key: cord-253910-pmurx4jh
authors: Miles, David; Stedman, Mike; Heald, Adrian H
title: “Stay at Home, Protect the National Health Service, Save Lives”: a cost benefit analysis of the lockdown in the United Kingdom
date: 2020-08-13
journal: Int J Clin Pract
DOI: 10.1111/ijcp.13674
sha: 
doc_id: 253910
cord_uid: pmurx4jh

INTRODUCTION: The COVID‐19 pandemic has transformed lives across the world. In the UK, a public health driven policy of population ‘lockdown’ has had enormous personal and economic impact. METHODS: We compare UK response and outcomes with European countries of similar income and healthcare resources. We calibrate estimates of the economic costs as different % loss in Gross Domestic Product (GDP) against possible benefits of avoiding life years lost, for different scenarios where current COVID‐19 mortality and comorbidity rates were used to calculate the loss in life expectancy and adjusted for their levels of poor health and quality of life. We then apply a quality‐adjusted life years (QALY) value of £30,000 (maximum under national guidelines). RESULTS: There was a rapid spread of cases and significant variation both in severity and timing of both implementation and subsequent reductions in social restrictions. There was less variation in the trajectory of mortality rates and excess deaths, which have fallen across all countries during May/June 2020. The average age at death and life expectancy loss for non‐COVID‐19 was 79.1 and 11.4 years respectively while COVID‐19 were 80.4 and 10.1 years; including adjustments for life‐shortening comorbidities and quality of life plausibly reduces this to around 5 QALY lost for each COVID‐19 death. The lowest estimate for lockdown costs incurred was 40% higher than highest benefits from avoiding the worst mortality case scenario at full life expectancy tariff and in more realistic estimations they were over 5 times higher. Future scenarios showed in the best case a QALY value of £220k (7xNICE guideline) and in the worst‐case £3.7m (125xNICE guideline) was needed to justify the continuation of lockdown. CONCLUSION: This suggests that the costs of continuing severe restrictions are so great relative to likely benefits in lives saved that a rapid easing in restrictions is now warranted.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2),) also known as COVID-19 virus, was spreading alarmingly in early March 2020. The matter of whether the National Health Service (NHS) would be able to deal with rapidly rising numbers of seriously ill people was unclear. A group at Imperial College put the likely level of United Kingdom (UK) deaths if there was no change in behaviour at 500,000 (1). The UK government followed the example of several other European countries in with the Prime Minister announcing severe restrictions on individual movement. (2) The key message was to stay at home to protect the NHS to save lives. This was a lockdown. The precise extent to which the lockdown contributed to a subsequent slowing in the rate of new infections and deaths is not clear, though that it did so to some extent seems very likely.

As a highly infectious disease, the government response was to "Save Lives" through "Stay at Home" to reduce transmission outside the home, curtailing non-essential recreation, travel and suggesting people work from home. "Protect the NHS" reflected concern that the key services such as hospitals, especially Intensive Care Units (ICU), would have been overloaded and unable to treat the potentially large number of very ill patients and so there would have been increased mortality.

The evidence from the first 3 months suggests that most of these measures worked.

However, some quickly became less relevant.

The NHS rapidly put in place sufficient surge hospital & ICU capacity to cope with the very high level of expected demand, so service overload was no longer an immediate concern. Mateen et al (3) showed that NHS converted 2,000 normal acute beds into ICU and further 11,000 beds were coming on stream within the 5 additional Nightingale Units (there were further 1200 beds booked in private ICUs (4) ). This gave a total potential capacity of over 14,000 ICU beds. They also showed at the peak in early April 3,000 ICU

This article is protected by copyright. All rights reserved beds were being used by COVID-19 patients in the context of what turned out to be 60,000 excess deaths, i.e. 1 ICU bed to 20 excess deaths. This suggests that the 10,000 surge ICU beds gave technically sufficient ICU capacity to support a pandemic size resulting in up to 200,000 excess deaths. In the general wards, (3) showed around 12 ,000 beds were occupied by COVID-19 patients, which gave a ratio of 1 General and Acute (G&A) bed to 5 excess deaths. There were still 30,000 beds free and a further 8,000 beds in private hospitals had been booked (4); these 38,000 G&A beds gave sufficient headroom for a pandemic up to 200,000 excess deaths. The NHS through its own extreme efforts was far from being overwhelmed.

