The WHO calls the virus SARS-CoV-2 and the disease Covid-19. The virus would be genetically very much like the original SARS-CoV from 2003, with many similar properties like the effect on age and sex, also on superspreading events (“clusters”), which explains the success of source and contract tracing in Japan. Molecular biologist Peter Borger argues that we are basically dealing with the same virus but a bit less deadly (as happens over time), and he wonders why the world did not prepare for its remergence and why it was claimed that the virus would be “new” and “unknown” – though admittedly the outbreak of 2003 did not reach the West.

Let us discuss:

  • Parliament goes into recess and takes a two-month vacation till the end of August
  • European recovery funds
  • Where we are now
  • The exit strategy
  • How did we get into the emergency brake of the lockdown ?
  • The medical world and litigation
  • The failure of the Dutch source and contact tracing (SCT)
  • What are major unknowns ?
  • Repair of national trust

Parliament goes into recess, but inadvisably so

The government has asked the Dutch Safety Board, chaired by Jeroen Dijsselbloem, to evaluate how Holland responded to the SARS-CoV-2 pandemic.

“With the investigation the Board will look at the preparations for a pandemic, crisis management, the measures taken and the phasing out of these measures. The Safety Board will also look at the effects of the corona crisis on the safety of vulnerable people in the society, for example due to discontinuation of regular care or social services. Medical treatments and economic support measures fall outside of the scope of the investigation. The goal of the investigation is to draw lessons for potential future epidemics.”

Since this report may be expected somewhere in 2021, Dutch parliament arranged, though not without some struggle, that another report will be available before September 1. Satisfied with the job done, Dutch parliament apparently intends to have the recess July 3 – August 31.

This attitude by Dutch parliament is flabbergasting.

The situation is not in control, national trust is corroding, the lack of information still is huge, the financial loss to families is large, and the risks of coming Fall and Winter are huge: with reduced buffers, while the economy is in recession and people fear bankruptcies and unemployment.

For a sense of perspective, the Winter 2017-2018 flu took 9500 excess deaths, see my earlier discussion, so that the figure of 9000 excess deaths in 2020 should not be dramatised. However, the basic facts remain: (1) SARS-CoV-2 can be deadlier than the flu, (2) the virus can also be nasty for younger healthier persons, and thus might better be eradicated, (3) the risk of a 2nd wave has not been avoided yet, (4) the economy must somehow recover with these unknowns.

Parliament should not rest till it has provided clarity about the following.

  • The government still hasn’t formulated an exit strategy other than muddling through, and RIVM still leans on notions of herd immunity that conflict with the containment / suppression / eradication. There is need for a clear choice.
  • There is not only RIVM that looks at the infection dynamics but there is also Zorginstituut Nederland (comparable to the US NIH), that advises on cost-effectiveness of health care, and that ought to advise on the (quality adjusted) “life years” (qaly). Are the infected adequately monitored (given the nastiness of the virus) ? The ZiN agenda on Covid-19 however is rather timid. The blogs by its advisory council are more informative. Advisable is the blog by Hugo Keuzenkamp, former editor of economics journal ESB and former hospital director. There seem to be more questions than ZiN can answer, and how has it been arranged e.g. within Europe that this capacity to answer questions is best allocated ?
  • Without such clarity on strategy, the European discussion is vague too. You cannot bargain for a result when you do not know what you are bargaining for. The next EU council is planned for July 17.
  • The lack of information still is huge, not only because of lack of research funds, but also because key agents like RIVM and ZiN do not provide the information that they have. They might be overworked on what they are doing but what they are doing may also be misguided. When parliament thinks that such information will be available in that new report of September 1, then this is ostrich behaviour, and it may well be that parliament isn’t even aware of what questions must be asked. RIVM indeed applied the emergency brake in March so that the death toll was restricted to 9000 instead of 250,000 (see below), and it must be greatly appreciated that they eventually did so, but this does not imply that they know what they are doing overall, see below. To make sure that answers are given, parliament must ask questions itself, and provide a bridge for questions coming from science and society.
  • If there would be this new report by September 1 then this information can indeed be used for the discussion about the national budget for 2021, but this is too late for the Fall of 2020. Preparations must be made in July – August already.
    • For example, the scientific evidence on aerosol transmission is overwhelming, but OMT / RIVM seem to be mentally blocked by the linguistic distinction between “infectious” (the capacity to infect) and “having infected” (having performed the actual deed), see this deconstruction. We are now on a path to lose the Summer months for adaptation of ventilation systems. (Admitting that “ventilation has a role” opens the can of worms that it is not clear for each ventilation system when and how. But it is better to specify this uncertainty than deny the causal influence.)
    • The theory of infections contains a notion of “herd immunity”. If a population is not mixed – say the strong animals form a protective circle around the vulnerables – then predators may die from hunger before they can do any harm. If a population is mixed, then a predator may still die when the chance of meeting a strong animal is much larger than meeting a vulnerable one. In general, when you do not specify what model you are using then you are at risk of (spreading) confusion. This is a major problem in the current discussion about SARS-CoV-2. My paper on redesign of didactics, section 1.5.5 on page 26, questions what RIVM (the Dutch CDC) has stated about the virus, and section 6.11 on page 105 has a longer discussion of the theory. For SARS-CoV-2, RIVM has stated that herd immunity would be at 60% of infected people in the population. As far as I know, and please correct me if I am wrong, RIVM hasn’t explicitly stated how they arrived at this figure. RIVM stated that they intended to protect the vulnerables (eldery and younger with comorbidity) but many deaths actually occurred in homes for the elderly. And if you lock down the economy so that R0 becomes much lower, how do you intend to achieve that herd immunity ? RIVM has been so ambiguous and inconsistent on this issue that tough questioning is required to arrive at clarity about what the Dutch policy approach is.
  • What institutional structure would you want to have, such that there is adequate and transparant planning with not only “lives saved” (lives extended) but also (quality adjusted) “life years gained” – or the compromise of the “unit square root” – and with the distinction between statistical data collection for the past and planning for the future ?
  • Most of all: apparently there still is too little awareness that the pandemic has been caused by policies that are environmentally unsustainable. It is scientifically obvious that current policies are inconsistent on economics and climate change, see here. It is absurd that Dutch parliament hasn’t made such statement yet. Europe is already moving into this direction but let this be a key cornerstone of the discussion of July 17 and let Holland support this. Impose a carbon tax. For investments, companies require as much certainty as can be provided.
    • The proposed support of about EUR 3.4 bn for Air France / KLM is a case in point. The government argues that the company and Schiphol are important for some 100,000 jobs, but the government does not state that this employment is fundamentally at odds with the goal on environmental sustainability.  The government states that CO2 emissions per passenger must be reduced “by 50% in 2030 compared to 2005” – which causes the question why 2005 ? – but why not target a level of 5% of passengers for 2021+ anyhow ? Why not acknowledge that tourism in distant countries is not environmentally sustainable with our present world population and technology ?
    • For the Fall and Winter on the Northern hemisphere, my suggestion is that unemployment, also for the transition to environmental sustainability, is avoided by allowing and encouraging people to get more education. One day per week education for the work force would mean a 20% reduction of the labour force, with time mostly spent studying at home. The scheme could be financed by a general tax also on wealth, replacing such capital by human capital. Pay for the educational day would be at 70% of normal pay, with a minimum of the net legal minimum wage and a maximum at half the prime minister’s salary, with regular testing and check-up, and ending of participation if not studying. I take my inspiration for this scheme from the late Louis Emmerij (1934-2019). If one would agree with this kind of idea, then it obviously requires preparation for the educational system to make this possible.

