citizen-led policy changes).  Focusing on this type of policy change, two major categories of insights unfold:

  1. Patterns of Policy Change: incrementalism, punctuations, and drift

A focus on decisions suggests that most policymaking venues contribute primarily to incremental policy change, or often show little change from year to year but with the occasional punctuation of major policymaking activity.  This pattern reflects a frequent story about governments doing too much or nothing at all. The logic is that policymaking attention is always limited, so a focus on one issue in any policymaking venue requires minimal focus on others.  Then, when attention shifts, we see instances of major policy change as attempts to compensate (or overcompensate) for what was ignored for too long.

An additional focus on institutions highlights factors such as policy drift, to describe slow and small changes to policies, or to aspects of their design, that accumulate eventually and can have huge impacts on outcomes and society.  These drifts often happen outside the public eye or are overlooked as being negative but trivial.  For example, rising economic inequality in the US resulted from the slow accumulation of policies – related to labor unions, tax structures, and corporate governance – as well as globalization and labor-saving technologies.

  1. Factors Associated with Policy Change

Many factors help us understand instances of policy change. We can separate them analytically (as below) but, in practice, they occur simultaneously or sequentially, and can reinforce or stifle each other.

Context

Context includes history, biophysical conditions, socio-economic conditions, culture, and basic institutional structures (such as a constitution).  For example, historical and geographic conditions are often viewed as funneling or constraining the type of policy decisions made by a government.

Events 

Policymaking venues are often described as being resistant to change or in a state of equilibrium of competing political forces.  As a result, one common explanation for change is a focusing event or shock.  Events by themselves don’t create policy change. Rather, they present an opportunity for people or coalitions to exploit.   Focusing events might include disasters or crises, tragic incidents, a terrorist attack, disruptive changes in technology, or more routine events such as elections. Events may have tangible qualities, but studies tend to highlight the ways in which people frame events to construct their meaning and implications for policy.

Public Opinion 

The relationship between public opinion and policy change is a difficult one to assess.  Some research shows that the preferences of the general public only matter when they coincide with the preferences of the elite or major interest groups.  Or, it matters only when the topic is salient and the public is paying attention. Little evidence suggests that public opinion matters when few are paying attention.  Others describe public opinion as setting the boundaries within which the government operates.

Learning

Learning is a process of updating understandings of the world in response to signals from the environment.  Learning is a political activity rather than simply a technical exercise in which people learn from teachers. Learning could involve becoming aware of the severity of a policy problem, evaluating outcomes to determine if a government intervention works, and learning to trust an opponent and reach compromise. For example, certain types of rules in a collaborative process can shape the ways in which individuals gain new knowledge and change their views about the scientific evidence informing a problem.

Diffusion of Ideas 

Sometimes governments learn from or transfer policies from other governments. For example, in collections of policymaking venues (such as US state governments or EU member states) it is common for one venue to adopt a policy and prompt this policy to spread across other venues in a process of diffusion.  There are many explanations for diffusion including learning, a response to competition, mimicking, and coercion. In each case, the explanation for policy change comes from an external impetus and an internal context.

Champions and Political Associations

All policy change is driven, to some extent, by individual or group agency.  Key players include public policy champions in the form of policy entrepreneurs or in groups of government and/or non-government entities in the form of coalitions, social movements, epistemic communities, and political parties.  In each case, individuals or organizations mobilize resources, capitalize on opportunities, and apply pressure to formulate and adopt public policies.

 

The presence of these factors does not always lead to policy change, and no single study can capture a full explanation of policy change. Instead, many quantitative studies focus on multiple instances of policy change and are often broad in geographic scope or spans of time, while many case study or qualitative studies focus intensely on a very particular instance of policy change. Both approaches are essential.

See also:

Policy in 500 Words: what is public policy and why does it matter?

Policy in 500 Words: how much does policy change?

Policy Concepts in 1000 Words: Policy change and measurement (podcast download)

Policy Concepts in 1000 Words: how do policy theories describe policy change?

 

 

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8. Race, ethnicity, and the social determinants of health

The beginning of this section comes from: Coronavirus and the ‘social determinants’ of health inequalities: lessons from ‘Health in All Policies’ initiatives

A ‘social determinants’ focus shows that the most profound impacts on population health can come from (a) environments largely outside of an individual’s control (e.g. in relation to threats from others, such as pollution or violence), (b) access to high quality education and employment, and (c) economic inequality, influencing access to warm and safe housing, high quality water and nutrition, choices on transport, and access to safe and healthy environments.

In that context, the coronavirus also provides stark examples of major inequalities in relation to self-isolation and social distancing: some people have access to food, private spaces to self-isolate, and open places to exercise away from others; many people have insufficient access to food, no private space, and few places to go outside.

Corburn et al’s (2014) study of Richmond, California’s, focusing on ‘coproducing health equity in all policies’ highlights the strong connection between health and income and wealth, which differs markedly according to race and immigration status. It reports on a series of community discussions to identify key obstacles to health:

emerging from the workshops and health equity discussions was that one of the underlying causes of the multiple stressors experienced in Richmond was structural racism. By structural racism we meant that seemingly neutral policies and practices can function in racist ways by disempowering communities of color and perpetuating unequal historic conditions” (2014: 627-8).

In the UK, there has been some political attention devoted on the impact of coronavirus according to race and ethnicity, albeit generally described with the problematic catch-all term BAME (Black, Asian, and minority ethnic) to refer to all non-white populations.

Most notably, the PHE report Disparities in the risk and outcomes of COVID-19 highlights the unequal impact of coronavirus, with an action plan delayed, but expected to follow.

PHE ethnicity 2020

This inequality is discussed somewhat in committee proceedings, including in relation to:

  • Walton (1.5.20: q3) on concerns for BAME pregnant women and NHS staff
  • Owen (5.5.20: q424) on the social determinants of health inequalities
  • Owen (14.5.20: q95, q100) on the poor fit of PPE for women and BAME women
  • Owatemi (14.5.20: q99):

‘In a survey of over 2,000 BAME NHS staff, 50% stated that there was a culture of discrimination within the NHS. They felt that they were unable to speak up due to the lack of BAME representation in leadership roles. Currently, only 6% of NHS leadership positions are BAME staff’

COVID-19 policy in the UK: oral evidence to the Health and Social Care Committee (5th March- 3rd June 2020)

  1. The need to ramp up testing (for many purposes)
  2. The inadequate supply of personal protective equipment (PPE)
  3. Defining the policy problem: ‘herd immunity’, long term management, and the containability of COVID-19
  4. Uncertainty and hesitancy during initial UK coronavirus responses
  5. Confusion about the language of intervention and stages of intervention
  6. The relationship between science, science advice, and policy
  7. Lower profile changes to policy and practice
  8. Race, ethnicity, and the social determinants of health

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7. Lower profile changes to policy and practice

A future series of posts will describe the many ways in which policy will (or should) change in practice, as public sector and other organizations change the way they do things in response to crisis. Current examples include the relaxation or postponement of high-political-stakes issues such as NHS targets and testing in schools, and as-important but lower stakes issues such as mental health self-management and the local authority obligation to provide social care.

In relation to oral evidence, examples include:

  • Stevens (17.3.20: q150-3) discusses relaxations on rules for GP prescribing, paying GPs upfront in relation to contracts, reducing the regularity of Care Quality Commission checks, and taking a more flexible approach to A&E and other targets to avoid their inevitable unintended consequences. The changes take place in the context of a reduced-capacity NHS and growing waiting list for services not met during the lockdown (see Hopson, Dixon (Chief Executive The Health Foundation), and Edwards (Chief Executive The Nuffield Trust) 14.5.20: q75-84).
  • Taiwo Owatemi MP (17.4.20: q371) on medicinal cannabis for children.
  • Hancock (17.4.20: q373) on the availability and operation of cancer services (compare with Rosie Cooper MP, 17.4.20: q380; Palmer, National Cancer Director NHS England, 1.5.20: q21-35; Murray, Chief Executive The King’s Fund, 14.5.20: q73)
  • Dean Russell MP (17.4.20: q386):

‘Last November, the Committee [Joint Committee on Human Rights] identified that human rights were being abused for people with learning disabilities and/or autism in mental health hospitals. As part of that, one of the concerns is that with coronavirus, family visits are currently being restricted and routine inspections have been suspended, which in turn potentially increases the young people’s isolation and also makes them more vulnerable to abuse of their rights.’

  • Walton (Chief Executive, Royal College of Midwives) (1.5.20: q11) on ‘domestic abuse increases during pregnancy’ and ‘it appears that during lockdown domestic abuse and control issues have increased’.
  • Murdoch (National Mental Health Director, NHS England) (1.5.20: q47-51) on the temporary reduction in referrals to child and adult mental health services, followed by a general consensus (MPs and witnesses, 14.5.20: q87-90) that adult and child mental health services were poorly funded anyway, with too few staff, dealing mostly with emergencies, so the post-pandemic provision is a major worry since there will be the latent demand plus new causes of mental health problems.

COVID-19 policy in the UK: oral evidence to the Health and Social Care Committee (5th March- 3rd June 2020)

  1. The need to ramp up testing (for many purposes)
  2. The inadequate supply of personal protective equipment (PPE)
  3. Defining the policy problem: ‘herd immunity’, long term management, and the containability of COVID-19
  4. Uncertainty and hesitancy during initial UK coronavirus responses
  5. Confusion about the language of intervention and stages of intervention
  6. The relationship between science, science advice, and policy
  7. Lower profile changes to policy and practice
  8. Race, ethnicity, and the social determinants of health

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6. The relationship between science, science advice, and policy

There is a lot written in general about the extent to which UK policy is evidence-based (go to EBPM and this article and I’ll see you in a few days).

This issue was initially a big feature of the UK government rhetoric in March, in which the idea of ministers ‘following the science’ (or the advice of advisers and bodies such as Royal Colleges – Hancock, 17.4.20: q312) can be used to project a certain form of authority and control (see Weible et al).

