Tag Archives: coronavirus

The UK Government’s COVID-19 policy: assessing evidence-informed policy analysis in real time

abstract 25k words

On the 23rd March 2020, the UK Government’s Prime Minister Boris Johnson declared: ‘From this evening I must give the British people a very simple instruction – you must stay at home’. He announced measures to help limit the impact of COVID-19 , including new regulations on behaviour, police powers to support public health, budgetary measures to support businesses and workers during their economic inactivity, the almost-complete closure of schools, and the major expansion of healthcare capacity via investment in technology, discharge to care homes, and a consolidation of national, private, and new health service capacity (note that many of these measures relate only to England, with devolved governments responsible for public health in Northern Ireland, Scotland, and Wales). Overall, the coronavirus prompted almost-unprecedented policy change, towards state intervention, at a speed and magnitude that seemed unimaginable before 2020.

Yet, many have criticised the UK government’s response as slow and insufficient. Criticisms include that UK ministers and their advisors did not:

  • take the coronavirus seriously enough in relation to existing evidence (when its devastating effect was increasingly apparent in China in January and Italy from February)
  • act as quickly as some countries to test for infection to limit its spread, and/ or introduce swift measures to close schools, businesses, and major social events, and regulate social behaviour (such as in Taiwan, South Korea, or New Zealand)
  • introduce strict-enough measures to stop people coming into contact with each other at events and in public transport.

They blame UK ministers for pursuing a ‘mitigation’ strategy, allegedly based on reducing the rate of infection and impact of COVID-19 until the population developed ‘herd immunity’, rather than an elimination strategy to minimise its spread until a vaccine or antiviral could be developed. Or, they criticise the over-reliance on specific models, which underestimated the R (rate of transmission) and ‘doubling time’ of cases and contributed to a 2-week delay of lockdown.

Many cite this delay, compounded by insufficient personal protective equipment (PPE) in hospitals and fatal errors in the treatment of care homes, as the biggest contributor to the UK’s unusually high number of excess deaths (Campbell et al, 2020; Burn-Murdoch and Giles, 2020; Scally et al, 2020; Mason, 2020; Ball, 2020; compare with Freedman, 2020a; 2020b and Snowden, 2020).

In contrast, scientific advisers to UK ministers have emphasised the need to gather evidence continuously to model the epidemic and identify key points at which to intervene, to reduce the size of the peak of population illness initially, then manage the spread of the virus over the longer term (e.g. Vallance). Throughout, they emphasised the need for individual behavioural change (hand washing and social distancing), supplemented by government action, in a liberal democracy in which direct imposition is unusual and, according to UK ministers, unsustainable in the long term.

We can relate these debates to the general limits to policymaking identified in policy studies (summarised in Cairney, 2016; 2020a; Cairney et al, 2019) and underpinning the ‘governance thesis’ that dominates the study of British policymaking (Kerr and Kettell, 2006: 11; Jordan and Cairney, 2013: 234).

First, policymakers must ignore almost all evidence. Individuals combine cognition and emotion to help them make choices efficiently, and governments have equivalent rules to prioritise only some information.

Second, policymakers have a limited understanding, and even less control, of their policymaking environments. No single centre of government has the power to control policy outcomes. Rather, there are many policymakers and influencers spread across a political system, and most choices in government are made in subsystems, with their own rules and networks, over which ministers have limited knowledge and influence. Further, the social and economic context, and events such as a pandemic, often appear to be largely out of their control.

Third, even though they lack full knowledge and control, governments must still make choices. Therefore, their choices are necessarily flawed.

Fourth, their choices produce unequal impacts on different social groups.

Overall, the idea that policy is controlled by a small number of UK government ministers, with the power to solve major policy problems, is still popular in media and public debate, but dismissed in policy research .

Hold the UK government to account via systematic analysis, not trials by social media

To make more sense of current developments in the UK, we need to understand how UK policymakers address these limitations in practice, and widen the scope of debate to consider the impact of policy on inequalities.

A policy theory-informed and real-time account helps us avoid after-the-fact wisdom and bad-faith trials by social media.

UK government action has been deficient in important ways, but we need careful and systematic analysis to help us separate (a) well-informed criticism to foster policy learning and hold ministers to account, from (a) a naïve and partisan rush to judgement that undermines learning and helps let ministers off the hook.

To that end, I combine insights from policy analysis guides, policy theories, and critical policy analysis to analyse the UK government’s initial coronavirus policy. I use the lens of 5-step policy analysis models to identify what analysts and policymakers need to do, the limits to their ability to do it, and the distributional consequences of their choices.

I focus on sources in the public record, including oral evidence to the House of Commons Health and Social Care committee, and the minutes and meeting papers of the UK Government’s Scientific Advisory Group for Emergencies (SAGE) (and NERVTAG), transcripts of TV press conferences and radio interviews, and reports by professional bodies and think tanks.

The short version is here. The long version – containing a huge list of sources and ongoing debates – is here. Both are on the COVID-19 page.

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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

Frankly, the widespread and intense focus on ‘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.’

Defining the COVID-19 problem in the UK

If so, this clarity 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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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.

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Filed under COVID-19, Prevention policy, 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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The coronavirus and evidence-informed policy analysis (short version)

The coronavirus feels like a new policy problem that requires new policy analysis. The analysis should be informed by (a) good evidence, translated into (b) good policy. However, don’t be fooled into thinking that either of those things are straightforward. There are simple-looking steps to go from defining a problem to making a recommendation, but this simplicity masks the profoundly political process that must take place. Each step in analysis involves political choices to prioritise some problems and solutions over others, and therefore prioritise some people’s lives at the expense of others.

The very-long version of this post takes us through those steps in the UK, and situates them in a wider political and policymaking context. This post is shorter, and only scratches the surface of analysis.

5 steps to policy analysis

  1. Define the problem.

Perhaps we can sum it up as: (a) the impact of this virus and illness will be a level of death and illness that could overwhelm the population and exceed the capacity of public services, so (b) we need to contain the virus enough to make sure it spreads in the right way at the right time, so (c) we need to encourage and make people change their behaviour (primarily via hygiene and social distancing). However, there are many ways to frame this problem to emphasise the importance of some populations over others, and some impacts over others.

  1. Identify technically and politically feasible solutions.

Solutions are not really solutions: they are policy instruments that address one aspect of the problem, including taxation and spending, delivering public services, funding research, giving advice to the population, and regulating or encouraging changes to social behaviour. Each new instrument contributes an existing mix, with unpredictable and unintended consequences. Some instruments seem technically feasible (they will work as intended if implemented), but will not be adopted unless politically feasible (enough people support their introduction). Or vice versa. This dual requirement rules out a lot of responses.