European recovery funds

There is a disastrous economic imbalance between on one side Germany and Holland and on the other side Southern Europe. The world is advised to boycott Holland till the censorship of economic science in Holland since 1990 is resolved. It might seem as if every crisis is another excuse to ride one’s hobby horses, but my hobby horses are fundamental issues that apparently must be emphasized again and again.

The loss of lives and livelihoods because of SARS-CoV-2 causes sorrow all over Europe. There are expressions of compassion and solidarity all over.

On SARS-CoV-2, the distinction between North and South was broken by Greece in the South (doing well) and Sweden in the North (doing worse). Diversity of nations gives a great reward in information.

While Greece responded immediately and adequately to the virus with source and contact tracing (SCT), with now 191 deaths (18 per million) (not counting “other excess mortality”) apparently the systems of health in Italy and Spain suffer from similar problems as the Dutch system does, and these problems could be resolved nationally, without the need for European supervision. It is only in the areas of economies of scale and scope, of deliberate interdependence by trade and monetary union, and the overall impact on the environment, that the European Union has relevance. With the historical process towards closer co-operation, there is also the awareness for common justice and civil liberties and the defense of the borders of the larger region. (It must also be remarked that Brexit has basically been caused by a non-proportional electoral system, and scientific failure of “political science” still locked in the humanities, see my proposal of a buddy system of physicists and such “political scientists”.)

Italy and Spain have pointed to their problematic state finances and heavy death tolls: Italy 34.7 thousand (574 per million) and Spain 28.3 thousand (606 per million) (not counting other excess mortality) (compared to Holland 356 per million).

Italy and Spain can raise taxes on their own rich, who are much better off than the average German or Dutch.

Nations like Italy with 60 million people and Spain with 47 million people, with their proud histories and highly developed governments and often excellent universities, really do not need Europe to help out. When politicians in Southern Europe use the European Union and Northern Europe as scapegoats to distract attention from their own failure to properly manage their own economies and systems of health care, then this is better said clearly, so that voters in Southern Europe are advised not to vote for such politicians. (There is a distinction between scapegoating Holland and boycotting it for said specific reason.)

By mid April, the Italian debt / GDP ratio was expected to rise by 20% to 156% (IMF table 1.2). Italy and Spain were also earlier in the pandemic and the Dutch death toll hadn’t fully materialised yet. The Italian proposal was to have Eurobonds, so that country-specific rates of interest would not be hit by stigma as happened during the financial crisis of 2007+. I myself had agreed, for that particular crisis in this period, that such bonds might be used temporarily indeed, obviously with conditions.

The Italian prime minister Giuseppe Conte must have known that relaunching the proposal of eurobonds is a slap in the face of Northern Europe. He decided to slap anyway. This attitude is unhelpful and anti-European.