It prompted regular debate on the extent to which scientific advisory bodies were subject to group-think and drawn from too-narrow pools of expertise (see for example Dingwall, Today programme 10.6.20, from 838am), and Vallance’s (17.3.20: q96) response:

‘If you thought SAGE and the way SAGE works was a cosy consensus of agreeing scientists, you would be very mistaken. It is a lively, robust discussion, with multiple inputs. We do not try to get everybody saying exactly the same thing. The idea is to look at the evidence and come up with the answers as best we can. There are sub-groups that work and feed into SAGE. The membership of SAGE changes, depending on what we are discussing. It is not as though it is the same group of people who always discuss all the topics; there are members who come for specific items’.

Then, when things began to go very wrong, commentators speculated about the extent to which ministers would blame their advisers for their policy and its timing. The latter problem became a regular feature in oral evidence. For example:

  • Vallance (5.5.20: 392-6) states that (a) ‘SAGE does not make decisions. SAGE gives advice; it is an advisory body and Ministers of course have to make decisions’, and (b) they need some confidentiality to make sure that ministers get the information to make choices first (‘to be allowed time to make those decisions’).
  • Vallance (5.5.20: q406) is heavy on the line that scientists only give advice, not make policy: ‘we give science advice and then Ministers have to make their decisions. All I can say is that the advice that we have given has been heard and has been taken by the Government. Clearly, what we do not give advice on is absolutely precise policy decisions or absolute timings on things. Those are decisions that Ministers must take on the basis of the science. The correct way of saying it is that the decisions are informed by science. They are not led by science, as you said in opening the question’.
  • Vallance (5.5.20: Q407) describes how that advice may be presented when the scientists do not agree: ‘… our output is very much in the form of options, in the form of uncertainty and in the form of what could be done and what the potential consequences might be, not, “Here is the answer. Get on and do this.” That is not how it works.’

The UK’s nascent blame-game problem makes Costello’s (17.4.20: q298) suggestion of ‘a no-blame audit’ (‘where were the system errors that led us to have probably the highest death rates in Europe?’), to inform planning for the second wave, seem unrealistic. Open debates may be common in some scientific conferences (albeit not the ones I attend), but such learning is competitive and contested in adversarial political systems (see Dunlop, and Dunlop & Radaelli). I think this limitation helps explain Vallance’s (5.5.20: q390) reluctance to reflect openly on what he would do differently if he had better data on the doubling time of the virus in March (see also Harries, 5.5.20: q414-7 on excess deaths).

COVID-19 policy in the UK: oral evidence to the Health and Social Care Committee (5th March- 3rd June 2020)

  1. The need to ramp up testing (for many purposes)
  2. The inadequate supply of personal protective equipment (PPE)
  3. Defining the policy problem: ‘herd immunity’, long term management, and the containability of COVID-19
  4. Uncertainty and hesitancy during initial UK coronavirus responses
  5. Confusion about the language of intervention and stages of intervention
  6. The relationship between science, science advice, and policy
  7. Lower profile changes to policy and practice
  8. Race, ethnicity, and the social determinants of health

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5. Confusion about the language of intervention and stages of intervention

The Health and Social Care Committee sessions highlight two types of confusion about how best to describe stages of government policy. In particular, the difference between mitigate/suppress represents either a profound change in UK government policy or trivial semantics.

The distinction between contain and delay measures.

The Committee probes the idea of a shift in early March from contain to delay, which taps into wider debates in which critics suggest that the UK gave up on containment too soon (discussed in post 1 in relation to testing). In two sessions, Whitty (5.3.20: q2-4 and q55; 16.3.20) emphasizes that the measures to contain and delay are very similar, so the distinction is misleading:

‘At this point in the early stage of delay, the actions are primarily ones of case finding and isolating cases that come from high-risk areas, which is to try to reduce the possibility of seeding into the community and therefore slow down the initiation of an epidemic, then try to pick up cases early and isolate them in hospital environments so we minimise the chance of transmission within hospitals’ (5.3.20: q55).

Vallance (5.5.20: q41) states that the initial plan was to isolate and track to contain the virus. Then, the UK had a ‘massive influx of cases, not from China but from all sorts of other places, partly because of the huge connectivity of the UK … once it went beyond that to being a pandemic you didn’t know where it was going to come from, and we got a very large number of cases coming in right the way across the country from multiple European sources somewhere around late February and detected in early March’.

The distinction between mitigation and suppression measures

It is common for UK media and social media discussions to highlight a U-turn from mitigation to suppression measures in mid-March, summed up to some extent by the Prime Minister’s exhortation to stay home (16.3.20) and then obligation to stay home (23.3.20).

During this time, the Imperial College COVID-19 Response Team report dated 16.3.20 described (a) ‘mitigation’ measures as likely to reduce UK deaths only from 500000 to 250000, and therefore not viable, prompting (b) the need for ‘suppression’ measures to reduce deaths to 5,600-48,000 over two years.

In contrast, Vallance (17.3.20: q67) describes the distinction as mere semantics:

‘It is a semantic difference, whether you call it suppression, delay or mitigation. The aim is exactly the same, which is, how do you keep this thing down, how do you keep it below the level at which you want to keep it, and how do you keep it down for long enough to ensure that you have managed to achieve suppression?’

Vallance suggests that the UK took suppression measures from 16.3.20 without using the word suppress (17.3.20: q84; see also 5.5.20: q432 ‘we are definitely in “mitigate” now’, which suggests that he says ‘mitigation’ when most might say ‘suppression’). Similarly, Hunt (17.3.20: q69) describes ‘the very dramatic social distancing measures that have now been announced’. Whitty is also keen in the 5.3.20 sessions to downplay the idea that there are distinct categories of action associated with different terms.

For me, these discussions highlight two main issues.

First, initial UK government policy was often confusing because its communication was poor. In this case, it seems that the meaning of each term was not agreed from the outset, contributing to some confusion among adviser, advisee, and commentator.

Second, and more importantly, they betray a lack of appreciation of the difference between measures in relation to their likely levels of implementation. Most notably, several discussions (17.3.20: q84-5) equate UK policy from 16.3.20 as the kinds of suppression measures associated with China or South Korea, despite a huge gulf in their level of enforcement (see also Harries, 5.5.20: q440: ‘People seem to think there was a lockdown moment, whereas in fact a series of interventions based on science were recommended’). In contrast, Costello (17.4.20: q298) favours a more compulsory form of isolation associated with ‘a lot of the Asian states’: ‘Just asking people to self-isolate will not achieve the quarantine that you want’.

COVID-19 policy in the UK: oral evidence to the Health and Social Care Committee (5th March- 3rd June 2020)

  1. The need to ramp up testing (for many purposes)
  2. The inadequate supply of personal protective equipment (PPE)
  3. Defining the policy problem: ‘herd immunity’, long term management, and the containability of COVID-19
  4. Uncertainty and hesitancy during initial UK coronavirus responses
  5. Confusion about the language of intervention and stages of intervention
  6. The relationship between science, science advice, and policy
  7. Lower profile changes to policy and practice
  8. Race, ethnicity, and the social determinants of health

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4. Uncertainty and hesitancy during initial UK coronavirus responses

Vallance (17.3.20: q114) ‘I do not think any of us have seen anything like this. It is a first in not just a generation but potentially the first for 100 years. None of us has seen this. … This is a daily changing and unique situation where we are learning as we go along’.

Early UK discussions are characterized by the expression of uncertainty about what was happening (based on limited data and the questionable accuracy of the most-used model), and hesitancy about how quickly and substantively to respond. This combination of uncertainty and hesitancy informs continuous discussions about why the UK appeared to pursue a lockdown too late, contributing to an unusually high number of excess deaths.

However, it is worth keeping them separate – analytically – to compare uncertainty about (a) what is happening, and (b) what ministers and the public are willing to do about it (as described in the previous post, in relation to problem definition), which inform hesitancy in different ways. Either way, the wider context is that the UK government eventually introduced measures on social regulation that would have seemed unthinkable in the UK before 2020.

The NERVTAG notes show how much uncertainty there was in January 2020, with initial assessments of low risk before the virus spread to other countries and then the UK. Even by the early stages, and still in March, there was some hesitancy about recommending quarantine-style measures, and a tendency to focus on low impact or low social compliance as a way to reject new measures.

  • Compare with Freedman 7.6.20 (‘Where the science went wrong. Sage minutes show that scientific caution, rather than a strategy of “herd immunity”, drove the UK’s slow response to the Covid-19 pandemic).

The oral evidence to the Health and Social Care committee

In the first oral evidence session in March, Whitty (5.3.20: q1) was still describing the virus in relation to China and only providing an initial mild warning that the chances of containment in China (followed by minimal global spread) are ‘slim to zero’ since it is ‘highly likely that there is some level of community transmission of this virus in the UK now’.

Similarly, Willett (Director for Acute Care, NHS England) (17.3.20: q175) described the sense that there was no perceived emergency (in WHO and UK statements) by the end of January, followed by the sense that information, advice, and policy was changing ‘literally every few days’.

The initial oral evidence shows that the science advice was primarily about how to inform and persuade people to change their behavior, focusing heavily on regular handwashing, followed by exhortations to self-isolate at home if feeling symptoms.

Whitty (5.3.20: 2-4) describes delaying the peak of the epidemic via ‘changes to society’ to (a) avoid it coinciding with ‘winter pressures on the NHS’ and boost the capacity to respond, (b) understand the virus better, and (c) hope that it ‘if you move into spring and summer, the natural rate of transmission may go down’ (as with respiratory viruses ‘like flu, colds and coughs’, in which people are less often in small enclosed spaces).

These early discussions emphasise the need for parliamentary and public discussion on more impositional measures, but with no strong push for anything like a lockdown (and, for example, some concern about the measures in South Korea not being acceptable in the UK – Whitty, 5.3.20: q5).

Even on 17.3.20, Vallance (q72) was describing waiting 2-3 weeks to find out the effect of the Prime Minister’s 16.3.20 message, hoping that it could keep the number of ‘excess deaths’ down to 20000 (and Vallance and Whitty had been describing pre-lockdown measures as quite extreme). The same day, Stevens (and Powis, National Medical Director, NHS England) described the PM’s hope that people would act according to the ‘good judgment and altruistic instincts of the British people’ without the need to impose social distancing (17.3.20: q176).