  1. Use values and goals to compare solutions.

Typical judgements combine: (a) broad descriptions of values such as efficiency, fairness, freedom, security, and human dignity, (b) instrumental goals, such as sustainable policymaking (can we do it, and for how long?), and political feasibility (will people agree to it, and will it make me more or less popular or trusted?), and (c) the process to make choices, such as the extent to which a policy process involves citizens or stakeholders (alongside experts) in deliberation. They combine to help policymakers come to high profile choices (such as the balance between individual freedom and state coercion), and low profile but profound choices (to influence the level of public service capacity, and level of state intervention, and therefore who and how many people will die).

  1. Predict the outcome of each feasible solution.

It is difficult to envisage a way for the UK Government to publicise all of the thinking behind its choices (Step 3) and predictions (Step 4) in a way that would encourage effective public deliberation. People often call for the UK Government to publicise its expert advice and operational logic, but I am not sure how they would separate it from their normative logic about who should live or die, or provide a frank account without unintended consequences for public trust or anxiety. If so, one aspect of government policy is to keep some choices implicit and avoid a lot of debate on trade-offs. Another is to make choices continuously without knowing what their impact will be (the most likely scenario right now).

  1. Make a choice, or recommendation to your client.

Your recommendation or choice would build on these four steps. Define the problem with one framing at the expense of the others. Romanticise some people and not others. Decide how to support some people, and coerce or punish others. Prioritise the lives of some people in the knowledge that others will suffer or die. Do it despite your lack of expertise and profoundly limited knowledge and information. Learn from experts, but don’t assume that only scientific experts have relevant knowledge (decolonise; coproduce). Recommend choices that, if damaging, could take decades to fix after you’ve gone. Consider if a policymaker is willing and able to act on your advice, and if your proposed action will work as intended. Consider if a government is willing and able to bear the economic and political costs. Protect your client’s popularity, and trust in your client, at the same time as protecting lives. Consider if your advice would change if the problem seemed to change. If you are writing your analysis, maybe keep it down to one sheet of paper (in other words, fewer words than in this post up to this point).

Policy analysis is not as simple as these steps suggest, and further analysis of the wider policymaking environment helps describe two profound limitations to simple analytical thought and action.

  1. Policymakers must ignore almost all evidence

The amount of policy relevant information is infinite, and capacity is finite. So, individuals and governments need ways to filter out almost all of it. Individuals combine cognition and emotion to help them make choices efficiently, and governments have equivalent rules to prioritise only some information. They include: define a problem and a feasible response, seek information that is available, understandable, and actionable, and identify credible sources of information and advice. In that context, the vague idea of trusting or not trusting experts is nonsense, and the larger post highlights the many flawed ways in which all people decide whose expertise counts.

  1. They do not control the policy process.

Policymakers engage in a messy and unpredictable world in which no single ‘centre’ has the power to turn a policy recommendation into an outcome.

  • There are many policymakers and influencers spread across a political system. For example, consider the extent to which each government department, devolved governments, and public and private organisations are making their own choices that help or hinder the UK government approach.
  • Most choices in government are made in ‘subsystems’, with their own rules and networks, over which ministers have limited knowledge and influence.
  • The social and economic context, and events, are largely out of their control.

The take home messages (if you accept this line of thinking)

  1. The coronavirus is an extreme example of a general situation: policymakers will always have very limited knowledge of policy problems and control over their policymaking environment. They make choices to frame problems narrowly enough to seem solvable, rule out most solutions as not feasible, make value judgements to try help some more than others, try to predict the results, and respond when the results do not match their hopes or expectations.
  2. This is not a message of doom and despair. Rather, it encourages us to think about how to influence government, and hold policymakers to account, in a thoughtful and systematic way that does not mislead the public or exacerbate the problem we are seeing. No one is helping their government solve the problem by saying stupid shit on the internet (OK, that last bit was a message of despair).

 

Further reading:

The longer report sets out these arguments in much more detail, with some links to further thoughts and developments.

This series of ‘750 words’ posts summarises key texts in policy analysis and tries to situate policy analysis in a wider political and policymaking context. Note the focus on whose knowledge counts, which is not yet a big feature of this crisis.

These series of 500 words and 1000 words posts (with podcasts) summarise concepts and theories in policy studies.

This page on evidence-based policymaking (EBPM) uses those insights to demonstrate why EBPM is  a political slogan rather than a realistic expectation.

These recorded talks relate those insights to common questions asked by researchers: why do policymakers seem to ignore my evidence, and what can I do about it? I’m happy to record more (such as on the topic you just read about) but not entirely sure who would want to hear what.

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Filed under 750 word policy analysis, agenda setting, Evidence Based Policymaking (EBPM), Policy learning and transfer, POLU9UK, Prevention policy, Psychology Based Policy Studies, Public health, public policy, Social change, UK politics and policy

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

This is the long version. It is long. Too long to call a blog post. Let’s call it a ‘living document’ that I update and amend as new developments arise (then start turning into a more organised paper). In most cases, I am adding tweets, so the date of the update is embedded. If I add a new section, I will add a date. If you seek specific topics (like ‘herd immunity’), it might be worth doing a search. The short version is shorter.

The coronavirus feels like a new policy problem. Governments already have policies for public health crises, but the level of uncertainty about the spread and impact of this virus seems to be taking it to a new level of policy, media, and public attention. The UK Government’s Prime Minister calls it ‘the worst public health crisis for a generation’.

As such, there is no shortage of opinions on what to do, but there is a shortage of well-considered opinions, producing little consensus. Many people are rushing to judgement and expressing remarkably firm opinions about the best solutions, but their contributions add up to contradictory evaluations, in which:

  • the government is doing precisely the right thing or the completely wrong thing,
  • we should listen to this expert saying one thing or another expert saying the opposite.

Lots of otherwise-sensible people are doing what they bemoan in politicians: rushing to judgement, largely accepting or sharing evidence only if it reinforces that judgement, and/or using their interpretation of any new development to settle scores with their opponents.

Yet, anyone who feels, without uncertainty, that they have the best definition of, and solution to, this problem is a fool. If people are also sharing bad information and advice, they are dangerous fools. Further, as Professor Madley puts it (in the video below), ‘anyone who tells you they know what’s going to happen over the next six months is lying’.

In that context, how can we make sense of public policy to address the coronavirus in a more systematic way?

Studies of policy analysis and policymaking do not solve a policy problem, but they at least give us a language to think it through.

  1. Let’s focus on the UK as an example, and use common steps in policy analysis, to help us think through the problem and how to try to manage it.
  • In each step, note how quickly it is possible to be overwhelmed by uncertainty and ambiguity, even when the issue seems so simple at first.
  • Note how difficult it is to move from Step 1, and to separate Step 1 from the others. It is difficult to define the problem without relating it to the solution (or to the ways in which we will evaluate each solution).
  1. Let’s relate that analysis to research on policymaking, to understand the wider context in which people pay attention to, and try to address, important problems that are largely out of their control.