The Dutch finance minister Wopke Hoekstra rejected the proposal of eurobonds and pointed to the national responsibility to adhere to the targets of the Maastricht Treaty, with a debt / GDP ratio of at most 60%. Southern Europe hadn’t done enough in the years since the financial crisis and was accountable for its own errors. This rejection caused anger in Southern Europe and Hoekstra apologised for not having been emphatic enough in this particular statement, and for not expressing enough his compassion for the plight in Southern Europe.

As said, it is problematic to discuss European funds when there is no clarity on the common exit strategy and embedding within the discussion on climate change and the environment overall. I regard it as valid that the ECB and the EU stepped in with emergency plans to keep the economies afloat but it would also be a grave error when the structural imbalances are not tackled, when censorship of science is allowed, when there is no clarity on environmental sustainability, and when Southern Europe does not deal with its financial elites too.

Where we are now

Holland has 17.4 million inhabitants, of which 0.65 million showed antibodies for SARS-CoV-2, a prevalence of 3.7%. The total death score in Holland today is about 9000, of which some 6000 have been officially tested (356 per million) and some 3000 are “other excess mortality” including non-SARS-CoV-2 deaths in unknown proportion. A raw estimate, also given by RIVM (the Dutch CDC), is that the infection fatality factor (IFF) is 9000 / 650,000 = 1.38%. The IFF for 60+ is 4.84% and for <60 it is 0.06%.

  • The SARS-CoV-2 pandemic landed in Holland in apparently some four genetic variants with people returning from ski holidays and from Northern Italy, around Valentine’s day (February 14) or Carnival (February 23) (my guess at a super-spreader-event).
  • The Dutch lockdown started in steps on March 11 and can be taken as effective on March 18 (day 24 since Carnival). It may be mentioned that the virus likely came via Italy but also that scenes in Italian hospitals had an influence on the Dutch decision on a lockdown.
  • The Dutch death count per day reached its top around April 5, six weeks after Carnival.
  • Today we are some 17 weeks after Carnival with hardly any recorded deaths and excess mortality.
  • All-cause mortality is annually some 150,000 persons on average anyway. We may be speaking about 1% loss of life expectancy, but the risk of the virus of course is that it may still explode to the level of 250,000 (see below) additional deaths.
  • For climate change, the 2020-2030 decade still is crucial, and the world is in dire need of policies that work, see here.

Addendum July 5 2020: The figure of 250,000 deaths derives from a didactic scenario with R0 = 4 and an IFF of 1.5%. The figure assumes that Rt = R0 = 4 whatever happens. It is not claimed that this is a realistic scenario though I am inclined to think that it might be close to a worst case scenario. The point is that a realistic scenario has endogenous reactions, with people noticing the epidemic and reducing contacts themselves before the government steps in with additional measures. With endogenous reactions, perhaps the death toll might be a factor 10 less, thus 25,000, so that the effect of government measures is only the last 1/3 to 9000. The issue of what would be realistic scenario’s forms part of the huge unknowns in this discussion.

In the former weblog entry, I discussed: (i) my change of viewpoint towards containment / suppression / eradication, and current rejection of the scenario of using the virus as its own vaccine while shielding the vulnerables, (ii) a redesign of didactics of some epidemiological models, (iii) the abuse of the notion of “herd immunity” in much discussion about the virus. (Recommended reading is Pueyo.)

The new Dutch government “dashboard” gives a daily or weekly figure and doesn’t allow you to trace the history or look at a forecast yet. RIVM has always declined to make projections about mortality and loss in (quality adjusted) life years. RIVM neither states the economic cost of the policy. The dashboard states that it is being developed, and perhaps we may hope for such crucial information in the future. Today the estimate is that there would be 1715 infected persons. It is remarkable that so few people can threaten the entire EUR 800 bn Dutch economy. (It is not clear to me how this number has been estimated, and if tests have been used how the false positives have been accounted for.) The key problem is the asymptomatic transmission, because most people with symptoms would tend to see their social duty of self-quarantine. This week, the 5-day Rt would be 1.05 which roughly means that over 5 days there could be 1715 * 1.05 infected persons. The infection fatality factor (IFF) of 1.38% over February-June indicates that 24 of these people could die. Perhaps a point of reference are the 661 / 52 = 12.7 weekly deaths in traffic accidents. However, many deaths occurred in care-homes, and perhaps the country has now learned to better protect the vulnerables. If those 1715 people would be only healthy <60 with an IFF of 0.06%  then there would be 1 death. The dashboard doesn’t give the age distribution of the estimated 1715 infected persons. Presumably these are like the population age distribution but this is dubious. This means that the “dashboard” doesn’t give us the crucial information about what these figures actually mean. The government has been working on the SARS-CoV-2 issue since January and they still do not grasp what relevant information is. It is not so that the crucial information isn’t there, but they simply do not collect or present it. Somehow the world of medicine and epidemiology are still at a far distance from the world of public health (economics and statistics). (See also the Appendix, example 6 on the “dashboard”.)

The exit strategy

The following could also have been discussed and settled in January / February, with the information available then (and the R0 estimated back then at 2.7). See the articles that had been published in The Lancet in January. RIVM failed in its task of protecting the country from the epidemic. See the next section with some causes why it wasn’t settled back then.

In all exit strategies, there is (i) research for vaccines, tests and treatment, and (ii) while such do not exist yet, society better is segmented, and the vulnerable section of society (currently the 60+ aged and those with comorbidity) would be shielded by a “quarantine border” of test, test, and test of source and contact tracing (SCT). The only issue is what to do with the less vulnerables.