While it is clear that the cost of the lockdown has been large, the UK Finance Minister covered some of these in his summer statement (5) , just how great it is will not be known for many years. This cost -as well as the benefits of lockdowns -should be measured in terms of human welfare in the form of length and quality of lives. Such measurement is profoundly difficult. Yet measurement of the costs of restrictions needs to be weighed against the benefits of different levels of restrictions to assess what is the best policy now. We use rules that the National Institute for Clinical Excellence use to guide decisions on public health expenditure by the NHS (6) and which implicitly value years of lives saved to assess benefits of the lockdown relative to its likely cost -costs both in narrow economic terms but also in health terms.

The cost of severe restrictions plausibly rises more than in proportion to the length of a lockdown. There is some evidence that the benefits of maintaining a lockdown may be diminishing as described in Bongaerts et al (2020) (4) .

In this article, we aimed to calibrate what the costs and benefits of severe restrictions might be and what that implies about the policy that should now be followed in the UK.

Bringing together costs and benefits is necessary if good policy decision are to be made.

There is no simple way to do this that is clearly ethically justifiable, empirically reliable and widely accepted. However to make no assessment is just to make policy in a vacuum.

This article is protected by copyright. All rights reserved We selected 10 European countries with populations over five million and average income/person over £15,000/year and examine the relation between the outcomes of the excess death as reported in Human Mortality Database of the University of California (5) and the different levels of lockdown as calculated and reported as a composite measure based on nine response indicators including school closures, workplace closures, hospitality venue closures and travel bans, in the Government Response Stringency from Blavatnik School of Government, University of Oxford (6) to see if there were any clear relationships. A detailed breakdown by country is described in the Results section.

Another approach is to focus on quality-adjusted life years (QALYs) that may have been saved as a result of restrictions that have been in place in the UK up to early June and to convert that to a metric that can be compared with estimates of the cost of the restrictions. To that, we add estimates of the value of health care resources saved (both now and into the future) because lockdown reduced the numbers of sick people. That is the strategy we follow. We then go on to make estimates of costs and benefits of alternative ways forward with restrictions eased to different extents.

We make use of the guidelines established in the UK by the National Institute for Health and Care Excellence (NICE) for the use of resources in the UK health system (see NICE (2013) (7)). These are guidelines applied to resource decisions that have a direct impact on lives saved. It is hard to see how you could run a public health care system without such rules.

The benefits are measured as the number of quality life-years gained compared to the potential with different levels of lockdown. To establish these total quality life years, we examine the number of deaths directly reported and those excess deaths which were defined as the number of deaths above the average over comparable periods for recent years (10) . We examine the international situation to see if there was any relationship between level of lockdown and levels of excess deaths. We look at the ages of those that died to based on the normal ONS evaluate their life expectancy at those and then their comorbidities to establish a quality of life We add to these estimates of the saving of NHS resources from a much-reduced demand upon its resources as lockdown slowed the numbers who became seriously sick.

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To implement this, we need to assess how many likely extra years of good life might be enjoyed by the people who would have died but for a lockdown. We assume that the age and health of those who would have died are similar to that of those who have died with the virus. The ONS has been publishing each week the number of deaths where COVID-19 has been recorded as a possible cause by quinary age and gender. By applying the average life expectancy (11) to the actual recorded COVID-19 deaths by age and gender a total life expectancy years loss can be calculated. The average figure for years of life lost does not account for the fact that those who have died with COVID-19 have often been in poor health, conditional on their age. We, therefore, examine reports on their actual levels of serious comorbidities and assessed their life-shortening impact. We evaluate the quality of life they might have expected in those remaining years. We report benefits finding against both the full life expectancy loss and the quality of life adjusted loss.