Throughout, note that I am describing a thought process as simply as I can, not a full examination of relevant evidence. I am highlighting the problems that people face when ‘diagnosing’ policy problems, not trying to diagnose it myself. To do so, I draw initially on common advice from the key policy analysis texts (summaries of the texts that policy analysis students are most likely to read) that simplify the process a little too much. Still, the thought process that it encourages took me hours alone (spread over three days) to produce no real conclusion. Policymakers and advisers, in the thick of this problem, do not have that luxury of time or uncertainty.

See also: Boris Johnson’s address to the nation in full (23.3.20) and press conference transcripts

https://twitter.com/BorisJohnson/status/1246358936585986048

https://twitter.com/BorisJohnson/status/1243496858095411200

https://twitter.com/R_S_P_H/status/1242833029728477188

Step 1 Define the problem

Common advice in policy analysis texts:

  • Provide a diagnosis of a policy problem, using rhetoric and eye-catching data to generate attention.
  • Identify its severity, urgency, cause, and our ability to solve it. Don’t define the wrong problem, such as by oversimplifying.
  • Problem definition is a political act of framing, as part of a narrative to evaluate the nature, cause, size, and urgency of an issue.
  • Define the nature of a policy problem, and the role of government in solving it, while engaging with many stakeholders.
  • ‘Diagnose the undesirable condition’ and frame it as ‘a market or government failure (or maybe both)’.

Coronavirus as a physical problem is not the same as a coronavirus policy problem. To define the physical problem is to identify the nature, spread, and impact of a virus and illness on individuals and populations. To define a policy problem, we identify the physical problem and relate it (implicitly or explicitly) to what we think a government can, and should, do about it. Put more provocatively, it is only a policy problem if policymakers are willing and able to offer some kind of solution.

This point may seem semantic, but it raises a profound question about the capacity of any government to solve a problem like an epidemic, or for governments to cooperate to solve a pandemic. It is easy for an outsider to exhort a government to ‘do something!’ (or ‘ACT NOW!’) and express certainty about what would happen. However, policymakers inside government:

  1. Do not enjoy the same confidence that they know what is happening, or that their actions will have their intended consequences, and
  2. Will think twice about trying to regulate social behaviour under those circumstances, especially when they
  3. Know that any action or inaction will benefit some and punish others.

For example, can a government make people wash their hands? Or, if it restricts gatherings at large events, can it stop people gathering somewhere else, with worse impact? If it closes a school, can it stop children from going to their grandparents to be looked after until it reopens? There are 101 similar questions and, in each case, I reckon the answer is no. Maybe government action has some of the desired impact; maybe not. If you agree, then the question might be: what would it really take to force people to change their behaviour?

See also: Coronavirus has not suspended politics – it has revealed the nature of power (David Runciman)

The answer is: often too much for a government to consider (in a liberal democracy), particularly if policymakers are informed that it will not have the desired impact.

https://twitter.com/AdamJKucharski/status/1238152492178976769

If so, the UK government’s definition of the policy problem will incorporate this implicit question: what can we do if we can influence, but not determine (or even predict well) how people behave?

Uncertainty about the coronavirus plus uncertainty about policy impact

Now, add that general uncertainty about the impact of government to this specific uncertainty about the likely nature and spread of the coronavirus:

https://www.youtube.com/watch?time_continue=350&v=blkDulsgh3Q&feature=emb_logo

A summary of this video suggests:

  • There will be an epidemic (a profound spread to many people in a short space of time), then the problem will be endemic (a long-term, regular feature of life) (see also UK policy on coronavirus COVID-19 assumes that the virus is here to stay).
  • In the absence of a vaccine, the only way to produce ‘herd immunity’ is for most people to be infected and recover

[Note: there is much debate on whether ‘herd immunity’ is or is not government policy. Much of it relates to interpretation, based on levels of trust/distrust in the UK Government, its Prime Minister, and the Prime Minister’s special adviser. I discuss this point below under ‘trial and error policymaking’. See also Who can you trust during the coronavirus crisis? ]

  • The ideal spread involves all well people sharing the virus first, while all vulnerable people (e.g. older, and/or with existing health problems that affect their immune systems) protected in one isolated space, but it won’t happen like that; so, we are trying to minimise damage in the real world.
  • We mainly track the spread via deaths, with data showing a major spike appearing one month later, so the problem may only seem real to most people when it is too late to change behaviour

https://twitter.com/ChrisGiles_/status/1247458186300456960

https://twitter.com/d_spiegel/status/1248157520943857665

https://twitter.com/d_spiegel/status/1247824140645683205

https://twitter.com/EmergMedDr/status/1250039068890726400

See also: Coronavirus: Government expert defends not closing UK schools (BBC, Sir Patrick Vallance 13th March 2020)

https://twitter.com/DrSamSims/status/1247445729439895555

  • The choice in theory is between a rapid epidemic with a high peak, or a slowed-down epidemic over a longer period, but ‘anyone who tells you they know what’s going to happen over the next six months is lying’.
  • Maybe this epidemic will be so memorable as to shift social behaviour, but so much depends on trying to predict (badly) if individuals will actually change (see also Spiegelhalter on communicating risk).

None of this account tells policymakers what to do, but at least it helps them clarify three key aspects of their policy problem:

  1. The impact of this virus and illness could overwhelm the population, to the extent that it causes mass deaths, causes a level of illness that exceeds the capacity of health services to treat, and contributes to an unpredictable amount of social and economic damage.
  2. We need to contain the virus enough to make sure it (a) spreads at the right speed and/or (b) peaks at the right time. The right speed seems to be: a level that allows most people to recover alone, while the most vulnerable are treated well in healthcare settings that have enough capacity. The right time seems to be the part of the year with the lowest demand on health services (e.g. summer is better than winter). In other words, (a) reduce the size of the peak by ‘flattening the curve’, and/or (b) find the right time of year to address the peak, while (c) anticipating more than one peak.

My impression is that the most frequently-expressed aim is (a) …

https://twitter.com/STVNews/status/1238468179036459008

https://twitter.com/DHSCgovuk/status/1238540941717356548

… while the UK Government’s Deputy Chief Medical Officer also seems to be describing (b):

  1. We need to encourage or coerce people to change their behaviour, to look after themselves (e.g. by handwashing) and forsake their individual preferences for the sake of public health (e.g. by self-isolating or avoiding vulnerable people). Perhaps we can foster social trust and empathy to encourage responsible individual action. Perhaps people will only protect others if obliged to do so (compare Stone; Ostrom; game theory).