  1. Containment, and at best eradication. The age <60 healthy population is less likely to suffer an infection, but when they do have an infection then the virus may have nasty properties. This suggests that eradication is a better strategy. Thus, test, test, and test, with source and contact tracing (SCT) and quarantine of those who have been in contact with someone infected (or suspected of being infected). Eradication is only feasible if the WHO establishes the virus as unacceptable indeed, with international agreement. My preference has shifted to this scenario, see Tabarrok (2020). It is urgent that the Dutch ZiN provides clarity about the burden of disease and the qaly corrections.
  2. Mitigation. The virus can be used as its own vaccine. See here how this could be done in Holland. Since even the less vulnerables might still appear to be vulnerable after all, we need to reserve ICU capacity. Also, shielding of the vulnerables might not be perfect, and there still may be quarantine breaches with some transmissions. Since a vaccine may take a while, or might not work well for this part of society, many vulnerables might prefer to move to gated communities or larger protected areas, with specialisation of hospitals and such to particular service areas. With proper management, the number of deaths and life-years lost would be comparable to other diseases. (De Vlas & Coffeng (2020), Van Bunnik et al. (2020), Colignatus (2020 – April 5), Eichenberger et al. (2020).)
  3. Muddling through and lock on-off. This assumes that the above two options are not feasible, or society doesn’t make a decision, and we muddle through, a bit as we have been doing. This would be the “Harvard study”, Kissler et al. (2020), but they do not elaborate on the effect on the economy, as RIVM hasn’t done either. Overall, the WHO commission on macro-economics and health (CMH) is underdeveloped, even though it is a key chapter for public health (economics).

How did we get into the emergency brake of the lockdown ?

The choice between containment (eradication) or mitigation could already have been made in Holland in early February, with the information available from China.

There is the WHO PHEIC of January 30, the article by Wu et al. (2020) in The Lancet January 31, and the WHO research roadmap of February 12. We ought to assume that the epidemiologists know about pandemics. They ought to be able to inform their medical colleagues, public health authorities and policy makers about the risks of a pandemic.

Dutch microbiologist and former president of the Dutch federation of associations for research in medicine, John Jacobs, states that the Dutch agencies were lost in a well-mapped world (Dutch).

Example countries who chose for containment are Taiwan and South Korea, and in Europe there is Greece (though I did not see excess  mortality yet). Sweden adopted mitigation with the deliberate build-up of herd immunity, and later admitted to having misjudged the protection of the vulnerables in care homes.

In Holland, RIVM (the Dutch CDC), supported by the advisory council called “Outbreak Management Team” (OTM) from the medical world and universities, on January 27 advised the minister of health to declare the virus as a risk of category A, meaning that mandatory quarantine was possible. However, RIVM still underestimated the problem so that the month of February was lost, see the convention on the virus at the Dutch Academy of Sciences (KNAW) on February 21. Even virologist Marion Koopmans (Erasmus MC), who has been warning for some years about the risk of a pandemic, now (interview June 19) acknowledges that she underestimated the asymptomatic transmission of the virus, even while it had been reported. However, the Dutch system of source and contact tracing (SCT) failed more structurally,  see below.

In March, the government and RIVM applied the emergency brake of the national lockdown. The cost of the delay was 9000 deaths and economic disaster, but the emergency brake prevented some 240,000 deaths and other economic fall-out. At least Holland is not like the USA or Brazil. (PM. Also for comparing hospital data, it is important to recall that the USA has a different system, and that not all infected persons have the option to go to the hospital. Perhaps the notion of universal health care might make more sense to Americans now ?)

PM. Richard Horton, editor of The Lancet, regards the UK handling of the issue as catastrophic:

“Individually, they’re great people, but the system was a catastrophic failure.”

In a review of Horton’s book, reviewer Mark Honigsbaum, with a background in politics, philosophy and economics at Oxford and a PhD on the history of influenza (cv), makes a very strange comment:

“Horton is on firmer ground when he points out that by the end of January, the Lancet had published five papers setting out the risks of a global pandemic and how Sars-CoV-2 could be controlled using track-and-trace measures successfully employed during the first Sars outbreak in 2003. However, given the confusing data coming out of China in January, it is an exaggeration to say that the WHO’s declaration of an international public health emergency on 30 January was the “wake-up call” the world needed, especially as the WHO did not recommend travel bans and waited until 12 March to declare a pandemic.”

This is very strange since:

  1. The PHEIC is by definition the wake up call, that announces the risk that there can be a pandemic. By definition it differs from the observation that there is a pandemic.
  2. Honigsbaum does not extend on what would be “confusing” about the articles published in The Lancet (having passed some peer review as opposed to media reports). (Let me again refer Dutch readers to the review by Jacobs that Holland got lost in a well-mapped world.)
  3. Overall this review is misrepresenting and sloppy, and uses a gimmick to seem “balanced and unbiased” (as is expected from a review). Honigsbaum is advised to retract this or his thesis.

The medical world and litigation

Remarkably, the medical world will not use the virus as its own vaccine, but they will allow the virus to spread “by itself”, so that “herd immunity” can be built up.

Think about this for a while. You reject the responsibility of creating and monitoring driver’s licenses but will allow that people simply start driving and learn it the hard way. How much sense does this make to you ?