The lockdown has reduced the amount of Intensive Care Unit (ICU) and General and Acute (G&A) ward costs required by the potential COVID-19 patients. We evaluate reports on the current levels of use and against the number of deaths that occurred and extrapolated to the higher numbers seen in the scenarios.

To estimate the future costs of the lockdown we consider the wider shorter and longerterm economic, social and health effects but feel they would all be reflected within the impact on Gross Domestic Product, and so take the latest measured values from the ONS and the latest estimates of future values from the Bank of England, Office of Budget Responsibility (OBR) and other experts. It seems plausible that a large fraction of these estimates of lost output is due to the lockdown. However, even without a governmentmandated lockdown there would have been some reduction in incomes so only a part of the lockdown effect is incorporated into our model Finally we apply the same methodology to evaluate the future policy over the timing and rate of easing of the lockdown.

This article is protected by copyright. All rights reserved Section 1 -Preamble: Recorded cases, deaths and excess deaths Infections rose dramatically in many European countries between February and March of 2020 and, with some lag, so did deaths attributed to the virus. Excess deaths are a more reliable measure of the overall cost in lives of the virus given the policies that were adopted for dealing with it. Figure 1 shows how a measure of excess deaths for a group of European countries with similar levels of income and health care provision to the UK. This is total deaths above the average of such deaths over the comparable months in previous years. Figure 2 shows a measure of the stringency of government restrictions introduced in European countries to counter the spread of the virus.

In late February or early March 2020, many European countries brought in severe restrictions on movement meaning that the majority of populations stayed home and numbers able to work fell dramatically. New cases of the infection and of deaths ascribed to the virus were significantly lower within a few weeks of restrictions being introduced.

Evaluation of the Economic Impact of the lockdowns by sector using the number of staff furloughed reported by Her Majesty's Revenue and Customs (HMRC) (12) as metric for the reduction in GDP (13) also shows that 60% of the loss in GDP comes from those areas of the economy (real estate, manufacturing, administration, construction, professional services, IT, energy and water, financial) that have lower interaction with vulnerable groups while only 40% come from areas that could be seen to have a higher impact with vulnerable groups (retail, accommodation & food services, arts, entertainment, transport, health and social work) suggesting broad-based lockdown may not have been the best use of resources.

For the UK the Office for Budget Responsibility (OBR) and the Bank of England estimate that GDP is likely to have fallen by between 25% and 35% in Q2 2020 and by 10-15% in 2020 relative to 2019; unemployment may rise to around 10%. The OBR central estimate, and the illustrative scenario for the Bank of England made in May 2020, is that in 2020 the UK GDP will be around 13-14% lower than in 2019. The National Institute for Economic and Social Research (in its May quarterly report) put the cumulative loss of output in the UK over 10 years at over 30% of annual GDP.

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The estimates from the Bank of England and the OBR assume that easing of restrictions after June 2020 will mean that the lockdown is then soon over; it seems plausible that their estimates of economic cost are therefore estimates of the impact of the lockdown that had been in place in the UK from March to June and not of a continuation of the lockdown into the second half of 2020 and beyond. The OBR is explicit about this; in describing their forecasts they note: "The table below summarises the results of our three-month lockdown scenario where economic activity would gradually return to normal over the subsequent three months." The Bank of England in its May economic assessment takes a similar line: "Underlying the illustrative scenario for both the UK and the rest of the world is an assumption that enforced social distancing measures remain in place until early June and that they are then lifted gradually over the following four months, until the end of Q3". In that illustrative scenario, GDP in 2020 is 14% below the 2019 level (Table 1A, Care between mid-March 2020 and the beginning of June 2020; outpatients seen were 64% down and elective admissions were 75% down (16); attended appointments in General Practice were down 35% (17). The impact of the stress of the 'Lockdown' on anyone with a pre-existing mental health condition, let alone the population as a whole, is yet to be determined. This was eloquently addressed by Kilgore et al in their recent paper (18) which described greater loneliness and elevated depression and higher suicidal ideation in those socially isolating on a standard clinical screening instrument. The observed effect sizes were large, suggesting that social isolation is likely to have a tangible and meaningful impact when considered at the population level.