See also: From across the Ditch: How Australia has to decide on the least worst option for COVID-19 (Prof Tony Blakely on three bad options: (1) the likelihood of ‘elimination’ of the virus before vaccination is low; (2) an 18-month lock-down will help ‘flatten the curve’; (3) ‘to prepare meticulously for allowing the pandemic to wash through society over a period of six or so months. To tool up the production of masks and medical supplies. To learn as quickly as possible which treatments of people sick with COVID-19 saves lives. To work out our strategies for protection of the elderly and those with a chronic condition (for whom the mortality from COVID-19 is much higher’).

https://twitter.com/luciadambruoso/status/1246361265909444608

https://twitter.com/anandMenon1/status/1246712962519310337

From uncertainty to ambiguity

If you are still with me, I reckon you would have worded those aims slightly differently, right? There is some ambiguity about these broad intentions, partly because there is some uncertainty, and partly because policymakers need to set rather vague intentions to generate the highest possible support for them. However, vagueness is not our friend during a crisis involving such high anxiety. Further, they are only delaying the inevitable choices that people need to make to turn a complex multi-faceted problem into something simple enough to describe and manage. The problem may be complex, but our attention focuses only on a small number of aspects, at the expense of the rest. Examples that have arisen, so far, include to accentuate:

  1. The health of the whole population or people who would be affected disproportionately by the illness.
  • For example, the difference in emphasis affects the health advice for the relatively vulnerable (and the balance between exhortation and reassurance)

https://twitter.com/colinrtalbot/status/1238227267471527937?s=09

https://twitter.com/hacscot/status/1240588827829436416?s=09

https://twitter.com/lisatrigg/status/1249670660802187266

 

  1. Inequalities in relation to health, socio-economic status (e.g. income, gender, race, ethnicity), or the wider economy.
  • For example, restrictive measures may reduce the risk of harm to some, but increase the burden on people with no savings or reliable sources of income.
  • For example, some people are hoarding large quantities of home and medical supplies that (a) other people cannot afford, and (b) some people cannot access, despite having higher need.
  • For example, social distancing will limit the spread of the virus (see the nascent evidence), but also produce highly unequal forms of social isolation that increase the risk of domestic abuse (possibly exacerbated by school closures) and undermine wellbeing. Or, there will be major policy changes, such as to the rules to detain people under mental health legislation, regarding abortion, or in relation to asylum (note: some of these tweets are from the US, partly because I’m seeing more attention to race – and the consequence of systematic racism on the socioeconomic inequalities so important to COVID-19 mortality – than in the UK).

See also: COVID-19: how the UK’s economic model contributes towards a mismanagement of the crisis (Carolina Alves and Farwa Sial 30.3.20),

Economic downturn and wider NHS disruption likely to hit health hard – especially health of most vulnerable (Institute for Fiscal Studies 9.4.20),

Don’t be fooled: Britain’s coronavirus bailout will make the rich richer still (Christine Berry 13.4.20)

https://twitter.com/closethepaygap/status/1244579870392422400

https://twitter.com/heyDejan/status/1238944695260233728?s=09

https://twitter.com/TimothyNoah1/status/1240375741809938433

https://twitter.com/politicshome/status/1249236632009691136?s=09

 

https://twitter.com/NPR/status/1246837779474120705?s=09

https://twitter.com/povertyscholar/status/1246487621230092294

https://twitter.com/Yamiche/status/1248028548998344708

https://twitter.com/MalindaSmith/status/1247281226274107392

https://twitter.com/Jas_Athwal/status/1248875273568878592?s=09

https://twitter.com/GKBhambra/status/1248874500764073989

cc

https://twitter.com/sunny_hundal/status/1247454112762990592

https://twitter.com/olivernmoody/status/1248260326140805125

https://twitter.com/boodleoops/status/1246717497308577792

https://twitter.com/boodleoops/status/1246717497308577792

https://twitter.com/MarioLuisSmall/status/1239879542094925825

https://twitter.com/kevinstoneUWE/status/1240000285046640645?s=09

https://twitter.com/colinimckay/status/1240721797731045378?s=09

https://twitter.com/heytherehurley/status/1242113416103432195

https://twitter.com/stellacreasy/status/1244022413865648128

https://twitter.com/NIOgov/status/1246482663738871811

https://twitter.com/refugeecouncil/status/1243842703680471040

https://twitter.com/libertyhq/status/1248173788598013953

https://twitter.com/TheLancet/status/1246039259880054784

https://twitter.com/profhrs/status/1247572112061222914

https://twitter.com/HumzaYousaf/status/1248262165657722885

  • For example, governments cannot ignore the impact of their actions on the economy, however much they emphasise mortality, health, and wellbeing. Most high-profile emphasis was initially on the fate of large and small businesses, and people with mortgages, but a long period of crisis will a tip the balance from low income to unsustainable poverty (even prompting Iain Duncan Smith to propose policy change), and why favour people who can afford a mortgage over people scraping the money together for rent?
  1. A need for more communication and exhortation, or for direct action to change behaviour.
  2. The short term (do everything possible now) or long term (manage behaviour over many months).
  1. How to maintain trust in the UK government when (a) people are more or less inclined to trust a the current part of government and general trust may be quite low, and (b) so many other governments are acting differently from the UK.

https://twitter.com/DrSophieHarman/status/1238893265782530059

https://twitter.com/Sander_vdLinden/status/1242168652180475906?s=09

https://twitter.com/policyatkings/status/1248318259029516289

  • For example, note the visible presence of the Prime Minister, but also his unusually high deference to unelected experts such as (a) UK Government senior scientists providing direct advice to ministers and the public, and (b) scientists drawing on limited information to model behaviour and produce realistic scenarios (we can return to the idea of ‘evidence-based policymaking’ later). This approach is not uncommon with epidemics/ pandemics (LD was then the UK Government’s Chief Medical Officer):

https://twitter.com/AndyBurnhamGM/status/1239153510903619584

  • For example, note how often people are second guessing and criticising the UK Government position (and questioning the motives of Conservative ministers).

See also: Coronavirus: meet the scientists who are now household names

  1. How policy in relation to the coronavirus relates to other priorities (e.g. Brexit, Scottish independence, trade, education, culture)

7. Who caused, or who is exacerbating, the problem? The answers to such questions helps determine which populations are most subject to policy intervention.

  • For example, people often try to lay blame for viruses on certain populations, based on their nationality, race, ethnicity, sexuality, or behaviour (e.g. with HIV).
  • For example, the (a) association between the coronavirus and China and Chinese people (e.g. restrict travel to/ from China; e.g. exacerbate racism), initially overshadowed (b) the general role of international travellers (e.g. place more general restrictions on behaviour), and (c) other ways to describe who might be responsible for exacerbating a crisis.

See also: ‘Othering the Virus‘ by Marius Meinhof

Under ‘normal’ policymaking circumstances, we would expect policymakers to resolve this ambiguity by exercising power to set the agenda and make choices that close off debate. Attention rises at first, a choice is made, and attention tends to move on to something else. With the coronavirus, attention to many different aspects of the problem has been lurching remarkably quickly. The definition of the policy problem often seems to be changing daily or hourly, and more quickly than the physical problem. It will also change many more times, particularly when attention to each personal story of illness or death prompts people to question government policy every hour. If the policy problem keeps changing in these ways, how could a government solve it?