It must be an issue of legal responsibility. A vaccinator apparently might be sued for malpractice but cannot be held accountable when looking away. The “Harvard study” (Kissler et al. (2020) in Science) mentions the process towards “herd immunity”: those infected get a fair chance at the ICU, even though 30-50% of the vulnerables would die at the ICU. It is your own responsibility, or a “natural phenomenon” when you get infected.

It is scientifically sound of course when mathematical properties of reduced infection rates are described (perhaps also with the label “herd immunity” even when the label is inaccurate).

However, the issue now is whether you can use such phenomenon as an acceptable component in a public health strategy.

The ethical view is that if you allow a virus to spread then you must also consider using it as its own vaccine. And if you reject using it as its own vaccine (and thus don’t consider it safe enough), then you should not allow it to spread.

Dutch viewers might look at the tv interview with Jaap van Dissel (RIVM) by Marielle Tweebeeke, “Hoe werkt groepsimmuniteit?”, broadcast March 16. The interview shows Van Dissel as incompetent and manipulative and untrustworthy.

  • Van Dissel does not mention the strategy of containment / suppression by SCT.
  • He does not mention that RIVM goofed in February by not developing this scenario so that they needed the emergency brake of the lockdown. He does not present any excuse for his failure.
  • He presents the psychological frame of three options, of which two are extreme and the third is the proposed one. This is clearly a political frame and no scientific listing of the options.
  • He does not mention that the virus has nasty properties that can show also in younger and healthier persons. (Personally I only discovered this rather late in tracking the discussion about the virus, and I suppose that doctors knew this much earlier.)
  • He allows people to get infected “by natural processes” but doesn’t mention that if he considers the virus to be so safe that he allows it to run around, that by implication it can also be used as its own vaccine. He focuses on the younger and healthier persons and suggests protection of the elderly and comorbid risk groups, but is vague on the contacts between the groups.
  • He mentions herd immunity as a goal (which later will become a by-product) but does not specify that this goal cannot be attained when the lockdown reduces Rt to a much lower value.

Apart from Van Dissel’s disingenuity on RIVM’s goofing on SCT, this kind of reasoning in epidemiology is rather conventional, see also the Harvard study, though it still is (horribly) irrational. The reasoning dates from medieval times before Bismarck and the creation of public health. It is akin to the Anglo-Saxon, but rather Viking, mentality of preferring contest above co-operation. However, we are no longer in pure nature anymore. Public health by definition has the objective to balance benefits and costs.

The issue of legal responsibility for allowing a potentially lethal virus to run its course better be discussed in the open.

In Holland RIVM on January 27 activated SCT but later tended to emphasize “herd immunity” (exit strategy 2 or 3) rather than containment (with SCT). (See this discussion.) Indeed, if you want people to become infected then you don’t need to test them. In this manner, however, RIVM tended to overlook the importance of SCT for the quarantine protection of the vulnerables too: and many deaths were recorded in the care homes, while others at home were not tested and showed up as “excess mortality”.

The failure of Dutch source and contact tracing (SCT)

RIVM might not have been aware enough of the situation for SCT for a pandemic, though they did warn about understaffing at GGD before. An early RIVM document of January 27 2020 already advised the ministry to give alert status A to the infection by the virus, but only in case of symptoms. The document did not deal with one of the known key properties of this virus of asymptomatic transmission – which had been reported about in China. When the number of cases exploded, the Dutch stopped SCT instead of hiring more people to do it. The Dutch system of SCT failed:

  • The Dutch GGD are bureaus assigned to municipalities without a central headquarter. They still have responsibility for source and contact tracing (SCT) for the entire country. Eventually the nestor spoke up for all but without legal position. They appear to have been underfunded and less prepared for a pandemic, see here.  The GGD in 2014 reported to “being below the capacity of a pilot light“, and RIVM in 2015 confirmed that more than half of the GGD bureaus had insufficient numbers of doctors to do the job of infection control. Apparently, GGD even lost the capacity to understand what was needed for a pandemic even though it is their job. They waited for instructions from others while it is their job to do something. In April almost four weeks were lost on “waiting”.
  • We now see a blame game between RIVM, GGD and the ministry of health about who would be responsible for the January / February disaster and also the lost month of April, while Dutch parliament takes a vacation and hopes that all will be clear by September 1, and properly prepared if the 2nd wave would arrive.
  • Unfortunately, the Dutch method of SCT is lackluster compared to the German manner anyway. The Dutch instruction looks at symptoms indeed while the German instruction allows for contacts with an infected person anyhow. At first, the GGD nestor suggested to “write a letter”, like with a sexually transmitted infection, instead of using the phone.
  • RIVM stated that there would not be enough capacity for testing, which might have been literally true at some point, but did not investigate the issue. It later appeared that such capacity could easily be expanded. RIVM misinformed the Dutch.
  • The ministry announced recently that in July there would be an app for contact tracing by phone.

What are major unknowns ?