COVID-19 policy in the UK: oral evidence to the Health and Social Care Committee (5th March- 3rd June 2020)

  1. The need to ramp up testing (for many purposes)
  2. The inadequate supply of personal protective equipment (PPE)
  3. Defining the policy problem: ‘herd immunity’, long term management, and the containability of COVID-19
  4. Uncertainty and hesitancy during initial UK coronavirus responses
  5. Confusion about the language of intervention and stages of intervention
  6. The relationship between science, science advice, and policy
  7. Lower profile changes to policy and practice
  8. Race, ethnicity, and the social determinants of health

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3. Defining the policy problem: ‘herd immunity’, long term management, and the containability of COVID-19

Note: it is worth reading this post together with COVID-19 policy in the UK: The overall narrative underpinning SAGE advice and UK government policy since both examine how the UK government defined the policy problem.

Frankly, the widespread and intense focus on the misleading phrase ‘herd immunity’ was a needless distraction, sparked initially by government advisors but then nitrous-turbo-boosted, gold-plated, and covered in neon lights during a series of ridiculous media and social media representations of ill-worded statements.

This initial focus took attention away from a much more profound discussion of what the UK government thinks is feasible, which informs a very stark choice: to define the COVID-19 problem as (a) a short term pandemic to be eradicated (as in countries like South Korea) or (b) a long term pandemic to be expected and managed every year (the definition in countries like the UK).

There is no ‘herd immunity strategy’

The key thing to note is that ministers and their advisors:

  • Did talk in general terms about the idea of ‘herd immunity’ in March (best summed up as: herd immunity is only possible if there is a vaccine or enough people are infected and recover)
  • Did not recommend an extreme non-intervention policy in which most of the population would be infected quickly to achieve herd immunity (in February, advisers described this outcome as the Reasonable Worst Case Scenario; see also Whitty, 5.3.20: q15-17)

Rather, describing the idea of herd immunity as an inevitability (not determined by choice) is key to understanding the UK approach. It helps us question the idea that there was a big policy U-turn in mid-March. Policy did change in the short term, but a sole focus on the short term distracts from the profound implications of its long-term strategy (in the absence of a vaccine) associated with phrases such as ‘flatten the curve’ (rather than ‘eradicate the virus’).

Examples of UK government representatives talking about herd immunity

1.      Wilful misrepresentation, often put to music

Full Fact’s challenge to the wilful misrepresentation of Prime Minister Boris Johnson’s appearance on the ITV programme This Morning (10.3.20): Here is the transcript of what Boris Johnson said on This Morning about the new coronavirus

These video stinkers, in which people (a) cut quotes so that you don’t hear the context, and provide a misleading headline, or (b) put a bunch of cut interviews in sequence and combine them with a tune that sounds like a knock-off version of the end credits to the TV Series The Hulk (in other words, people design these messages to get an emotional reaction).

2.      Headlines stoking the idea of herd immunity during a time when everyone should have been careful about how explain and interpret early discussions

British government wants UK to acquire coronavirus ‘herd immunity’, writes Robert Peston (12.3.20)

3.      The accentuation of a message not being emphasised by government spokespeople, at the expense of a message that requires more attention.

This interview is described by Sky News (13.3.20) as: ‘The government’s chief scientific adviser Sir Patrick Vallance has told Sky News that about 60% of people will need to become infected with coronavirus in order for the UK to enjoy “herd immunity”’. You might be forgiven for thinking that he was on Sky extolling the virtues of a strategy to that end. This was certainly the write-up in respected papers like the FT (UK’s chief scientific adviser defends ‘herd immunity’ strategy for coronavirus). Yet, he was saying nothing of the sort. Rather, when prompted, he discussed herd immunity in relation to the belief that COVID-19 will endure long enough to become as common as seasonal flu.

See Vallance’s interview on the same day (13.3.20) during Radio 4’s Today programme (transcribed by the Spectator and headlined as “How ‘herd immunity’ can help fight coronavirus” as if it is his main message). The Today Programme also tweeted only 30 seconds to single out that brief exchange. Yet, clearly his overall message – in this and other interviews – was that some interventions (e.g. staying at home; self-isolating with symptoms) would have bigger effects than others (e.g. school closures; prohibiting mass gatherings) during the ‘flattening of the peak’ strategy (‘What we don’t want is everybody to end up getting it in a short period of time so that we swamp and overwhelm NHS services’). Rather than describing ‘herd immunity’ as a strategy, he is really describing how to deal with its inevitability.

[PAC: Note that these examples are increasingly difficult to track, because people take the herd immunity argument for granted or cite reference to it misleadingly. For example, Scalley et al state “To widespread criticism, he floated an approach to “build up some degree of herd immunity” founded on an erroneous view that the vast majority of cases would be mild, like influenza”. Their citation takes you here, in which there is no reference to herd immunity or the quotation]

In oral evidence, Vallance (17.3.20: q70) compares these measures as follows (while describing the ‘confidence intervals’ as ‘quite wide’, q77):

‘The interventions we have made have all been modelled out – it is just modelling; we need to be aware of that – to say what effect they would have on the peak. In the first one we introduced, case isolation, you would expect to bring the peak down by about 20%. In the second one, whole household quarantine, you would expect to bring it down by about 25%. The social shielding of the elderly has less of an effect on the peak but a much bigger effect on the mortality, where you might expect it to be between 20% and 30%. General social distancing measures—as you said, quite extreme ones have now been introduced—would be expected to reduce the peak by about 50%. They are not necessarily all completely additive, but it tells you that together we should expect those to have a very significant effect on the peak, and we should start to see the rates come down in two or three weeks’ time. The ambition in any outbreak is to try to get the R0 value down below one. That is the value, on average, of what one person would do in infecting others. At the moment, the R0 value is somewhere between two and three, and the aim is to get it below one, at which time things start to decrease’

Further discussion of herd immunity in oral evidence

Throughout the evidence sessions, some MPs raise the herd immunity idea, but not energetically, and perhaps largely to allow government advisers to clarify their initial statements (e.g. 17.3.20: q112; 17.4.20: q303).

In May, Vallance (5.5.20: q389 and q404) makes it extra-clear that he was not advocating the ‘herd immunity’ idea associated with no intervention:

‘Q389 Chair: It sounds like there is still a degree of uncertainty as to whether an antibody leads to an immune response. Back on 13 March, you said the aim was to build up some kind of herd immunity where lots of people in the country had had the virus so that they could not catch it again. When you said that, which was nearly two months ago, what was your evidence then for the existence of that kind of immunity?

Sir Patrick Vallance: I should be clear about what I was trying to say, and, if I did not say it clearly enough, I apologise. What I was trying to say was that, in the absence of a therapeutic, the way in which you can stop a community becoming susceptible to this is through immunity. Immunity can be obtained either by vaccination or by people who have had the infection. We don’t know, as I said, exactly what degree of protection you get from natural infection, and we don’t yet have a vaccine. The second thing is that the higher the proportion of people in the community with immunity, the easier it is to control the disease and, ultimately, the easier it is to release measures. So vaccination becomes an important part of how you end up with protection, assuming you can get a decent immune response with vaccines, which we also do not know yet, but you would expect there to be some degree of immunity. The expectation is that antibody responses will correlate with immunity to some degree—maybe very high or maybe not so high. As to the degree of protection, whether it is to reduce the severity of the disease or to reduce the overall effect of the disease and the ability to catch the disease, we still have some work to do to find out about that.

Q404 ‘To reiterate, as I said at the beginning to Jeremy Hunt, my points about immunity were not actually about getting immunity through that route. My point has been clear from the outset that we need to suppress the peak, and keep the peak down flat below the level at which the NHS can cope, to protect the NHS and to make sure that we reduce deaths. That has been the strategy.’

See also:

Government emails on herd immunity

[Update 15.10.20] The BBC used a Freedom of Information request to secure ‘every email sent by Sir Patrick [Vallance] and chief medical officer for England, Professor Chris Whitty, from the start of February to the start of June, containing the words “herd immunity”‘.

The BBC narrative is that some people think that the government was in favour of pursuing ‘herd immunity’ via high infection rates in the population (60%) that would contribute to hundreds of thousands of deaths.

For me, this is a misleading story.

The emails largely show that these advisors regret ever using the term ‘herd immunity’ because it allows people to jump to wild conclusions based on patching together minimal evidence (and ignoring more convincing evidence that advisors pushed strongly for suppression measures).

Lebowski new shit information

Dominic Cummings: herd immunity was the plan

(update 24.5.21) On the 22nd May 2021, Dominic Cummings (Prime Minister Boris Johnson’s former Special Advisor) tweeted to confirm that ‘herd immunity’ was government policy before a major policy shift in early March 2020:

dominic cummings tweet 38 herd immunity

As such, I think we are now at the stage of insiders arguing with insiders about (a) what happened, and (b) what ‘herd immunity’ means. It has prompted people to argue that their initial suspicions or reporting has been vindicated (e.g. Robert Peston). It has also prompted rejections of Cummings’ narrative by insiders such as Dr Jenny Harries. At the heart of this discussion is a combination of intentional and unintentional confusion about what ‘herd immunity’ means in relation to policy. For the most energetic government critics, it means an extreme hands-off measure to allow the epidemic to sweep through a population as quickly as possible. For me, it was a phrase used far too loosely to describe aspects of the mitigation strategy in place before lockdown (e.g. cocooning the most vulnerable during a wave of infection). For the government itself, it forms part of the emerging definition described below.