Step 2 Identify technically and politically feasible solutions

Common advice in policy analysis texts:

  • Identify the relevant and feasible policy solutions that your audience/ client might consider.
  • Explain potential solutions in sufficient detail to predict the costs and benefits of each ‘alternative’ (including current policy).
  • Provide ‘plausible’ predictions about the future effects of current/ alternative policies.
  • Identify many possible solutions, then select the ‘most promising’ for further analysis.
  • Identify how governments have addressed comparable problems, and a previous policy’s impact.

Policy ‘solutions’ are better described as ‘tools’ or ‘instruments’, largely because (a) it is rare to expect them to solve a problem, and (b) governments use many instruments (in different ways, at different times) to make policy, including:

  1. Public expenditure (e.g. to boost spending for emergency care, crisis services, medical equipment)
  2. Economic incentives and disincentives (e.g. to reduce the cost of business or borrowing, or tax unhealthy products)
  3. Linking spending to entitlement or behaviour (e.g. social security benefits conditional on working or seeking work, perhaps with the rules modified during crises)
  4. Formal regulations versus voluntary agreements (e.g. making organisations close, or encouraging them to close)
  5. Public services: universal or targeted, free or with charges, delivered directly or via non-governmental organisations
  6. Legal sanctions (e.g. criminalising reckless behaviour)
  7. Public education or advertising (e.g. as paid adverts or via media and social media)
  8. Funding scientific research, and organisations to advise on policy
  9. Establishing or reforming policymaking units or departments
  10. Behavioural instruments, to ‘nudge’ behaviour (seemingly a big feature in the UK , such as on how to encourage handwashing).

As a result, what we call ‘policy’ is really a complex mix of instruments adopted by one or more governments. A truism in policy studies is that it is difficult to define or identify exactly what policy is because (a) each new instrument adds to a pile of existing measures (with often-unpredictable consequences), and (b) many instruments designed for individual sectors tend, in practice, to intersect in ways that we cannot always anticipate. When you think through any government response to the coronavirus, note how every measure is connected to many others.

Further, it is a truism in public policy that there is a gap between technical and political feasibility: the things that we think will be most likely to work as intended if implemented are often the things that would receive the least support or most opposition. For example:

  1. Redistributing income and wealth to reduce socio-economic inequalities (e.g. to allay fears about the impact of current events on low-income and poverty) seems to be less politically feasible than distributing public services to deal with the consequences of health inequalities.
  2. Providing information and exhortation seems more politically feasible than the direct regulation of behaviour. Indeed, compared to many other countries, the UK Government seems reluctant to introduce ‘quarantine’ style measures to restrict behaviour.

Under ‘normal’ circumstances, governments may be using these distinctions as simple heuristics to help them make modest policy changes while remaining sufficiently popular (or at least looking competent). If so, they are adding or modifying policy instruments during individual ‘windows of opportunity’ for specific action, or perhaps contributing to the sense of incremental change towards an ambitious goal.

Right now, we may be pushing the boundaries of what seems possible, since crises – and the need to address public anxiety – tend to change what seems politically feasible. However, many options that seem politically feasible may not be possible (e.g. to buy a lot of extra medical/ technology capacity quickly), or may not work as intended (e.g. to restrict the movement of people). Think of technical and political feasibility as necessary but insufficient on their own, which is a requirement that rules out a lot of responses.

https://twitter.com/CairneyPaul/status/1244970044351791104

https://twitter.com/ChrisCEOHopson/status/1249617980859744256?s=09

Step 3 Use value-based criteria and political goals to compare solutions

Common advice in policy analysis texts:

  • Typical value judgements relate to efficiency, equity and fairness, the trade-off between individual freedom and collective action, and the extent to which a policy process involves citizens in deliberation.
  • Normative assessments are based on values such as ‘equality, efficiency, security, democracy, enlightenment’ and beliefs about the preferable balance between state, communal, and market/ individual solutions
  • ‘Specify the objectives to be attained in addressing the problem and the criteria  to  evaluate  the  attainment  of  these  objectives  as  well as  the  satisfaction  of  other  key  considerations  (e.g.,  equity,  cost, equity, feasibility)’.
  • ‘Effectiveness, efficiency, fairness, and administrative efficiency’ are common.
  • Identify (a) the values to prioritise, such as ‘efficiency’, ‘equity’, and ‘human dignity’, and (b) ‘instrumental goals’, such as ‘sustainable public finance or political feasibility’, to generate support for solutions.
  • Instrumental questions may include: Will this intervention produce the intended outcomes? Is it easy to get agreement and maintain support? Will it make me popular, or diminish trust in me even further?

Step 3 is the most simple-looking but difficult task. Remember that it is a political, not technical, process. It is also a political process that most people would like to avoid doing (at least publicly) because it involves making explicit the ways in which we prioritise some people over others. Public policy is the choice to help some people and punish or refuse to help others (and includes the choice to do nothing).

Policy analysis texts describe a relatively simple procedure of identifying criteria and producing a table (with a solution in each row, and criteria in each column) to compare the trade-offs between each solution. However, these criteria are notoriously difficult to define, and people resolve that problem by exercising power to decide what each term means, and whose interests should be served when they resolve trade-offs. For example, see Stone on whose needs come first, who benefits from each definition of fairness, and how technical-looking processes such as ‘cost benefit analysis’ mask political choices.

Right now, the most obvious and visible trade-off, accentuated in the UK, is between individual freedom and collective action, or the balance between state, communal, and market/ individual solutions. In comparison with many countries (and China and Italy in particular), the UK Government seems to be favouring individual action over state quarantine measures. However, most trade-offs are difficult to categorise

  1. What should be the balance between efforts to minimise the deaths of some (generally in older populations) and maximise the wellbeing of others? This is partly about human dignity during crisis, how we treat different people fairly, and the balance of freedom and coercion.
  2. How much should a government spend to keep people alive using intensive case or expensive medicines, when the money could be spent improving the lives of far more people? This is partly about human dignity, the relative efficiency of policy measures, and fairness.

If you are like me, you don’t really want to answer such questions (indeed, even writing them looks callous). If so, one way to resolve them is to elect policymakers to make such choices on our behalf (perhaps aided by experts in moral philosophy, or with access to deliberative forums). To endure, this unusually high level of deference to elected ministers requires some kind of reciprocal act:

https://twitter.com/devisridhar/status/1240648925998178304

See also: We must all do everything in our power to protect lives (UK Secretary of State for Health and Social Care)

Still, I doubt that governments are making reportable daily choices with reference to a clear and explicit view of what the trade-offs and priorities should be, because their choices are about who will die, and their ability to predict outcomes is limited.