Furthermore, the cost from disrupted education of children and students will be felt over a horizon of many years, even decades.

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The guidelines in the UK set out by NICE are that treatments that are expected to increase life expectancy for a patient by one year (in quality of life adjusted years, QALYs) should cost no more than £30,000 (7). We apply that figure to possible total numbers of QALYs saved by restrictions to estimate their benefit. Table 1 shows the calculation of ONS Life expectancy lost by age and gender. Average life expectancy loss comes out at 10.1 years per COVID-19 death. (The average life expectancy years lost for a non-COVID-19 death is higher at 11.4 years confirming that the age for COVID-19 mortality is slightly older than normal mortality). The median COVID-19 age at death is around 80 and the average life years lost for the older 50% is 5 years and for younger 50% is 15 years.

In their detailed study of 23,804 hospital deaths in England from COVID-19 from 1st

March 2020 to 11th May 2020, Valabhji et al (2020) (19) found that various life-shortening risk factors were significantly more prevalent in those patients who died of COVID-19 than in the general population. This included diabetes (33% vs 5%), and previous hospital admission for significant cardiovascular comorbidities including coronary heart disease (31% vs 3.5%), cerebrovascular disease (19.8% vs 1.5%) and heart failure (17.7% vs 1%).

Other comorbidities such as dementia in its various forms, chronic obstructive pulmonary disease (COPD), vitamin D deficiency, and hyperlipidaemia were not collected and compared, but it is plausible that these would also show similar levels of differences.

Each of these comorbidities has been shown to significantly increases the risk of early death. The National Diabetes Audit in their mortality study (20) found that the presence of diabetes increases a person standard mortality risk by a factor of 1.6.

This article is protected by copyright. All rights reserved It is, therefore, plausible that those patients who died of COVID-19 were, on average, already in relatively poor health for their age and this poor health would give them a life expectancy, on average, significantly below that of the age-equivalent general population.

These comorbidities and conditions also reduce the person's quality of life, as well as its quantity (21) . The impact of poor health through long-term conditions and comorbidities are usually incorporated into modelling through a quality of life utility factor which ranges from 1 (healthy) to 0 (death); this is used to adjust the total life years. Beaudet 

In the current situation, the following existing costs are associated with the current 60,000 excess deaths. The following associated hospital activity was reported  ICU: The Intensive Care National Audit and Research Centre (ICNARC report) (25) showed that 10,130 patients with COVID-19 were treated (including 72% advanced respiratory support, 30% advanced cardiovascular support, 26% renal support) for a median of 11 days, which based on reference costs of £1,503/day for a mix of 1/2/3 organ support (26) gives a total £16,500/ICU admission. From the current ratio, 1 ICU

This article is protected by copyright. All rights reserved admission is associated with 6 excess deaths, this is equivalent to £2,600 ICU costs incurred/ excess death. (19) . If 20% of ICU survivors experience these effects, there would be a total loss of 18,000 life years in the future relative to the current 60,000 excess deaths or 0.3 QALY/excess death, which if valued at @£30,000/QALY gives £9,000 QALY value lost /excess death.

Together these would bring approximately £20,000 healthcare benefits for each excess death avoided through the lockdown.