[See also: Who can you trust during the coronavirus crisis? ]

[Update 16.6.21 Cummings also released a lot of information on his substack (7000 words) in relation to his oral evidence (7 hours) to the House of Commons Science and Technology/ Health and Social Care committees]

Defining the COVID-19 problem in the UK

Greater clarity on key terms is essential. It allows us to think more about the implications of the UK government’s problem definition. In a much larger paper (that’s right – its completion is on the to-do list), I suggest that these elements inform the UK government’s definition of the policy problem by mid-March 2020:

  1. We are responding to an epidemic that cannot be eradicated. Herd immunity is only possible if there is a vaccine or enough people are infected and recover.
  2. We need to use a suppression strategy to reduce infection enough to avoid overwhelming health service capacity, and shield the people most vulnerable to major illness or death caused by COVID-19, to minimize deaths during at least one peak of infection.
  3. We need to maintain suppression for a period of time that is difficult to predict, subject to compliance levels that are difficult to predict and monitor.
  4. We need to avoid panicking the public in the lead up to suppression, avoid too-draconian enforcement, and maintain wide public trust in the government.
  5. We need to avoid (a) excessive and (b) insufficient suppression measures, either of which could contribute to a second wave of the epidemic of the same magnitude as the first.
  6. We need to transition safely from suppression measures to foster economic activity, find safe ways for people to return to work and education, and reinstate the full use of NHS capacity for non-COVID-19 illness. In the absence of a vaccine, this strategy will likely involve social distancing and (voluntary) track-and-trace measures to isolate people with COVID-19.
  7. Any action or inaction has a profoundly unequal impact on social groups.

In other words, UK government policy is about reducing or moving the initial peak of infection, followed by longer term management to ensure that the NHS always has capacity to treat. The short-term focus emphasized the need to get the timing right in relation to the balance between public health benefits and social and economic cost (rather than to adopt a precautionary principle):

‘There is also timing. There will be quite a long period between knowing that we have an epidemic running at a reasonable rate and the actual peak. We are keen not to intervene until the point when we absolutely have to, so as to minimise the economic and social disruption on people, and then to stop it again as soon as we can afterwards. It is both the combination of what we need to do—in later questions we might want to go into some details about the things we can do—and the timing. The timing is critical. It is important that we minimise the social disruption while doing what we can to make sure we maximise the public health impact’ (Whitty, 5.3.20: q18)

[See also q39 on the unresolved difficulties of isolating vulnerable people physically without producing too high costs socially, and

q59 on ‘no need at this stage to be stocking up on anything. … this is going to be a marathon not a sprint. This is going to be a long period. There is going to be a lead time before the serious take-off of this comes, which we will be able to indicate … There is nothing in the current environment that would rationally lead someone to want to go out and stock up on stuff’.]

It is difficult to tell exactly what ministers and advisors expect to happen long-term in the absence of a vaccine (although Vallance 17.3.20: q102 is clear that the initial suppression measures will take an indeterminate number of months, not a few weeks). For example, are they managing infections and expecting regular deaths (assuming a mortality rate at approximately 1%) or expecting a high NHS capacity to reduce that mortality rate? Most discussions in public refer generally to the peak and NHS capacity but not the specifics:

‘Overall, the goal is clearly to bend the curve down and to make sure that the NHS capacity is there, and at the same time to do the work to try to improve our ability as a society to cope with this disease, with the goal of lifting some of the incredibly restrictive methods that we have had to place on the population in order to get the disease under control’ (Hancock, 17.4.20: q306)

The long-term implications of ‘flatten the curve’

In that context, Costello (17.4.20: q303) sums up my niggling concerns about the ‘flatten the curve’ message. This phrase suggests that we

  • keep transmission low enough to make sure that the number of relevant cases does not overwhelm the NHS (an approach with high support), and
  • accept that transmission will remain at a lower but significant rate until a vaccine is found (an approach that is not discussed as much, but it implies the continuation of deaths at a lower but regular rate):

‘The recent estimates, even from the chief scientific officer, are that after this wave, where we could see 40,000 deaths by the time it is over, we could have maybe only 10% to 15% of the population infected or covered, so the idea of herd immunity would mean maybe another five or six more waves to get to 60%. I do not think we should be using phrases such as “flatten the curve” because it implies continuing. We have to suppress this right down.’ (Costello, 17.4.20: q303)

The other side of this coin is that government advisers were initially working on the assumption that they could keep the initial number of deaths to 20000, which suggests a population infection rate well below 10% of the population (2/60m people, assuming the 1% mortality rate described by Whitty, 5.3.20: q11) and no expectation of herd immunity in the short term.

Comparing the UK definition with approaches in South Korea and China

The oral evidence sessions, probing the UK government’s longer term vision, help make key aspects of this definition somewhat clearer in two main ways.

First, they help confirm that UK policy is built on the assumption that COVID-19 will be a regular or seasonal problem (in the absence of a vaccine and culture change). For example, Hunt (17.3.20: q105) suggests that some country leaders think there will be (a) a peak of infection, then (b) containment, followed by (c) fizzling out:

‘China has officially announced that it thinks it is past the peak. The South Korean Foreign Minister was on TV at the weekend saying that she thinks South Korea has passed the peak, and it seems to think it has passed the peak with less than 1% of the population being infected. It is very realistic that there could be second or third waves, but it does not seem to be expecting it as much as you do … The Chinese and Korean view seems to be that it could be something like SARS, for example, which just burns itself out when the reproduction rate gets below one. Why is it that you are, unfortunately, so certain that it will come back?’

In contrast, Vallance (e.g. 17.3.20: q104-5) suggests strongly that COVID-19’s properties indicate high transmissibility and continuous recurrence (we may have to plan for a ‘spike every year’). This definition of the problem underpins the UK government’s expectation of long term management and, I think, is one of several reasons that ministers and advisers describe evaluation as premature.

Second, they suggest that this approach is built on a further assumption of what it feasible in the UK in relation to social behaviour.

A key element of international comparison relates to very different assumptions about social behaviour in each country. For example, the committee heard from respondents about experiences in South Korea, Hong Kong, Taiwan, and Singapore, in which previous pandemics – such as SARS – had a profound effect on government preparation and public behaviour (e.g. Comas-Herrera, 19.5.20: q446; Lum (Professor of Social Work and Social Administration, Hong Kong University) 19.5.20: q450, 456, 463; Chen (Former Vice-President of the Republic of China (Taiwan), 3.6.20: 492-504).

As a result, in many countries, you can expect widespread mask use and routine temperature checks, relatively invasive test and tracing measures, and obligatory isolation, to form part of a government’s response (such as to act quickly on regional ‘hotspots’ to prevent nationwide spread; compare with Hancock, 17.4.20: q318 on the connection of a UK lockdown to national unity, and Vallance, 5.5.20: q410-11 lukewarm on regional approaches, but also Harries, 5.5.20; q416 on the UK addressing hotspots in the earliest phase).

All of these measures and behaviours can contain the transmission of coronavirus in a way that seems to be far less feasible in the UK. For example, Doyle (26.3.20: q199-202) suggests that the South Korean system involves a degree of personal invasion not expected in UK, including giving bank details to government and being tested in public places like restaurants.

Further, even if these measures are possible, there is scepticism about their long-term impact: ‘the Chinese state and people are still doing some pretty extraordinary things’, with the potential that ‘when they take their foot off the brake the epidemic will surge back again’ (Whitty, 5.3.20: q13-4).

Instead, the emphasis from UK government respondents is initially (from March) about recommending the measures with the highest positive public health impact and lowest negative social and economic impact (handwashing). For example, Whitty (5.3.20: q18, see also q25, and Vallance 17.3.20: q92) compares measures:

‘ranging from those with almost no economic impact and high efficacy – top of the range being washing your hands and second being covering your mouth with a tissue when you cough – all the way down to those that have major societal impact, such as closing schools, which obviously affects children but also parents, potentially employment and particular sectors of the economy. It is very easy to choose a package of measures that is quite dramatic but has relatively little impact on the epidemic. We are very keen to avoid that, so we are modelling out all the combinations that we can because people’s livelihoods depend on it’.

Throughout, there is an emphasis on what might work in a UK-style liberal democracy characterised by relatively low social regulation, reinforced with reference to behavioural public policy:

‘All the behavioural science would suggest that we have to get the transparency right. We have to get the communication right. We have to trust that people want to know things, they want to know about this and they want to be able to be empowered to make their own decisions’ (Vallance, 17.3.20: 98).

COVID-19 policy in the UK: oral evidence to the Health and Social Care Committee (5th March- 3rd June 2020)

  1. The need to ramp up testing (for many purposes)
  2. The inadequate supply of personal protective equipment (PPE)
  3. Defining the policy problem: ‘herd immunity’, long term management, and the containability of COVID-19
  4. Uncertainty and hesitancy during initial UK coronavirus responses
  5. Confusion about the language of intervention and stages of intervention
  6. The relationship between science, science advice, and policy
  7. Lower profile changes to policy and practice
  8. Race, ethnicity, and the social determinants of health

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2. The inadequate supply of personal protective equipment (PPE)

The inadequate supply of PPE is a feature of almost every evidence session (more so than the focus on adequate numbers of ventilators and ICU capacity – 17.3.20: q67, q124, q139-44; 26.3.20: q194; 14.4.20: q306; 17.4.20: q296).

Initial sessions focused on who should have access to PPE (for example, perhaps not GPs since people are advised not to attend surgeries – Harries, 5.3.20: q51) and the limited training on how to wear or dispose of it safely (Whitty, Chief Medical Officer, 5.3.20: q53).

The remaining sessions exposed a gulf in feedback between: (a) people giving oral evidence to the committee on behalf of government bodies, and (b) most other people responding to requests for information by MPs.

This disconnect prompts several MPs to describe PPE as a policy ‘fiasco’, note its impact on already decreasing trust in government, and connect this problem of trust to issues such as

  • PPE standards that seemed out of step with WHO guidance (for example, 26.3.20: q237-48), and
  • the reclassification of COVID-19 as no longer a ‘high-consequences infectious disease’ (note: it relates to the individual, not the population) (17.3.20: q170; 26.3.20: q258-9).

In other words, UK bodies denied – with only moderate success – that changes to PPE advice related to shortages of the right equipment.

Examples of specific PPE discussions include:

Pritchard (Chief Operating Officer, NHS England) and Stevens describe sufficient stockpiles but temporary distributional issues and a need to ramp up supply in the future, perhaps solved in a week (17.3.20: q129-31; 137). The Chair, Jeremy Hunt MP suggests that this answer is at odds with feedback from NHS staff describing access only to paper masks and aprons (17.3.20: q132).