See also: Media experts despair at Boris Johnson’s coronavirus campaign (Sonia Sodha)

Step 4 Predict the outcome of each feasible solution.

Common advice in policy analysis texts:

  • Focus on the outcomes that key actors care about (such as value for money), and quantify and visualise your predictions if possible. Compare the pros and cons of each solution, such as how much of a bad service policymakers will accept to cut costs.
  • ‘Assess the outcomes of the policy options in light of the criteria and weigh trade-offs between the advantages and disadvantages of the options’.
  • Estimate the cost of a new policy, in comparison with current policy, and in relation to factors such as savings to society or benefits to certain populations. Use your criteria and projections to compare each alternative in relation to their likely costs and benefits.
  • Explain potential solutions in sufficient detail to predict the costs and benefits of each ‘alternative’ (including current policy).
  • Short deadlines dictate that you use ‘logic and theory, rather than systematic empirical evidence’ to make predictions efficiently.
  • Monitoring is crucial because it is difficult to predict policy success, and unintended consequences are inevitable. Try to measure the outcomes of your solution, while noting that evaluations are contested.

It is difficult to envisage a way for the UK Government to publicise the thinking behind its choices (Step 3) and predictions (Step 4) in a way that would encourage effective public deliberation, rather than a highly technical debate between a small number of academics:

Further, people often call for the UK Government to publicise its expert advice and operational logic, but I am not sure how they would separate it from their normative logic, or provide a frank account without unintended consequences for public trust or anxiety. If so, government policy involves (a) to keep some choices implicit to avoid a lot of debate on trade-offs, and (b) to make general statements about choices when they do not know what their impact will be.

Step 5 Make a recommendation to your client

Common advice in policy analysis texts:

  • Examine your case through the eyes of a policymaker. Keep it simple and concise.
  • Make a preliminary recommendation to inform an iterative process, drawing feedback from clients and stakeholder groups
  • Client-oriented advisors identify the beliefs of policymakers and tailor accordingly.
  • ‘Unless your client asks you not to do so, you should explicitly recommend one policy’

I now invite you to make a recommendation (step 5) based on our discussion so far (steps 1-4). Define the problem with one framing at the expense of the others. Romanticise some people and not others. Decide how to support some people, and coerce or punish others. Prioritise the lives of some people in the knowledge that others will suffer or die. Do it despite your lack of expertise and profoundly limited knowledge and information. Learn from experts, but don’t assume that only scientific experts have relevant knowledge (decolonise; coproduce). Recommend choices that, if damaging, could take decades to fix after you’ve gone. Consider if a policymaker is willing and able to act on your advice, and if your proposed action will work as intended. Consider if a government is willing and able to bear the economic and political costs. Protect your client’s popularity, and trust in your client, at the same time as protecting lives. Consider if your advice would change if the problem would seem to change. If you are writing your analysis, maybe keep it down to one sheet of paper (and certainly far fewer words than in this post). Better you than me.

Please now watch this video before I suggest that things are not so simple.

Would that policy analysis were so simple

Imagine writing policy analysis in an imaginary world, in which there is a single powerful ‘rational’ policymaker at the heart of government, making policy via an orderly series of stages.

cycle and cycle spirograph 18.2.20

Your audience would be easy to identify at each stage, your analysis would be relatively simple, and you would not need to worry about what happens after you make a recommendation for policy change (since the selection of a solution would lead to implementation).  You could adopt a simple 5 step policy analysis method, use widely-used tools such as cost-benefit analysis to compare solutions, and know where the results would feed into the policy process.

Studies of policy analysts describe how unrealistic this expectation tends to be (Radin, Brans, Thissen).

Table for coronavirus 750

For example, there are many policymakers, analysts, influencers, and experts spread across political systems, and engaging with 101 policy problems simultaneously, which suggests that it is not even clear how everyone fits together and interacts in what we call (for the sake of simplicity) ‘the policy process’.

Instead, we can describe real world policymaking with reference to two factors.

The wider policymaking environment: 1. Limiting the use of evidence

First, policymakers face ‘bounded rationality’, in which they only have the ability to pay attention to a tiny proportion of available facts, are unable to separate those facts from their values (since we use our beliefs to evaluate the meaning of facts), struggle to make clear and consistent choices, and do not know what impact they will have. The consequences can include:

  • Limited attention, and lurches of attention. Policymakers can only pay attention to a tiny proportion of their responsibilities, and policymaking organizations struggle to process all policy-relevant information. They prioritize some issues and information and ignore the rest.
  • Power and ideas. Some ways of understanding and describing the world dominate policy debate, helping some actors and marginalizing others.
  • Beliefs and coalitions. Policymakers see the world through the lens of their beliefs. They engage in politics to turn their beliefs into policy, form coalitions with people who share them, and compete with coalitions who don’t.
  • Dealing with complexity. They engage in ‘trial-and-error strategies’ to deal with uncertain and dynamic environments (see the new section on trial-and-error- at the end).
  • Framing and narratives. Policy audiences are vulnerable to manipulation when they rely on other actors to help them understand the world. People tell simple stories to persuade their audience to see a policy problem and its solution in a particular way.
  • The social construction of populations. Policymakers draw on quick emotional judgements, and social stereotypes, to propose benefits to some target populations and punishments for others.
  • Rules and norms. Institutions are the formal rules and informal understandings that represent a way to narrow information searches efficiently to make choices quickly.
  • Learning. Policy learning is a political process in which actors engage selectively with information, not a rational search for truth.

Evidence-based or expert-informed policymaking

Put simply, policymakers cannot oversee a simple process of ‘evidence-based policymaking’. Rather, to all intents and purposes:

  1. They need to find ways to ignore most evidence so that they can focus disproportionately on some. Otherwise, they will be unable to focus well enough to make choices. The cognitive and organisational shortcuts, described above, help them do it almost instantly.
  2. They also use their experience to help them decide – often very quickly – what evidence is policy-relevant under the circumstances. Relevance can include:
  • How it relates to the policy problem as they define it (Step 1).
  • If it relates to a feasible solution (Step 2).
  • If it is timely, available, understandable, and actionable.
  • If it seems credible, such as from groups representing wider populations, or from people they trust.
  1. They use a specific shortcut: relying on expertise.

However, the vague idea of trusting or not trusting experts is a nonsense, largely because it is virtually impossible to set a clear boundary between relevant/irrelevant experts and find a huge consensus on (exactly) what is happening and what to do. Instead, in political systems, we define the policy problem or find other ways to identify the most relevant expertise and exclude other sources of knowledge.

In the UK Government’s case, it appears to be relying primarily on expertise from its own general scientific advisers, medical and public health advisers, and – perhaps more controversially – advisers on behavioural public policy.

box 7.1

Right now, it is difficult to tell exactly how and why it relies on each expert (at least when the expert is not in a clearly defined role, in which case it would be irresponsible not to consider their advice). Further, there are regular calls on Twitter for ministers to be more open about their decisions.