I am an econometrician and teacher of mathematics and no medical doctor. The literature about this virus is already huge and there will be more known than I can oversee. Key issues with lack of knowledge for me are:

  • What kind of model will cover epidemiology (days) and the national budget cycle (year and medium term) and long term sustainability (world population in 2100) ? Acemoglu et al. (2020) suggest that we might need another modeling format and more complex modeling for all the interactions that are relevant for a more realistic discussion of the pandemic. Even these authors do not explicitly mention the life-years – though they link the life-years to lost economic output.
  • Apparently we still know relatively little about the aetiology (natural history) of the virus. Also a study by Ganyani et al. (2020) in which RIVM participated uses data of some 200 follow-up cases from the early outbreak in China. There are some 40,000 hospital cases in Holland for which GGD might have performed a statistical analysis for key model parameters, and comparable cases known by general practitioners. As far as I know, there is no such study yet. Perhaps such study has been delegated to GGD but then they do not have the funds to do so ?
  • For testing, a fairly quick method, comparable to a pregnancy test, apparently has been developed at MIT (“Sherlock“). It is not clear to me whether the race for a vaccine and the race for a treatment are accompanied by a similar race for such testing. The criteria for a vaccine appear to be rather tough (see above on litigation, and using the virus as its own vaccine), but the criteria for a test might be much easier (including sensitivity and specificity). Perhaps such a test might be taken as a pill and produce an artificial symptom (e.g. a different colour of one’s urine), so that asymptomatic transmission by the virus need no longer be such a problem: for the person with such an artificial symptom knows that self-quarantine is required.
  • RIVM (the Dutch CDC) still publishes only deaths and not (quality adjusted) “expected life years lost”, and thus still has an epidemiological and no Public Health focus (though their mission and very name concerns public health and the environment). My first weblog on the SARS-CoV-2 pandemic also pointed to the Unit-Square-Root as a compromise between lives and years (March 31). The combined CDC’s and National Institutes of Health of Europe ought to be able to present a study of the cost-effectiveness of handling SARS-CoV-2, and such study ought to have the same quality as a cost-effectiveness study on the annual flu vaccine – using measures that avoid a national lockdown. It is too simple to argue that the medical world can only do cost-effectiveness studies when a vaccine already exists: if there is no vaccine yet then consider measures other than the emergency brake of the lockdown of the national economy.
  • There now is an official proposal about triage in the 3rd stage of ICU treatment, in which the life-years gained criterion has been given more attention. Medical ethics can be rather mundane at times – like “first come first served” – with rules that allow for emergency decisions based upon little information. In the modern world, with electronic patient dossiers, such information however tends to be available, and the emphasis lies on the willingness of the medical world to consider more complicated algorithms. They are advised to consider that also other areas – like construction, transport, economics – have considerations about the value of life. There is a key distinction between macro problems, like allocating funds for food security versus national defense, and the micro problem about the next available bed, but such aspects can better be discussed than neglected. (At least, if you neglect it, do not base this upon an axiom as if medical problems would be of special uniqueness, or that issues of life and death are medical by definition.)
  • CBS Statistics Netherlands has mortality statistics that look at the “recorded cause” like “pneumonia” or “heart failure”, or whatever doctors record as the cause of death, and it is quite a statistical exercise for example to determine the impact of a flu season. Apparently such statistical exercise is still in the making for SARS-CoV-2 (with uncertainty about excess mortality), and it is unclear why there was no immediate action on this (e.g. with taking of samples of people dying since February, with the option to test them later). Overall, medical research would be served by a more sophisticated recording of diseases, treatments and causes of death. (For cancer, risk factors are body mass (number of cells), age (time for processes to go wrong) and cell specialisation (specialised cells don’t change much).)
  • There is no clarity about the delay in the normal health care due to the SARS-CoV-2 episode in the first half of 2020. What is the burden of disease and death of this effect ? It is no use crying over spilled milk but what can we learn about maintaining common care if there would be this 2nd wave or the next pandemic (if we don’t do anything about environmental sustainability) ?
  • What is the situation on immunity and mutation ? As we know little about this, what are the risks and how will we be dealing with those ?
  • What would be the relevant path to allow the WHO to decide, with proper data, on whether the virus better be eradicated or not ?

Repair of national trust

National trust has corroded. The captain of the ship had been given the task to steer the ship between Scylla and Charybdis, but hit Scylla with 9000 deaths and hit Charybdis with a dent in the economy and people’s income and savings.

It is true that the government and RIVM by using the emergency brake have prevented some 240,000 deaths, but today the same arguments on content apply that already existed in January / February, so that the delay since February doesn’t make sense.

More and more people understand that this delay, of now a half year, was not caused by lack of information, as RIVM claims, but by indecision at the cost of the general public.

Richard Horton, editor of The Lancet, can say: “Individually, they’re great people, but the system was a catastrophic failure.” However, for a government it is expected that it observes that something is amiss structurally. When that conclusion isn’t made and when repairs aren’t started, then people become restless and wonder why there is such delay at their cost. Not far away is the question: Would the government dodge the issue again at the next event ? Can I still trust that my life and livelihood are safe in their hands ?

Overall, I would also say that the Dutch government structurally misinforms the public also about the situation on environmental sustainability (see here) and the options for economic policy (see here). But okay, the objective is to focus on SARS-CoV-2 now.

Today, the government and RIVM and NiZ are still ambiguous about “containment” (with SCT) and “mitigation” (with “herd immunity”). The situation has improved, with few infections and hardly any recorded new deaths anymore, and with the availability of personal protection equipment (PPE), and testing and SCT. Nowadays, policy makers can choose for containment more easily.