Feedback from representatives of staff seeking PPE describe something more akin to a shortage crisis (for example, Nagpaul, 26.3.20: q239; Bullion, 26.3.20: q264; Green, 26.3.20: q266 and 289; Pittard, 17.4.20: q296; Kinnair, 17.4.20: q297 and 305). Again, Sarah Owen MP (26.3.20: q249) sums up the major gulf between oral evidence on PPE (from PHE and others) and the wider feedback from NHS and other care workers on the inadequacy of supply of the right protective equipment.

Hancock (17.4.20: q306) describes the supply of PPE (and ventilators) as the third element of his ‘battle plan’ (compare with Taiwo Owatemi MP, 17.4.20: q316 and Yvette Cooper MP, 17.4.20: q319 and a series of questions q348-58). However, Hopson (Chief Executive, NHS Providers, 14.5.20: q92-95) describes continued uncertainty (particularly with gowns), making it difficult to plan surgery or find the right PPE for women and ethnic minority staff, while Green (19.5.20: q470) describes the situation as far worse outside of NHS settings (on the assumption that the NHS was prioritised).

By June, Deighton, as ‘Adviser to the Secretary of State on PPE’, describes overcoming supply problems and taking the ‘kinks’ out of logistics (3.6.20: q553-4) and improvement by the day, while most questions suggest that this image of hope is still at odds with other feedback to MPs.

COVID-19 policy in the UK: oral evidence to the Health and Social Care Committee (5th March- 3rd June 2020)

  1. The need to ramp up testing (for many purposes)
  2. The inadequate supply of personal protective equipment (PPE)
  3. Defining the policy problem: ‘herd immunity’, long term management, and the containability of COVID-19
  4. Uncertainty and hesitancy during initial UK coronavirus responses
  5. Confusion about the language of intervention and stages of intervention
  6. The relationship between science, science advice, and policy
  7. Lower profile changes to policy and practice
  8. Race, ethnicity, and the social determinants of health

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1. The need to ramp up testing (for many purposes)

The need to ramp up testing is a recurring theme, in which respondents describe low capacity in the beginning, and continuous problems with ‘ramping up’ capacity, then reflect on the difference it could have made in key areas (during more reflective discussions in June).

The figures reported in oral evidence were 2000 per day (Harries, Deputy Chief Medical Officer, 5.3.20: q54), 4000 (Vallance, Chief Scientific Advisor, 17.3.20: q78-84), 7000 (Doyle, Medical Director, Public Health England, 26.3.20: q196), and 50000 (Hancock, Secretary of State, 17.4.20: q312), but increasingly in the absence of a definition of testing, which became important when the UK government began to treat all tests sent out as part of meeting its 100000 per day target.

In March, Vallance (17.3.20: q78-84) described capacity as 4000 reliable tests per day, and noted the lack of accuracy of the larger-scale of tests available in the market, to argue that the UK was one of the most frequent testers at the time. Such arguments dated very quickly. Hancock (17.4.20: q306) then describes ‘ramp-up testing’ as the fourth element of the government’s ‘battle plan’ but often with low clarity on how, and who would be responsible. This confusion is apparent when Doyle (26.3.20: q196) describes separate responsibilities, in which PHE would be responsible for testing NHS staff and patients (target 25000 tests per day), while the Office for Life Sciences would take forward the 100000 tests per day pledge.

In most cases, there is broad agreement on the negative impact of the limited testing capacity, including:

Surveillance and modelling

Vallance (17.3.20 and 5.5.20: q435) reflects on the need for more testing to aid initial surveillance, suggesting that they could have acted very differently if the testing capacity was higher. This issue will run and run. The absence of data affected the ability of advisory bodies to model the estimated ‘peak’ of infection (based partly on its doubling-rate) that became so central to the UK government’s initial lockdown strategy. Further, there is much debate on the adequacy of UK modelling. For example, listen to the Radio 4 series More or Less (10.6.20, ‘Antibody tests, early lockdown advice and European deaths’), which argues that, during the 1st press UK government conference (12th March), Vallance misjudged the UK as being 4- rather than 2-weeks behind Italy. Compare with Vallance (5.5.20: q390).

NHS staff and services

NHS bodies describe their reduced ability to operate effectively (throughout the session on 17.3.20 which included Stevens, chief executive of NHS England). Nagpaul (British Medical Association) (26.3.20: q203-4) describes the combination of (a) advice to self-isolate with symptoms, and (b) an absence of testing, as a potential cause of a 10% shortage of NHS staff during the crisis, and this problem is a continuous theme in this day’s evidence. Green (Care England) (26.3.20: q267) and Bullion (Vice-President, Association of Directors of Adult Social Services) (26.3.20: q279) make the same case for a social care sector already at low capacity. Kinnair (Royal College of Nursing) and Pittard (Faculty of Intensive Care Medicine) describe low testing (and limited PPE) as major worries for staff (17.4.20: q297)

Discharges to care homes

One key example – still to be explored fully – is the absence of routine testing of NHS patients during the push to discharge 15000 people from hospital to social care beds in England (Stevens, 17.3.20: q122-3; Green, 26.3.20: q274). Green (19.5.20: q470 and q478) notes that the UK Government prioritised the NHS at the expense of social care, prompting NHS discharges to care homes before proper testing was in place, while knowing that care homes are ill-suited to isolation measures. Note that the NHS was already under capacity pressure before the crisis (Stevens, 17.3.20: q165), and redeploying medical and nursing care from care homes, while Willet (Director for Acute Care, NHS England 17.3.20: q165) describes an already fragmented system of 12500 care homes in England.

Overall, the absence of sufficient information – from routine testing for the virus, and proper analysis of care home capacity – combined with a huge drive to favour NHS care and move people to care homes, contributed to a disproportionately large coronavirus problem in care homes.

This experience compares with many other countries that addressed care homes more effectively. In Germany, patients were not discharged to care homes unless they could quarantine (Halletz, Chief Executive Officer, AGVP (Employers’ Association – Care Homes) 19.5.20: q455). In South Korea, people were taken from care homes to be quarantined (Comas-Herrera, Assistant Professorial Research Fellow, Care Policy and Evaluation Centre, LSE, 19.5.20: q447).

Committee update, 12th June 2020: Figures confirming discharges of hospital patients into care homes, responding to the National Audit Office report Readying the NHS and adult social care in England for COVID-19. The NAO press release states:

‘Patients discharged quickly from hospitals between mid-March and mid-April were sometimes placed in care homes without being tested for COVID-19. On 17 March, hospitals were advised to discharge urgently all in-patients medically fit to leave in order to increase capacity to support those with acute healthcare needs. Between 17 March and 15 April, around 25,000 people were discharged from hospitals into care homes, compared with around 35,000 people in the same period in 2019. Due to government policy at the time, not all patients were tested for COVID-19 before discharge, with priority given to patients with symptoms. On 15 April, the policy was changed to test all those being discharged into care homes. It is not known how many patients discharged to care homes had COVID-19 at the point they left hospital’

Testing and contact tracing

The issue of testing in relation to initial contact tracing is less straightforward. On several occasions, PHE and health department respondents note that there came a point when the number of infections, and rate of infection, ruled out the effectiveness of contact tracing and testing in favour of UK-wide lockdown measures: ‘several weeks ago that ship had begun to sail. Nevertheless, we kept going until mid-March, until we were absolutely sure that contact tracing in that way would not work’ (Doyle, 26.3.20: q198; see also q232 on testing representing only one of many necessary measures).

There is a continuous discussion in multiple sessions on why the UK stopped contact tracing after it became clear that the rate of transmission was very high (e.g. Harries 5.5.20: q415 on the shift from ‘contain’ to ‘delay’ on 12th March, q418 on using limited tests in hospitals where most needed, and q425-8).

Costello (Professor of Global Health and Sustainable Development, UCL, 17.4.20: q303-4) agrees with this approach in relation to London and several other cities where prevalence and transmission were unusually high, but argues that in many places there were very few cases (fewer than 10 cases in 50 local health areas until mid-March) and that they could have been contained. This issue will run and run too (see the discussion on contain/ delay in the run up to the first peak).

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COVID-19 policy in the UK: oral evidence to the Health and Social Care Committee (5th March- 3rd June 2020)

This series of posts describes the key themes and issues to arise from oral evidence to the House of Commons Health and Social Care Committee on COVID-19. It is the first committee on my to-do list.

When possible, I have (or will) connect them to some other sources of information, such as the minutes from NERVTAG, the not-yet-read-by-me minutes by SAGE, and the 8000-word paper that I am writing (which is currently 20000 words, and based initially on this unwieldy blog post). The result is a very long read, which I have broken down into a collection of 9 reads. One unintended consequence is that you may not see a respondent’s full title in some posts, because originally I only listed it the first time on the full document. Fortunately, there is a simple solution: read all the posts from 1-8.

Two issues often seem to dominate the oral evidence to the Health and Social Care Committee in multiple sessions from March to June 2020:

  1. Limited testing: antigen testing to detect the virus now, then antibody testing to detect if someone had COVID-19 in the past.
  2. Shortages of personal protective equipment (PPE), initially for NHS staff, followed by concerns about availability in social care and other sectors.

These issues connect to a series of knock-on issues, such as the discharge of patients from NHS hospitals to care homes without being tested.

They also intersect with broader policy themes which include how to:

  1. Define coronavirus as a policy problem, such as with reference to the oft-abused phrase ‘herd immunity.
  2. Act despite uncertainty, or a lack of information on which to give advice and make choices.
  3. Define different stages of intervention, including contain, delay, research, mitigate, and suppress.
  4. Describe the relationship between science advice and policy, to project the sense that policy is evidence-informed but that elected politicians are responsible for choice.
  5. Identify the many changes to policy and practice that would otherwise receive minimal attention (in other words, they are low salience but high importance).
  6. Address the links between health inequalities and race and ethnicity.