The benefit in terms of estimated lives saved Suppose that a group of people who each had expected quality-adjusted remaining years of life of 5 years, and who might have died with the virus, has been spared that because of government restrictions ("the lockdown"). We will assume that the benefit of the restrictions that prevented such deaths are the value of 5 quality-adjusted years of life multiplied by the number of lives saved. The NICE £30,000 threshold is an assessment of the (maximum) resource cost that would be justified for the UK health service to make an

This article is protected by copyright. All rights reserved expected saving of one quality-adjusted year of life. To save 5 QALY would be worth up to £150,000.

We apply this figure of £150,000 (or a figure of £300,000 if we make no adjustment for co-morbidities and take 10 life years lost per death) to estimates of the possible number of lives saved as a result of lockdowns to give an overall benefit number. To that, we add an estimate of £20,000 other health costs saved (per life saved) based on the evidence summarised above. We compare that aggregate number with an estimate of the lost resources from the lockdown. The Hospitalised Fatality Rate (30) has fallen from 6%/day at the start of April to 1.5% in mid-June. So, the estimate of 500,000 deaths made back in March and based upon fatality rates then may have been particularly pessimistic.

This article is protected by copyright. All rights reserved At the other end of the spectrum would be estimates of net saved lives that are effectively zero. We set the lowest estimated net set lives well above that and use (rather arbitrarily) a "lowest" estimate of 20,000.

For each life saved we apply a factor of either 5 or 10 quality-adjusted extra years of life, each valued with the NICE guideline figure of £30,000 (7). We also factor in that alongside fewer deaths there would have been far fewer demands made upon the resources of the public health system and we have placed a value of that per potential life saved of £20,000.

On the cost side the lowest resources cost is just to count the GDP that would have been produced in 2020 but for the lockdown established in March and assuming the lockdown to be eased from the end of June. This assumes a rapid bounce back by the end of the year so there is no effect on incomes and output from the start of 2021 onwards. That was the scenario envisaged by the Bank of England in their May 2020 assessment of the economic outlook when they put the GDP loss in 2020 at around 14%. The OBR estimate for lost output in 2020, also based on an assumed rapid recovery in the second half of the year, is close to 13%. It seems plausible that a large fraction of these estimates of lost output is due to the lockdown. But even absent a government-mandated lockdown there would have been some reduction in incomes. If the lockdown effect was only twothirds of the total, then the Bank of England and OBR estimates might imply around a 9% fall in GDP as a result of it.

At the high end of the spectrum would be an estimate of 15% of GDP lost in 2020 and lower output for the next few years on top of that as economic activity does not return to normal for several years with some firms permanently damaged by the lockdown and the large rise in unemployment slow to be reversed, even if restrictions are quickly removed from mid-2020. A shortfall of GDP of 15% in 2020; 7.5% in 2021 and 2.5% in 2022 (so that the cumulative lost output would then be 25% of GDP). That would be at the more 

This article is protected by copyright. All rights reserved as noted the National Institute of Economic and Social research put their best guess of the narrowly defined economic cost higher again. Tables 2 and 3 show the cost-benefit calculations of the lockdown based on such ranges:

In each cell, we report three numbers: benefits (+), costs (-) and (in red) the balance of the two -all measured as £ billion. Tables 2 and 3 (with benefits raised by a factor of 3) this would still generate costs of the lockdown in excess of benefits in nearly all the cases considered.

That judgement is, however, made with the benefit of hindsight: we now know more about the scale of the economic costs of the lockdown than was known in March, and also know about how deaths and new infections have evolved across Europe. The more interesting policy issue is what it is best to do now: how quickly should the lockdown be eased given what we know now? That issue we consider in the next section.

We apply a similar cost-benefit methodology to consider policy options for the level of restrictions applied in the UK over the next 3 months (July-September 2020). The options we consider fall under two broad headings:

This article is protected by copyright. All rights reserved 2. Move quickly to minimal lockdown (easing restrictions rapidly and relying on existing tracking of the cases/deaths to prevent re-emergence of the virus)

We consider the following scenarios for the consequences of each policy for the evolution of COVID-19 deaths:

1. Very limited easing of restrictions results in a continuing steady fall in the death rate over 13 weeks down to single figures per week at the end of three months. Each week deaths are assumed to be 0.7 x deaths of the previous week. each week they are 15% higher than the week before.