But economic uncertainty is still large, and employers and employees still fear the Fall and the risk of a second wave. The lack of clarity in choice, the lack of admission of mistakes, and the highly problematic economic situation: they now have created a smoldering fire of distrust.

And Dutch parliament intends to take a two-month vacation ?

NB. An evidence-based diagnosis of the corrosion of trust might require an opinion poll, but opinions might also be misguided, as the media still tend to portray RIVM as an anchor in the storm. Journalists love authorities and distrust outside scientists. This weblog diagnoses corrosion not by opinion poll but on content. When people refer to these points of content and state that they no longer trust the government and RIVM, then they cannot be said to be incorrect. When the media still portray RIVM as an anchor in the storm then the media apparently neglect this evidence. The appendix contains some other examples how RIVM clearly destroyed trust. Such examples might be seen as anecdotal only but the above clarifies that they are a result of a decision making structure.

Appendix. Some examples of corroding national trust

These examples might be seen as anecdotal only but the above clarifies that they are a result of a decision making structure.

Example 1. Earlier, the Dutch government did not want an evaluation by September 1. It required a petition and parliamentarian involvement before the government agreed to have it made. It still is not clear what the evaluation will involve in particular.

Example 2. John Jacobs is a biomedical researcher and has a clear statement in favour of containment and suppression (in Dutch). Why is this clarity missing at RIVM ? What is their answer ? Jacobs explains that scientific advice must be open access. When scientists participate in the OMT and longer have open access, then they no longer do science in this OMT.

(If RIVM keeps information secret (perhaps to avoid panic in the population) then they should not parade the involvement of scientists. But okay, it would be another extreme when the very existence of such contacts would be secret too … My diagnosis is that the position of scientists and scholars also involved in actual advice requires a key improvement, see here.)

Example 3. Jasper Lukkezen, editor of the Dutch economics journal ESB, reports that it now has occurred twice in the last months that an article about the cost-effectiveness of the virus policy has been withdrawn by the authors themselves. In one case, there was too much uncertainty about key assumptions. (Such uncertainty indeed holds in general. Lukkezen doesn’t say so, but I infer that it also relates to the lack of information by RIVM: you cannot check what they do when they control the information. In economics, we have a distinction between CBS that establishes the statistical data and CPB that does the planning.) For another case there was the “large political and social pressure concerning the lockdown measures”. This author referred to the case of Alfred Kleinknecht who since the 1990s presents an analysis that the Ministry of Economic Affairs disagrees with, so that they no longer gave him contracts for research. (See: (a) Kleinknecht’s website, (b) my disagreement with Kleinknecht.)

Example 4. There was the focus on the (end of pipe) ICU and the lack of attention for the (begin of pipe) home care that sends patients to the ICU. There was the curious discussion about closing schools and the role of children. There is the issue of aerosols and ventilation. RIVM first rejected the relevance of face masks and later agreed with using them in public transport. As said, RIVM misinformed the Dutch about the capacity on testing. There is the ambiguity and inconsistency on SCT and herd immunity. RIVM has made many errors and has tried to cover up and spin those errors too often.

Example 5. If Rt = 10 holds in one week then R(t+i) = 10 need not hold also in subsequent weeks, because the situation can change. Maurice de Hond rightly criticises RIVM for stating only Rt < 1 or Rt > 1 without clarifying the effect size. When the number of infected people concerns a small number of people, like the 1715 people on a population of 17.4 million, as reported on June 25, then even a value like Rt = 10 may have a limited impact. If over 5 days 1715 * 10 = 17150 people would be infected, and if these people would be youngsters with IFF = 0.06%, then 10 youngsters would die, while traffic accidents have 55 deaths per month. There can be safeguards, like proper reporting also about the effect size, so that Rt and the effect go down again. De Hond denounces the RIVM focus on Rt only as scaremongering and “malevolent”. I regard De Hond’s denunciation as over the top. It may also be a result from an overall lack of communication between RIVM and De Hond: however, we should expect a government institution to decently answer to fair questions. My impression is that RIVM is aware of this issue of the effect size, but simply hasn’t been creative enough to develop the proper dashboard. Aspect are: (1) RIVM refuses to state forecasts of expected deaths, as “speculative”, but then neglects that this is precisely the kind of information that is required (with nuances on qaly’s and cost-effectiveness). (2) Epidemiological models give projections of the developments of infections, clearing and deaths, and it is precisely this kind of information that best is provided by such a dashboard, so that users can see what is involved over what time horizon. (3) While RIVM states that it calibrates the calculation of Rt with hospital admissions, I think that they use a more complex model, while De Hond suggests that they use those numbers directly. I suppose that this can be clarified.

Example 6. Science journalist Jop de Vrieze reported on May 20:

“Hans Heesterbeek is not comfortable with the situation. The professor of theoretical epidemiology at Utrecht University also founded a Slack group in late March, together with chief modeler Jacco Wallinga of RIVM and professor Sake de Vlas of Erasmus MC, with the objective to also give RIVM an opportunity to submit modeling questions to experts from outside the institute, notably questions that are relevant for the Dutch exit strategy. “But these questions have not yet been asked since RIVM has been so busy.” As a result, precious time has been lost. Although contact tracing is now being scaled up, and the lockdown is being relaxed step by step, the substantiation for the dashboard that the Cabinet wants to use is minimal, says Heesterbeek.”

