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.
- 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).
- 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.
Step 1 Define the problem
- 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:
- Do not enjoy the same confidence that they know what is happening, or that their actions will have their intended consequences, and
- Will think twice about trying to regulate social behaviour under those circumstances, especially when they
- 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.
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:
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
- A lot of the spread will happen inside homes, where the role of government is minimal (compared to public places). So, for example, the impact of school closures could be good (isolation) or make things worse (children spreading the virus to vulnerable relatives) (see also ‘we don’t know [if the UKG decision not to close schools] was brilliant or catastrophic’). [Update 18.3.20: as it turned out, the First Minister’s argument for closing Scottish schools was that there were too few teachers available).
See also: Coronavirus: Government expert defends not closing UK schools (BBC, Sir Patrick Vallance 13th March 2020)
- 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:
- 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.
- 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) …
… while the UK Government’s Deputy Chief Medical Officer also seems to be describing (b):
- 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’).
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:
- 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)
- 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).
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)
- 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?
- A need for more communication and exhortation, or for direct action to change behaviour.
- The short term (do everything possible now) or long term (manage behaviour over many months).
- 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.
- 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):
- For example, note how often people are second guessing and criticising the UK Government position (and questioning the motives of Conservative ministers).
- 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
- 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:
- Public expenditure (e.g. to boost spending for emergency care, crisis services, medical equipment)
- Economic incentives and disincentives (e.g. to reduce the cost of business or borrowing, or tax unhealthy products)
- Linking spending to entitlement or behaviour (e.g. social security benefits conditional on working or seeking work, perhaps with the rules modified during crises)
- Formal regulations versus voluntary agreements (e.g. making organisations close, or encouraging them to close)
- Public services: universal or targeted, free or with charges, delivered directly or via non-governmental organisations
- Legal sanctions (e.g. criminalising reckless behaviour)
- Public education or advertising (e.g. as paid adverts or via media and social media)
- Funding scientific research, and organisations to advise on policy
- Establishing or reforming policymaking units or departments
- 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:
- 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.
- 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.
Step 3 Use value-based criteria and political goals to compare solutions
- 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
- 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.
- 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:
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.
- 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
- 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.
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.
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:
- 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.
- 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.
- 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.
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.
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):
- Keeping lists of people who seem to know what they are talking about (or reporting lists of people who sign a letter)
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:
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: 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: why is the UK government ignoring WHO’s advice? (British Medical Journal editorial)
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: 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.
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:
- 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.
- To deal with uncertainty and change, encourage trial-and-error projects, or pilots, that can provide lessons, or be adopted or rejected, relatively quickly.
- 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).
- 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.
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):
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 headline “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 (‘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:
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):
The take home messages
- 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.
- 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.
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)