The assumed paths of deaths under the 4 scenarios are shown in Table 4 . In each case, we set the initial level of deaths in the week prior to each scenario at the last ONS Our low-end estimate of the (narrowly defined) cost of the March to early June lockdown was 9% of GDP -a figure of a little over £200 billion. One might assume that a continuation of the lockdown over the next three months with only a very limited easing of restrictions generates a further cost of the same size. But the rapid easing of restrictions is unlikely to generate zero costs. Such costs may still be substantial, though likely far lower than a continuation of lockdown policies. A conservative estimate of the benefits of easing the lockdown is that the £200 billion costs under lockdown might be half that size.

This article is protected by copyright. All rights reserved This would generate a benefit from easing of £100 billion over three months to be set against any extra lives lost.

Under all scenarios the cost of easing is a small fraction of the benefits -the maximum cost of £14 billion should be set against a conservative estimate of benefits of £100 billion. One would need to value QALYs at £220,000 -over 7 times the NICE guideline value of £30,000 to make a continuation of the lockdown warranted in the scenario of the greatest number of live years not lost with costs / QALY much higher for less live years saved. That runs counter to agreed UK policy on the economic viability of health interventions (7). 

It is not straightforward to assess exactly how much of the slowing in new infections and deaths is directly attributable to the lockdown. People were altering their behaviour before severe restrictions were introduced -mobile phone data reveals sharp declines in the movement of people some weeks ahead of lockdown. Some changes in behaviour (washing hands, avoiding crowds) may have been effective in reducing infections but at a low economic cost.

It is also possible that a significant degree of immunity may have built up by the time severe restrictions were introduced because the infection may have spread quite widely and largely unnoticed with the asymptomatic a very large fraction of the infected.

A substantial proportion of the population may have been effectively immune from the virus when lockdowns started not just because of recovery from past infections that conferred a degree of immunity but also because a significant proportion of the

This article is protected by copyright. All rights reserved population may never have been susceptible. In this regard at least two studies reported possible immunity against SARS-CoV-2 due to previous infections with harmless Coronaviruses. Braun et al (33) showed the presence of SARS-CoV-2 reactive T cells in COVID-19 healthy donors and Grifoni et al (34) reported the detection of SARS-CoV-2reactive CD4+ T cells in ∼40%-60% of unexposed individuals, suggesting cross-reactive T cell recognition between circulating "common cold" coronaviruses and SARS-CoV-2

All three factors described above may have played a role, and all would mean that Wieland (2020) (38) modelled the spread of the infection across Germany and concluded that infections were past their peak and starting to decline ahead of the introduction of government restrictions there. The results were summarised thus: "In a large majority of German counties, the epidemic curve has flattened before the social ban was established (March 23). In a minority of counties, the peak was already exceeded before school closures." Friston (39) and Levitt (40) both conclude that the numbers of people not susceptible to the COVID-19 virus were already very substantial before lockdowns were introduced and that the virus was burning itself out.

This article is protected by copyright. All rights reserved Testing based on the presence of antibodies, however, put the level of those who have had the infection in European countries where the virus has spread most rapidly at only 5-10%, though in some areas within countries it is still high enough to have had a significant impact on the R-value, which is the number of people subsequently infected by each infected person. Antibody testing itself is not a perfect tool and additional research is needed to determine if and to what extent a positive antibody test means a person may be protected from reinfection with SARS-CoV-2. Serology tests should not be used as a stand-alone tool to make decisions about personal safety related to SARS-CoV-2 exposure, Lerner et al (41).

In contrast to many other European countries, the Swedish strategy has been one of adopting much less restrictive measures that is far short of a lockdown (see Figure 2 ).