See also: Coronavirus: do governments ever truly listen to ‘the science’?

However, don’t underestimate the problems of identifying why we make choices, then justifying one expert or another (while avoiding pointless arguments), or prioritising one form of advice over another. Look, for example, at the kind of short-cuts that intelligent people use, which seem sensible enough, but would receive much more intense scrutiny if presented in this way by governments:

  • Sophisticated speculation by experts in a particular field, shared widely (look at the RTs), but questioned by other experts in another field:
  • Experts in one field trusting certain experts in another field based on personal or professional interaction:
  • Experts in one field not trusting a government’s approach based on its use of one (of many) sources of advice:
  • Experts representing a community of experts, criticising another expert (Prof John Ashton), for misrepresenting the amount of expert scepticism of government experts (yes, I am trying to confuse you):
  • Expert debate on how well policymakers are making policy based on expert advice
  • Finding quite-sensible ways to trust certain experts over others, such as because they can be held to account in some way (and may be relatively worried about saying any old shit on the internet):

There are many more examples in which the shortcut to expertise is fine, but not particularly better than another shortcut (and likely to include a disproportionately high number of white men with STEM backgrounds).

Update: of course, they are better than the volume trumps expertise approach:

See also:

Further, in each case, we may be receiving this expert advice via many other people, and by the time it gets to us the meaning is lost or reversed (or there is some really sophisticated expert analysis of something rumoured – not demonstrated – to be true):

For what it’s worth, I tend to favour experts who:

(a) establish the boundaries of their knowledge, (b) admit to high uncertainty about the overall problem:

(c) (in this case) make it clear that they are working on scenarios, not simple prediction

(d) examine critically the too-simple ideas that float around, such as the idea that the UK Government should emulate ‘what works’ somewhere else

(e) situate their own position (in Prof Sridhar’s case, for mass testing) within a broader debate

See also:

See also: Prof Sir John Bell (4.3.20) on why an accurate antibody test is at least one month away and these exchanges on the problems with test ‘accuracy’:

(f) use their expertise on governance to highlight problems with thoughtless criticism

However, note that most of these experts are from a very narrow social background, and from very narrow scientific fields (first in modelling, then likely in testing), despite the policy problem being largely about (a) who, and how many people, a government should try to save, and (b) how far a government should go to change behaviour to do it (Update 2.4.20: I wrote that paragraph before adding so many people to the list). It is understandable to defer in this way during a crisis, but it also contributes to a form of ‘depoliticisation’ that masks profound choices that benefit some people and leave others vulnerable to harm.

See also: COVID-19: a living systematic map of the evidence

See also: To what extent does evidence support decision making during infectious disease outbreaks? A scoping literature review

See also: Covid-19: why is the UK government ignoring WHO’s advice? (British Medical Journal editorial)

See also: Coronavirus: just 2,000 NHS frontline workers tested so far

See also: ‘What’s important is social distancing’ coronavirus testing ‘is a side issue’, says Deputy Chief Medical Officer [Professor Jonathan Van-Tam talks about the important distinction between a currently available test to see if someone has contracted the virus (an antigen test) and a forthcoming test to see if someone has had and recovered from COVID-19 (an antibody test)]. The full interview is here (please feel free to ignore the editorialising of the uploader):

See also: Why is Germany able to test for coronavirus so much more than the UK? (which is mostly a focus on Germany’s innovation and partly on the UK (Public Health England) focus on making sure its test is reliable, in the context of ‘coronavirus tests produced at great speed which have later proven to be inaccurate’ (such as one with a below-30% accuracy rate, which is worse than not testing at all). Compare with The Coronavirus Hit Germany And The UK Just Days Apart But The Countries Have Responded Differently. Here’s How and the Opinion piece ‘A public inquiry into the UK’s coronavirus response would find a litany of failures

See also: Rights and responsibilities in the Coronavirus pandemic

See also: UK police warned against ‘overreach’ in use of virus lockdown powers (although note that there is no UK police force and that Scotland has its own legal system) and Coronavirus: extra police powers risk undermining public trust (Alex Oaten and Chris Allen)

See also (Calderwood resigned as CMO that night):

See also: Social Licensing of Privacy-Encroaching Policies to Address the COVID-19 Pandemic (U.K.) (research on public opinion)

The wider policymaking environment: 2. Limited control

Second, policymakers engage in a messy and unpredictable world in which no single ‘centre’ has the power to turn a policy recommendation into an outcome. I normally use the following figure to think through the nature of a complex and unwieldy policymaking environment of which no ‘centre’ of government has full knowledge or control.

image policy process round 2 25.10.18

It helps us identify (further) the ways in which we can reject the idea that the UK Prime Minister and colleagues can fully understand and solve policy problems:

Actors. The environment contains many policymakers and influencers spread across many levels and types of government (‘venues’).

For example, consider how many key decisions that (a) have been made by organisations not in the UK central government, and (b) are more or less consistent with its advice, including:

  • Devolved governments announcing their own healthcare and public health responses (although the level of UK coordination seems more significant than the level of autonomy).
  • Public sector employers initiating or encouraging at-home working (and many Universities moving quickly from in-person to online teaching)
  • Private organisations cancelling cultural and sporting events.

Context and events. Policy solutions relate to socioeconomic context and events which can be impossible to ignore and out of the control of policymakers. The coronavirus, and its impact on so many aspects on population health and wellbeing, is an extreme example of this problem.

Networks, Institutions, and Ideas. Policymakers and influencers operate in subsystems (specialist parts of political systems). They form networks or coalitions built on the exchange of resources or facilitated by trust underpinned by shared beliefs or previous cooperation. Many different parts of government have practices driven by their own formal and informal rules. Formal rules are often written down or known widely. Informal rules are the unwritten rules, norms and practices that are difficult to understand, and may not even be understood in the same way by participants. Political actors relate their analysis to shared understandings of the world – how it is, and how it should be – which are often so established as to be taken for granted. These dominant frames of reference establish the boundaries of the political feasibility of policy solutions.  These kinds of insights suggest that most policy decisions are considered, made, and delivered in the name of – but not in the full knowledge of – government ministers.

Trial and error policymaking in complex policymaking systems (17.3.20)

There are many ways to conceptualise this policymaking environment, but few theories provide specific advice on what to do, or how to engage effectively in it. One notable exception is the general advice that comes from complexity theory, including:

  • Law-like behaviour is difficult to identify – so a policy that was successful in one context may not have the same effect in another.
  • Policymaking systems are difficult to control; policy makers should not be surprised when their policy interventions do not have the desired effect.
  • Policy makers in the UK have been too driven by the idea of order, maintaining rigid hierarchies and producing top-down, centrally driven policy strategies.  An attachment to performance indicators, to monitor and control local actors, may simply result in policy failure and demoralised policymakers.
  • Policymaking systems or their environments change quickly. Therefore, organisations must adapt quickly and not rely on a single policy strategy.