These sessions generally relate to activity for England, but with few indications that the actions or issues are markedly different in Northern Ireland, Scotland, or Wales. Indeed, (a) there is frequent reference to UK-wide cooperation and coordination, and (b) issues such as NHS hospital discharges to care homes without testing or quarantine measures seem UK-wide (albeit with variations in practice). A proper focus on devolved government is also on the to-do list.

PS I also left out some issues because they seemed unresolved by June:

  • Test, track, and trace (Hancock, 17.4.20: q325-7; Vallance and Harries, 5.5.20: q425-8; Chen, 3.6.20: 492-504; Fraser, Professor of Pathogen Dynamics, University of Oxford and Harding, Executive Chair of NHS Test and Trace programme, 3.6.20: 510-52)
  • When to have border restrictions (Cooper, 17.4.20: q344)
  • Testing for a vaccine (Van-Tam, Deputy Chief Medical Officer, 17.4.20: q366)
  • Who to learn from, in relation to comparability (Vallance, 5.5.20: q435; see also the dedicated session 19.5.20 on South Korea, Hong Kong, Germany).

The full series of posts:

  1. The need to ramp up testing (for many purposes)
  2. The inadequate supply of personal protective equipment (PPE)
  3. Defining the policy problem: ‘herd immunity’, long term management, and the containability of COVID-19
  4. Uncertainty and hesitancy during initial UK coronavirus responses
  5. Confusion about the language of intervention and stages of intervention
  6. The relationship between science, science advice, and policy
  7. Lower profile changes to policy and practice
  8. Race, ethnicity, and the social determinants of health

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Summary of NERVTAG minutes, January-March 2020

NERVTAG is the New and Emerging Respiratory Virus Threats Advisory Group, reporting to PHE (Public Health England).

It began a series of extraordinary meetings on the coronavirus from 13th January 2020 (normally it meets once per year), summarized in Table 1.

In January, it agreed with PHE that the risk to the UK population was ‘very low’, rising to ‘low’ (by this stage, the rate of human-to-human infection was unclear). It focused primarily on (a) developments in the city of Wuhan (population: 11m) and then other parts of China, and (b) advice to UK travellers to China, then (c) giving advice for the NHS on how to define a case of COVID-19 in relation to symptoms (primarily fever) and a history of travel to an affected area. From the end of January, it began to discuss personal protective equipment (PPE) frequently, without describing the need to modify PHE advice significantly (and was not responsible for securing supply).

In February, it agreed (on the 21st) that the risk to the UK population was ‘moderate’. It responded to questions from COBR (Cabinet Office civil contingencies committee, convened to discuss national emergencies) on the most effective public preventive efforts, prioritizing frequent and effective hand washing and advising against face masks for members of the public with no symptoms. In response to questions from the Department of Health and Social Care (DHSC), it described a ‘Reasonable Worst Case’ in the UK (to inform scenario modelling) as an 85% infection of the population, with half of those affected showing symptoms, then suggested that an estimate of 4% (of those with symptoms) needing hospital care ‘seems low’, while 25% (of the 4%) requiring respiratory support ‘seems high’.

In March, it advised that voluntary self-isolation should be 7-14 days after ‘illness onset’, depending ‘on desired balance between containment and social disruption at the particular stage of the epidemic’. It should be longer during the ‘containment’ phase (‘In the current situation NERVTAG would prefer this period to be towards the longer end of the range’) but could be shorter when transmission is so widespread that someone infected represents a decreasing share of the infected population (‘an increased proportion of people may still be infectious when they end self-isolation but they will constitute a decreasing proportion of all infectious people’, 6.3.20: 2).

Throughout, members of NERVTAG focused quite heavily on what seemed feasible to suggest, informing initial thoughts on:

  1. Handwashing advice. Initially it warned against too nuanced messages to the public, such as on the amount of time to wash.
  2. Face mask use. It identified (in multiple discussions) the unclear benefits if someone is well, plus the unlikely widespread public compliance, coupled with limited public training in their hygienic use and disposal (and the possibility that mask use in the UK ‘may add to fear and anxiety’ – 28.1.20: 8)
  3. Voluntary self-isolation. It expressed uncertainty about public compliance, and the difficulty of knowing when the illness begins and infectiousness ends.
  4. Port of entry screening, assuming a low impact since it would miss most cases.

[Note: please use the PDF if the tables look a bit weird below]

NERVTAG table 1aNERVTAG table 1b

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Evidence & Policy insights during the COVID-19 Pandemic

Evidence & Policy Blog

Kat Smith and Paul Cairney

The COVID-19 pandemic is shining a light on the roles that evidence and expertise can play in policy and practice. Understanding the nature of these debates, and developing tools to help decision-makers navigate them, is the focus of the Evidence & Policy community. In this post, we consider how our reflections on the field’s key insights help us understand the role evidence is playing in the UK’s response to the current pandemic:


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Welcome to the Evidence & Policy blog: Our reflections on the field

Evidence & Policy Blog

Kat Smith and Paul Cairney

This new blog helps make the insights within Evidence & Policy accessible to all. In this opening post, the current Editors reflect on what they feel are some of the key insights about the interplay between evidence and policy:


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Coronavirus and the ‘social determinants’ of health inequalities: lessons from ‘Health in All Policies’ initiatives

Many public health bodies are responding to crisis by shifting their attention and resources from (1) a long-term strategic focus on reducing non-communicable diseases (such as heart diseases, cancers, diabetes), to (2) the coronavirus pandemic.

Of course, these two activities are not mutually exclusive, and smoking provides the most high-profile example of short-term and long-term warnings coming together (see Public Health England’s statement that ‘Emerging evidence from China shows smokers with COVID-19 are 14 times more likely to develop severe respiratory disease’).

There are equally important lessons – such as on health equity – from the experiences of longer-term and lower-profile ‘preventive’ public health agendas such as ‘Health in All Policies’ (HIAP).*

What is ‘Health in All Policies’?

HIAP is a broad (and often imprecise) term to describe:

  1. The policy problem. Address the ‘social determinants’ of health, defined by the WHO as ‘the unfair and avoidable differences in health status … shaped by the distribution of money, power and resources [and] the conditions in which people are born, grow, live, work and age’.
  2. The policy solutions. Identify a range of policy instruments, including redistributive measures to reduce economic inequalities, distributive measures to improve public services and the physical environment (including housing), regulations on commercial and individual behaviour, and health promotion via education and learning.
  3. The policy style. An approach to policymaking that encourages meaningful collaboration across multiple levels and types of government, and between governmental and non-governmental actors (partly because most policy solutions to improve health are not in the gift of health departments).
  4. Political commitment and will. High level political support is crucial to the production of a holistic strategy document, and to dedicate resources to its delivery, partly via specialist organisations and the means to monitor and evaluate progress.

As two distinctive ‘Marmot reviews’ demonstrate, this problem (and potential solutions) can be described differently in relation to:

Either way, each of the 4 HIAP elements highlights issues that intersect with the impact of the coronavirus: COVID-19 has a profoundly unequal impact on populations; there will be a complex mix of policy instruments to address it, and many responses will not be by health departments; an effective response requires intersectoral government action and high stakeholder and citizen ownership; and, we should not expect current high levels of public, media, and policymaker attention and commitment to continue indefinitely or help foster health equity (indeed, even well-meaning policy responses may exacerbate health inequalities). 

A commitment to health equity, or the reduction of health inequalities

At the heart of HIAP is a commitment to health equity and to reduce health inequalities. In that context, the coronavirus provides a stark example of the impact of health inequalities, since (a) people with underlying health conditions are the most vulnerable to major illness and death, and (b) the spread of underlying health conditions is unequal in relation to factors such as income and race or ethnicity. Further, there are major inequalities in relation to exposure to physical and economic risks.

A focus on the social determinants of health inequalities

A ‘social determinants’ focus helps us to place individual behaviour in a wider systemic context. It is tempting to relate health inequalities primarily to ‘lifestyles’ and individual choices, in relation to healthy eating, exercise, and the avoidance of smoking and alcohol. However, the most profound impacts on population health can come from (a) environments largely outside of an individual’s control (e.g. in relation to threats from others, such as pollution or violence), (b) levels of education and employment, and (c) economic inequality, influencing access to warm and safe housing, high quality water and nutrition, choices on transport, and access to safe and healthy environments.

In that context, the coronavirus provides stark examples of major inequalities in relation to self-isolation and social distancing: some people have access to food, private spaces to self-isolate, and open places to exercise away from others; many people have insufficient access to food, no private space, and few places to go outside (also note the disparity in resources between countries).

The pursuit of intersectoral action

A key aspect of HIAP is to identify the ways in which non-health sectors contribute to health. Classic examples include a focus on the sectors that influence early access to high quality education, improving housing and local environments, reducing vulnerability to crime, and reforming the built environment to foster sustainable public transport and access to healthy air, water, and food.

The response to the coronavirus also appears to be a good advert for the potential for intersectoral governmental action, demonstrating that measures with profound impacts on health and wellbeing are made in non-health sectors, including: treasury departments subsidising business and wages, and funding additional healthcare; transport departments regulating international and domestic travel; social care departments responsible for looking after vulnerable people outside of healthcare settings; and, police forces regulating social behaviour.

However, most (relevant) HIAP studies identify a general lack of effective intersectoral government action, related largely to a tendency towards ‘siloed’ policymaking within each department, exacerbated by ‘turf wars’ between departments (even if they notionally share the same aims) and a tendency for health departments to be low status, particularly in relation to economic departments (also note the frequently used term ‘health imperialism’ to describe scepticism about public health in other sectors).  Some studies highlight the potential benefits of ‘win-win’ strategies to persuade non-health sectors that collaboration on health equity also helps deliver their core business (e.g. Molnar et al 2015), but the wider public administration literature is more likely to identify a history of unsuccessful initiatives with a cumulative demoralising effect (e.g. Carey and Crammond, 2015; Molenveld et al, 2020).  