Infections and deaths have been far higher than in neighbouring Denmark and Norway, but excess deaths are lower than in many European countries and only one third the level (relative to population) in the UK. In terms of overall impacts, there is contradictory evidence. Born et al (2020) (42) and Krueger, Uhlig and Xie (2020) (43) argue that the Swedish strategy has been successful. But health outcomes in countries most similar in terms of climate, the density of population and standard of living (that is Denmark and Norway) appear to be much better.

The UK data show a significantly higher cumulative death rate than Sweden; Figure 1 and (44) show excess deaths relative to expected in the UK at more than twice the Swedish level by early June 2020. On this measure, Sweden sits near the middle of the pack for European countries. Death rates in several countries with harder "lockdowns" have been significantly higher than in Sweden.

A great deal of evidence is already emerging on the (narrow) economic impacts of restrictions. Estimates made by Deb et al (2020) (45) to identify the particular effect of restrictive policies (lockdown) suggest that they reduced economic activity by 15% in the 30 days after they were adopted. They find that stay-at-home requirements and workplace closures are the costliest in economic terms. Preliminary estimates from the

This article is protected by copyright. All rights reserved UK Office for National Statistics showed a slightly more than 20% fall in GDP in April 2020, the first full month after the lockdown. Bonadio et al (2020) (46) put the impact on output and incomes (i.e. GDP) of policies to counter the spread of the infection on GDP averaged across 64 countries even higher, at around 30%. Costs which will come further down the road because of disruption to healthcare (47) and education are harder again (48) to measure relative to the more immediate effects on economic production and employment (49) .

The lockdown can be seen as having 2 elements: a social lockdown (distancing, no social gathering, recreation or sports events etc) and an employment lockdown (not travelling or going to non-essential work). The latter is not likely to be the most effective response as infection amongst the employed was not a major source of mortality. Linking the total population by age group with employment (50) (52) showed that the infection rate amongst employed age group (20-49) was 70% higher than the stay at home age groups, and combining this with the population by age group shows 51% of all infections and 1% of deaths were recorded within this age group.

In the UK it is hard to be sure of the scale of benefits of the lockdown in terms of lives saved and the avoidance of the resources of the health service being exhausted. In terms of lives saved estimates range from very few lives saved to a high of perhaps 450,000 lives saved (that is the difference between the 500,000 or so deaths projected by There are reasons to be sceptical of figures at the high end of that scale which puts the saving of lives from the lockdown at several hundreds of thousands:

 the low cost of effective forms of behavioural change (washing hands, avoiding crowds) adopted by individuals makes it unlikely that in the UK there would have seen

This article is protected by copyright. All rights reserved 500,000 deaths even with no government restrictions; the 500,000 figure from The benefits of a lockdown are, however, not just in terms of lives saved -though that is of immense value. Valuing the health care resources saved because the lockdown reduced the numbers of sick people is also an important element of its benefits.

This article is protected by copyright. All rights reserved There is a need to normalise how we view COVID-19 because its costs and risks are comparable to other health problems (such as cancer, heart problems, diabetes) where governments have made resource decisions for decades. Treating possible future COVID-19 deaths as if nothing else matters is going to lead to bad outcomes. Good decision making does not mean paying little attention to the collateral damage that comes from responding to a worst-case COVID-19 scenario.

The lockdown is a public health policy and we have valued its impact using the tools that guide health care decision in the UK public health system. On that basis and taking a wide range of scenarios of costs and benefits of severe restrictions, we find the lockdown has consistently generated costs that are greater -and often dramatically greater -than possible benefits. Movement away from blanket restrictions that bring large, lasting and widespread costs and towards measures targeted specifically at groups most at risk offers is now prudent.

Such a policy has now been implemented.

Ethics approval and consent to participate: The analysis used nationally available general practice-level data with no patient identifiable data. Therefore, we felt that Ethics Permission was not required. 

This article is protected by copyright. All rights reserved Funding: No external funding was accessed to fund the work 

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