On this basis, there is a tendency in the literature to encourage the delegation of decision-making to local actors:

  1. Rely less on central government driven targets, in favour of giving local organisations more freedom to learn from their experience and adapt to their rapidly-changing environment.
  2. To deal with uncertainty and change, encourage trial-and-error projects, or pilots, that can provide lessons, or be adopted or rejected, relatively quickly.
  3. Encourage better ways to deal with alleged failure by treating ‘errors’ as sources of learning (rather than a means to punish organisations) or setting more realistic parameters for success/ failure (although see this example and this comment).
  4. Encourage a greater understanding, within the public sector, of the implications of complex systems and terms such as ‘emergence’ or ‘feedback loops’.

In other words, this literature, when applied to policymaking, tends to encourage a movement from centrally driven targets and performance indicators towards a more flexible understanding of rules and targets by local actors who are more able to understand and adapt to rapidly-changing local circumstances.

[See also: Complex systems and systems thinking]

Now, just imagine the UK Government taking that advice right now. I think it is fair to say that it would be condemned continuously (even more so than right now). Maybe that is because it is the wrong way to make policy in times of crisis. Maybe it is because too few people are willing and able to accept that the role of a small group of people at the centre of government is necessarily limited, and that effective policymaking requires trial-and-error rather than a single, fixed, grand strategy to be communicated to the public. The former highlights policy that changes with new information and perspective. The latter highlights errors of judgement, incompetence, and U-turns. In either case, the advice is changing as estimates of the coronavirus’ impact change:

I think this tension, in the way that we understand UK government, helps explain some of the criticism that it faces when changing its advice to reflect changes in its data or advice. This criticism becomes intense when people also question the competence or motives of ministers (and even people reporting the news) more generally, leading to criticism that ranges from mild to outrageous:

For me, this casual reference to a government policy to ‘cull the heard of the weak’ is outrageous, but you can find much worse on Twitter. It reflects wider debate on whether ‘herd immunity’ is or is not government policy. Much of it relates to interpretation of government statements, based on levels of trust/distrust in the UK Government, its Prime Minister and Secretaries of State, and the Prime Minister’s special adviser

However, I think that some of it is also about:

1. Wilful misinterpretation (particularly on Twitter). For example, in the early development and communication of policy, Boris Johnson was accused (in an irresponsibly misleading way) of advocating for herd immunity rather than restrictive measures.

See: Here is the transcript of what Boris Johnson said on This Morning about the new coronavirus (Full Fact)

full fact coronavirus

Below is one of the most misleading videos of its type. Look at how it cuts each segment into a narrative not provided by ministers or their advisors (see also this stinker):

See also:

2. The accentuation of a message not being emphasised by government spokespeople.

See for example this interview, 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 (and expressing sincere concerns on that basis). 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.

The same goes for Vallance’s interview on the same day (13.3.20) during Radio 4’s Today programme (transcribed by the Spectator, which calls Vallance the author, and gives it the headlineHow ‘herd immunity’ can help fight coronavirusas 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 (‘Well, I think that we will end up with a number of people getting it’).

See also: British government wants UK to acquire coronavirus ‘herd immunity’, writes Robert Peston (12.3.20) and live debates (and reports grasping at straws) on whether or not ‘herd immunity’ was the goal of the UK government:

See also: Why weren’t we ready? (Harry Lambert) which is a good exemplar of the ‘U turn’ argument, and compare with the evidence to the Health and Social Care Committee (CMO Whitty, DCMO Harries) that it describes.

A more careful forensic analysis (such as this one) will try to relate each government choice to the ways in which key advisory bodies (such as the New and Emerging Respiratory Virus Threats Advisory Group, NERVTAG) received and described evidence on the current nature of the problem:

See also: Special Report: Johnson listened to his scientists about coronavirus – but they were slow to sound the alarm (Reuters)

Some aspects may also be clearer when there is systematic qualitative interview data on which to draw. Right now, there are bits and pieces of interviews sandwiched between whopping great editorial discussions (e.g. FT Alphaville Imperial’s Neil Ferguson: “We don’t have a clear exit strategy”; compare with the more useful Let’s flatten the coronavirus confusion curve) or confused accounts by people speaking to someone who has spoken to someone else (e.g. Buzzfeed Even The US Is Doing More Coronavirus Tests Than The UK. Here Are The Reasons Why).

See also: other rabbit holes are available

[OK, that proved to be a big departure from the trial-and-error discussion. Here we are, back again]

In some cases, maybe people are making the argument that trial-and-error is the best way to respond quickly, and adapt quickly, in a crisis but that the UK Government version is not what, say, the WHO thinks of as good kind of adaptive response. It is not possible to tell, at least from the general ways in which they justify acting quickly.

See also the BBC’s provocative question (which I expect to be replaced soon):

Compare with:

The take home messages

  1. The coronavirus is an extreme example of a general situation: policymakers will always have very limited knowledge of policy problems and control over their policymaking environment. They make choices to frame problems narrowly enough to seem solvable, rule out most solutions as not feasible, make value judgements to try help some more than others, try to predict the results, and respond when the results to not match their hopes or expectations.
  2. This is not a message of doom and despair. Rather, it encourages us to think about how to influence government, and hold policymakers to account, in a thoughtful and systematic way that does not mislead the public or exacerbate the problem we are seeing.

Further reading, until I can think of a better conclusion:

This series of ‘750 words’ posts summarises key texts in policy analysis and tries to situate policy analysis in a wider political and policymaking context. Note the focus on whose knowledge counts, which is not yet a big feature of this crisis.

These series of 500 words and 1000 words posts (with podcasts) summarise concepts and theories in policy studies.

This page on evidence-based policymaking (EBPM) uses those insights to demonstrate why EBPM is  a political slogan rather than a realistic expectation.

These recorded talks relate those insights to common questions asked by researchers: why do policymakers seem to ignore my evidence, and what can I do about it? I’m happy to record more (such as on the topic you just read about) but not entirely sure who would want to hear what.

See also: Advisers, Governments and why blunders happen? (Colin Talbot)

See also: Why we might disagree about … Covid-19 (Ruth Dixon and Christopher Hood)

See also: Pandemic Science and Politics (Daniel Sarewitz)

See also: We knew this would happen. So why weren’t we ready? (Steve Bloomfield)

See also: Europe’s coronavirus lockdown measures compared (Politico)

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Filed under 750 word policy analysis, agenda setting, Evidence Based Policymaking (EBPM), Policy learning and transfer, POLU9UK, Prevention policy, Psychology Based Policy Studies, Public health, public policy, Social change, UK politics and policy