The pursuit of wider collaboration

HIAP ambitions extend to ‘collaborative’ or ‘co-produced’ forms of governance, in which citizens and stakeholders work with policymakers in health and non-health sectors to define the problem of health inequalities and inform potential solutions. These methods can help policymakers make sense of broad HIAP aims through the eyes of citizens, produce priorities that were not anticipated in a desktop exercise, help non-health sector workers understand their role in reducing health inequalities, and help reinforce the importance of collaborative and respectful ways of working.

An excellent example comes from Corburn et al’s (2014) study of Richmond, California’s statutory measures to encourage HIAP. They describe ‘coproducing health equity in all policies’ with initial reference to WHO definitions, but then to social justice in relation to income and wealth, which differs markedly according to race and immigration status. It then reports on a series of community discussions to identify key obstacles to health:

For example, Richmond residents regularly described how, in the same day, they might experience or fear violence, environmental pollution, being evicted from housing, not being able to pay health care bills, discrimination at work or in school, challenges accessing public services, and immigration and customs enforcement (ICE) intimidation … Also emerging from the workshops and health equity discussions was that one of the underlying causes of the multiple stressors experienced in Richmond was structural racism. By structural racism we meant that seemingly neutral policies and practices can function in racist ways by disempowering communities of color and perpetuating unequal historic conditions” (2014: 627-8).

Yet, a tiny proportion of HIAP studies identify this level of collaboration and new knowledge feeding into policy agendas to address health equity.

The cautionary tale: HIAP does not cause health equity

Rather, most of the peer-reviewed academic HIAP literature identifies a major gap between high expectations and low implementation. Most studies identify an urgent and strong impetus for policy action to be proportionate to the size of the policy problem, and ideas about the potential implementation of a HIAP agenda when agreed, but no studies identify implementation success in relation to health equity. In fact, the two most-discussed examples – in Finland and South Australia – seem to describe a successful reform of processes that have a negligible impact on equity.  

A window of opportunity for what?

It is common in the public health field to try to identify ‘windows of opportunity’ to adopt (a) HIAP in principle, and (b) specific HIAP-friendly policy instruments. It is also common to try to identify the factors that would aid HIAP implementation, and to assume that this success would have a major impact on the social determinants of health inequalities. Yet, the cumulative experience from HIAP studies is that governments can pursue health promotion and intersectoral action without reducing health inequalities.

For me, this is the context for current studies of the unequal impact of the coronavirus across the globe and within each country. In some cases, there are occasionally promising discussions of major policymaking reforms, or to use the current crisis as an impetus for social justice as well as crisis response. Yet, the history of the pursuit of HIAP-style reforms should help us reject the simple notion that some people saying the right things will make that happen. Instead, right now, it seems more likely that – in the absence of significantly new action** – the same people and systems that cause inequalities will undermine attempts to reduce them. In other words, health equity will not happen simply because it seems like the right thing to do. Rather, it is a highly contested concept, and many people will use their power to make sure that it does not happen, even if they claim otherwise.

*These are my early thoughts based on work towards a (qualitative) systematic review of the HIAP literature, in partnership with Emily St Denny, Sean Kippin, and Heather Mitchell.

**No, I do not know what that action would be. There is no magic formula to which I can refer.

See also: Tired of science being ignored? Get political by @DrMaryTBassett

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I was knocked off my motorbike in 1996

I was going at 60mph on the M8 East. Fast enough to be life threatening, but not fast enough to stop a car from overtaking and hitting my front wheel before it sped off. I broke my helmet and my wrist, which never fully recovered. Later on, the doctors gave me morphine and the nurses told me I was lucky to be alive.

For some reason, I thought of my baby daughter and vowed to give up the bike before deciding to crawl off the road. I still remember that split second to this day. If I wake up in the middle of the night to think about it, it’s mostly to relive that moment.

The rest is a blur. I remember the car’s motion but not the car. I remember that a man stopped traffic with his car, to give me time to move. I remember he took me to hospital, but not who he was or what he looked like. I don’t know if I thanked him, and thats the second thing I wake up to think about.

You see, I really want to make sure that I thanked him and that he knows I’m grateful. What are the chances that he might read this and remember, or that he told someone his story and they remember?

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Who can you trust during the coronavirus crisis?

By Paul Cairney and Adam Wellstead, based on this paper and article: Paul Cairney and Adam Wellstead (2020) ‘COVID-19: effective policymaking depends on trust in experts, politicians, and the public’, Policy Design and Practice https://www.tandfonline.com/doi/full/10.1080/25741292.2020.1837466 (PDF)

Trust is essential during a crisis. It is necessary for cooperation. Cooperation helps people coordinate action, to reduce the need for imposition. It helps reduce uncertainty in a complex world. It facilitates social order and cohesiveness. In a crisis, almost-instant choices about who to trust or distrust make a difference between life and death.

Put simply, we need to trust: experts to help us understand and address the problem, governments to coordinate policy and make choices about levels of coercion, and each other to cooperate to minimise infection.

Yet, there are three unresolved problems with understanding trust in relation to coronavirus policy.

  1. What does trust really mean?

Trust is one of those words that could mean everything and nothing. We feel like we understand it intuitively, but would also struggle to define it well enough to explain how exactly it works. For example, in social science, there is some agreement on the need to describe individual motivation, social relationships, and some notion of the ‘public good’:

  • the production of trust helps boost the possibility of cooperation, partly by
  • reducing uncertainty (low information about a problem) and ambiguity (low agreement on how to understand it) when making choices, partly by
  • helping you manage the risk of making yourself vulnerable when relying on others, particularly when
  • people demonstrate trustworthiness by developing a reputation for competence, honesty, and/ or reliability, and
  • you combine cognition and emotion to produce a disposition to trust, and
  • social and political rules facilitate this process, from the formal and well-understood rules governing behaviour to the informal rules and norms shaping behaviour.

As such, trust describes your non-trivial belief in the reliability of other people, organisations, or processes. It facilitates the kinds of behaviour that are essential to an effective response to the coronavirus, in which we need to:

  1. Make judgements about the accuracy of information underpinning our choices to change behaviour (such as from scientific agencies).
  2. Assess the credibility of the people with whom we choose to cooperate or take advice (such as more or less trust in each country’s leadership).
  3. Measure the effectiveness of the governments or political systems to which we pledge our loyalty.

Crucially, in most cases, people need to put their trust in actions or outcomes caused by people they do not know, and the explanation for this kind of trust is very different to trusting people you know.

  1. What does trust look like in policymaking?

Think of trust as a mechanism to boost cooperation and coalition formation, help reduce uncertainty, and minimise the ‘transactions costs’ of cooperation (for example, monitoring behaviour, or producing or enforcing contracts). However, uncertainty is remarkably high because the policy process is not easy to understand. We can try to understand the ‘mechanisms’ of trust, to boost cooperation, with reference to these statements about trustees and the trusted:

  1. Individuals need to find ways to make choices about who to trust and distrust.
  2. However, they must act within a complex policymaking environment in which they have minimal knowledge of what will happen and who will make it happen.
  3. To respond effectively, people seek ways to cooperate with others systematically, such as by establishing formal and informal rules.

People seeking to make and influence policy must act despite uncertainty about the probability of success or risk of failure. In a crisis, it happens almost instantly. People generate beliefs about what they want to happen and how their reliance on others can help it happen. This calculation depends on:

  • Another person or organisation’s reputation for being trustworthy, allowing people the ability to increase certainty when they calculate the risk of engagement.
  • The psychology of trust and perceptions of another actor’s motives. To some extent, people gather information and use logic to determine someone’s competence. However, they also use gut feeling or emotion to help them decide to depend on someone else. They may also trust a particular source if the cognitive load is low, such as because (a) the source is familiar (e.g. a well-known politician or a celebrity, or oft-used source), or (b) the information is not challenging to remember or accept.

If so, facilitators of trust include:

  • People share the same characteristics, such as beliefs, norms, or expectations.
  • Some people have reputations for being reliable, predictable, honest, competent, and/ or relatively selfless.
  • Good experiences of previous behaviour, including repeated interactions that foster rewards and help predict future risk (with face to face contact often described as particularly helpful).
  • People may trust people in a position of authority (or the organisation or office), such as an expert or policymaker (although perhaps the threat of rule enforcement is better understood as a substitute for trust, and in practice it is difficult to spot the difference).

High levels of trust are apparent when effective practices – built on reciprocity, emotional bonds, and/ or positive expectations – become the norms or formalised and written down for all to see and agree. High levels of distrust indicate a need to deter the breach of agreements, by introducing expectations combined with sanctions for not behaving as expected.

  1. Who should you trust?

These concepts do not explain fully why people trust particular people more than others, or help us determine who you should trust during a crisis.

Rather, first, they help us reflect on the ways in which people have been describing their own thought processes (click here, and scroll to ‘Limiting the use of evidence’), such as trusting an expert source because they: (a) have a particular scientific background, (b) have proven to be honest and reliable in the past, (c) represent a wider scientific profession/ community, (d) are part of a systematic policymaking machinery, (e) can be held to account for their actions, (f) are open about the limits to their knowledge, and/or (g) engage critically with information to challenge simplistic rushes to judgement. Overall, note how much trust relates to our minimal knowledge about their research skills, prompting us to rely on an assessment of their character or status to judge their behaviour. In most cases, this is an informal process in which people may not state (or really know) why they trust or distrust someone so readily.

Then, we can reflect on who we trust, and why, and if we should change how we make such calculations during a crisis like the coronavirus. Examples include:

  • A strong identity with a left or right wing cause might prompt us only to trust people from one political party. This thought process may be efficient during elections and debates, but does it work so well during a crisis necessitating so high levels of cross-party cooperation?
  • People may be inclined to ignore advice because they do not trust their government, but maybe (a) high empathy for their vulnerable neighbours, and (b) low certainty about the impact of their actions, should prompt them to trust in government advice unless they have a tangible reason not to (while low empathy helps explain actions such as hoarding).
  • Government policy is based strongly on the extent to which policymakers trust people to do the right thing. Most debates in liberal democracies relate to the idea that (a) people can be trusted, so give advice and keep action voluntary, or cannot be trusted, so make them do the right thing, and that (b) citizens can trust their government. In other words, it must be a reciprocal relationship (see the Tweets in Step 3).

Finally, governments make policy based on limited knowledge and minimal control of the outcomes, and they often respond with trial-and-error strategies. The latter is fine if attention to policy is low and trust in government sufficiently high. However, in countries like the UK and US, each new choice prompts many people to question not only the competence of leaders but also their motivation. This is a worrying development for which everyone should take some responsibility.

See also:

Policy Concepts in 1000 Words: the Institutional Analysis and Development Framework (IAD) and Governing the Commons

The coronavirus and evidence-informed policy analysis (short version)

The coronavirus and evidence-informed policy analysis (long version)

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Filed under 1000 words, 750 word policy analysis, Public health, public policy

El Coronavirus y el Análisis de Políticas Públicas Basado en Evidencia (versión corta)

Paul Cairney, Profesor de Política y Políticas Públicas en la Universidad de Stirling, Escocia. Enlace a texto original en inglés.

El coronavirus se siente como un nuevo problema público que requiere un nuevo análisis de política pública. El análisis debe basarse en (a) buena evidencia, que se traduzca en (b) buena política. Sin embargo, no se deje engañar y piense que estas partes son sencillas. Hay pasos que parecen simples que van desde definir un problema hasta hacer una recomendación, pero esta simplicidad enmascara el proceso profundamente político que se lleva a cabo. Cada paso del análisis involucra elecciones políticas para priorizar algunos problemas y algunas soluciones sobre otros y, por lo tanto, priorizar la vida de algunas personas a expensas de otras.

La versión larga de esta publicación (en inglés) nos lleva a través de estos pasos en el Reino Unido y los sitúa en un contexto político y de formulación de política pública más amplio. Esta publicación es más corta y solamente presenta superficialmente dicho análisis.

5 pasos para el análisis de políticas públicas

  1. Defina el Problema

Quizás podamos resumirlo como: (a) el impacto de este virus y enfermedad tendrá cierto nivel de muertes y enfermedades que podrían abrumar a la población y exceder la capacidad de los servicios públicos, por lo que (b) necesitamos contener el virus lo suficiente para asegurarnos de que se propaga de la manera correcta en el momento correcto, por lo que (c) necesitamos alentar y hacer que las personas cambien su comportamiento (esencialmente a través de la higiene y el distanciamiento social). Sin embargo, hay muchas formas de encuadrar este problema para enfatizar la importancia de algunas poblaciones sobre otras y algunos impactos sobre otros.

  1. Identifique soluciones técnica y políticamente factibles

Las soluciones no son realmente soluciones: son instrumentos de política que abordan un aspecto del problema, incluidos los impuestos y el gasto, la prestación de servicios públicos, el financiamiento de la investigación,  las recomendaciones a la población y la regulación o el fomento de cambios en el comportamiento social. Cada nuevo instrumento contribuye a un conjunto existente , con consecuencias impredecibles y no deseadas. Algunos instrumentos parecen técnicamente factibles (funcionarán según lo previsto si se implementan), pero no se adoptarán a menos que sean políticamente factibles (suficientes personas apoyan su  adopción). O viceversa. Este doble requisito descarta muchas respuestas.

  1. Use valores y objetivos para comparar soluciones

Los juicios típicos combinan: (a) una descripción amplia de valores tales como eficiencia, equidad, libertad, seguridad y dignidad humana, (b) metas instrumentales, tales como la formulación de políticas sostenibles (¿podemos hacerlo? y ¿por cuánto tiempo?), y viabilidad política (¿la gente estará de acuerdo con esto?, y ¿me hará más o menos popular o confiable?), y (c) el proceso de toma de decisiones, tal como el grado en que un proceso de política pública involucra a ciudadanos o partes interesadas (junto con expertos) en la deliberación. Se congregan para ayudar a los formuladores de políticas en la toma de decisiones de alto perfil (como el equilibrio entre la libertad individual y la coerción del Estado) y opciones de bajo perfil, pero profundas (para influir en el nivel de capacidad del servicio público y el nivel de intervención estatal y, por lo tanto, quién y cómo  las personas morirán).

  1. Anticipe el resultado de cada solución factible

Es difícil concebir una forma en la cual el Gobierno del Reino Unido publique todo el proceso detrás de sus elecciones (Paso 3) y predicciones (Paso 4) de una manera que fomente una deliberación pública efectiva. La gente a menudo demanda al Gobierno del Reino Unido que publique su asesoramiento experto y su lógica operativa, pero no estoy seguro de cómo lo separarían de su lógica normativa sobre quién debería vivir o morir, o proporcionar una franca explicación sin consecuencias imprevistas para la confianza o ansiedad públicas. Si así fuera, un aspecto de la política gubernamental es mantener implícitas algunas opciones y evitar un gran debate sobre las alternativas. Otra forma es tomar decisiones continuamente sin saber cuál será su impacto (el escenario más probable en este momento).

 

  1. Tome una elección o proporcione una recomendación para su cliente

Su recomendación o elección se basaría en estos cuatro pasos. Defina el problema con un marco de análisis a expensas de los otros. Idealice a algunas personas y no a otras. Decida la forma de apoyar a algunas personas y coaccionar o castigar a otras. Priorice la vida de algunas personas sabiendo que otras sufrirán o morirán. Hágalo a pesar de su falta de experiencia y de su conocimiento e información profundamente limitados. Aprenda de los expertos, pero no asuma que únicamente los expertos científicos tienen conocimiento relevante (descolonizar; coproducir). Recomiende opciones que, si son perjudiciales, podrían tomar décadas para solucionarlas después de que se haya ido. Considere si un formulador de políticas está dispuesto y puede actuar siguiendo su consejo, y si su acción propuesta funcionará según lo planeado. Considere si un gobierno está dispuesto y puede soportar los costos económicos y políticos. Proteja la popularidad de su cliente y confíe en él, al mismo tiempo que se protegen vidas. Considere si su consejo se modificaría si el problema pareciera cambiar. Si está escribiendo su análisis, quizás manténgalo en una cuartilla (en otras palabras, menos palabras que las escritas hasta este momento).

El análisis de políticas no es tan simple como sugieren estos pasos, y un análisis más detallado del contexto amplio de la formulación de políticas públicas ayuda a describir dos limitaciones importantes para la acción y el pensamiento analítico sencillos.

  1. Los formuladores de política pública deben ignorar casi toda la evidencia

La cantidad de información relevante para la política pública es infinita y la capacidad de análisis es finita. Por lo tanto, los individuos y los gobiernos necesitan formas de filtrar casi todo. Los individuos combinan cognición y emoción para ayudarlos a tomar decisiones de manera eficiente y los gobiernos tienen reglas equivalentes para priorizar solo cierta información. Esto incluye: definir un problema y una respuesta factible, buscar información disponible, comprensible y procesable, e identificar fuentes creíbles de información y consejo. En ese contexto, la vaga idea de confiar o no en expertos no tiene sentido. La versión larga de esta publicación destaca las muchas formas defectuosas en que todas las personas deciden de quién es la experiencia que toman en cuenta.

  1. Los formuladores no controlan el proceso de políticas.

Los formuladores de políticas públicas participan en un mundo desordenado e impredecible en el que ningún “centro” tiene el poder de convertir una recomendación de política en un resultado.

  • Hay muchos formuladores de políticas e individuos influyentes diseminados a lo largo del sistema político. Por ejemplo, considere el grado en que cada departamento gubernamental, organismos desconcentrados y organizaciones públicas y privadas toman sus propias decisiones que ayudan u obstaculizan la política del gobierno del Reino Unido.
  • La mayoría de las elecciones en el gobierno se toman en “subsistemas”, con sus propias reglas y redes, sobre las cuales los ministros tienen un conocimiento e influencia limitados.
  • El contexto social y económico, al igual que otros eventos, están en gran medida fuera de su control.

Mensajes para llevar a casa (si acepta esta argumentación)

  1. El coronavirus es un ejemplo extremo de una situación general: los formuladores de política pública siempre tendrán un conocimiento limitado de la problemática en la política pública y de control sobre el entorno de formulación de políticas. Toman decisiones para encuadrar problemas de manera estrecha, de manera tal que parezcan solucionables, descartan la mayoría de las soluciones como no factibles, hacen juicios de valor para intentar ayudar a algunos más que a otros, intentan predecir los resultados y responden cuando los resultados no coinciden con sus esperanzas o expectativas.
  2. Este no es un mensaje de fatalidad y desesperación. Más bien, nos alienta a pensar sobre cómo influir en el gobierno, y hacer que los responsables de las políticas rindan cuentas de una manera reflexiva y sistemática que no engañe al público ni exacerbe el problema que estamos viendo. Nadie está ayudando a su gobierno a resolver el problema diciendo estupideces en internet (bueno, esto último fue un mensaje de desesperación).

Para saber más:

La versión larga de este reporte [en inglés] expone estos argumentos con mucho más detalle, con algunos enlaces a otras ideas.

Esta serie de publicaciones de “750 palabras” [en inglés y en español]  resume textos clave en el análisis de políticas e intenta situar el análisis de políticas en un contexto político y de formulación de políticas más amplio. Tenga en cuenta el enfoque dentro de este conocimiento, el cual aún no es una característica importante de esta crisis.

Estas series de publicaciones de 500 palabras y 1000 palabras [en inglés] resumen conceptos y teorías en los estudios de políticas públicas.

Esta página sobre formulación de políticas basadas en evidencia (EBPM) [en inglés] utiliza esos conocimientos para demostrar por qué EBPM es un eslogan político en lugar de una expectativa realista. Algunas entradas de EBPM también están disponibles en español.

Estas conferencias grabadas [en inglés] relacionan esas ideas con preguntas comunes formuladas por los investigadores: ¿por qué los encargados de formular políticas parecen ignorar mi evidencia? [en inglés] y ¿qué puedo hacer al respecto? [en inglés] Estoy feliz de grabar más (como sobre el tema que acabas de leer) pero no estoy completamente seguro de quién querría escuchar qué.

Traductores

Anette Bonifant Cisneros anette.bonifant@york.ac.uk

Enrique García Tejeda cgarcia@up.edu.mx

 

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