(Dutch; “Hans Heesterbeek is er niet gerust op. De hoogleraar theoretische epidemiologie aan de Universiteit Utrecht richtte nota bene eind maart samen met hoofdmodelleur Jacco Wallinga van het rivm en hoogleraar Sake de Vlas van het Erasmus MC half maart een Slackgroep op, waarin het rivm aan experts van buiten het instituut modelleringsvragen kon voorleggen die relevant zijn voor de Nederlandse exit-strategie. ‘Maar die vragen zijn er door de drukte nog niet gekomen.’ Hierdoor is er kostbare tijd verloren gegaan. Het contactonderzoek wordt nu weliswaar opgeschaald, er wordt stap voor stap versoepeld, maar de onderbouwing voor het dashboard dat het kabinet wil gaan gebruiken is minimaal, zegt Heesterbeek.”)

Example 7. Science journalist Jop de Vrieze reported on May 6: Yaneer Bar-Yam, who has been warning about a pandemic for 15 years and who set up www.endcoronavirus.org, sent a letter to RIVM on March 9, advising to do more and asking why RIVM wasn’t doing more. He did not get a reply yet. One might argue that RIVM may select itself whom it communicates with, but one cannot exclude valid questions by fellow scientists.

On May 5, De Vrieze quotes Bar-Yam on face masks:

Question: “The WHO does not yet advise the public to wear masks.” Answer: “Well, the question remains: if something is evident, are you waiting for an extensive study, or will you assume that it helps if you apply them correctly? We want to stop the outbreak. A good article has appeared that covers all of this: Why we all need to wear masks. If you continue to emphasize that masks are of no use, you swap absence of evidence with evidence of absence. That It [has no proven use][?] becomes a kind of mantra. They think they are talking about science, but they don’t. ”
Dutch: “De WHO geeft nog niet het advies om massaal mondkapjes te dragen. Tja, de vraag blijft: als iets evident is, wacht je dan op een uitgebreide studie of ga je er vanuit dat het wanneer je ze goed toepast helpt? We willen de uitbraak stoppen. Er is een goed stuk verschenen dat dit allemaal behandelt: Why we should all wear masks. Wie blijft benadrukken dat maskers geen nut hebben, verwisselt absence of evidence met evidence of absence. Dat Het [geeft geen bewezen nut][?] wordt een soort mantra. Ze denken dat ze het over wetenschap hebben, maar dat doen ze niet.’”

Example 8. Science journalist Jop de Vrieze on April 15 reported that Denny Borsboom invites government institutes to use open access methods to better use expertise at the academia and research institutes. There is this grassroots project but the harvest is not great. Scientists are aware that it isn’t efficient to put in energy without knowing that results will be used.

Example 9. On April 5, Maarten Keulemans, who studied history and antropology but still got a job as “science journalist” at Volkskrant, distorted a view that had been expressed by lawyer Jort Kelder. The latter had proposed to protect the elderly and make more speed with RIVM / Van Dissel’s “herd immunity” so that the economy could be saved. Keulemans applied the case fatality rates as published by the Imperial College in The Lancet, with instant flooding of the ICUs and not spreading the case load over time, and then he criticised Kelder instead of RIVM. Thus he distorted a critical view and was not critical enough w.r.t. the figure of authority. To this day Keulemans portrays Van Dissel as the wise national doctor instead that he performs critical journalism and informs the newspaper readership about the failure and spin. (This is not the first error made by Keulemans over time.) (The Volkskrant readership tends to be in education and health care.)

Example 10. I saved explicit lunacy for the last. Pepijn van Erp deconstructed the reasoning errors by Willem Engel, but the latter still managed to set up a demonstration on June 20 that ended in violence with 400 arrests. Remarkably Engel called for an end of the lockdown and such ending was quite in sight for July 1 but they still had the demonstration. Lunatics might not see their own errors but they might spot errors made by the national authorities (and then regard such errors by officials as proof that they themselves would not make errors). There is a tv channel around gold-bug Willem Middelkoop which tv channel parasitically feeds upon unrest and conspiracy theories, but there were two remarkably correct tv interviews, one with Cees Hamelink (on the government abuse of science) (wikipedia) and another with Michaela Schippers (on mass hysteria) (cv).

Switching from mitigation to suppression

Currently I tend to think that containment / suppression / eradication of the virus (with testing and source and contact tracing (SCT)) likely is a better policy than trying to mitigate (while protecting the vulnerables).

The key argument is that the virus appears to have nasty properties that also affect the younger and healthier persons. My impression is that this aspect requires more attention in the discussion. The WHO already advises to containment / suppression but the WHO does not yet advise to eradicate the virus. The latter would be an important decision.

For Dutch readers there is this clear discussion by John Jacobs, a researcher in microbiology and former chair of the federation of medical research associations in Holland. English readers might look here.

Redesign of didactics of some epidemiological models

A factor in my change in viewpoint is this redesign of didactics of some epidemiological models.

  • The redesign only transforms what is already known into a new format. There is no new model. There are no new data. The only idea is that aspects are presented in a clearer fashion.
  • However, this redesign caused me to reconsider notions of herd immunity, see section 1.5.5. (page 26) and section 6.11 (page 105). The standard formula for herd immunity, via the proportion of infected and recovered persons of 1 – 1 / R0, appears to be much abused in the discussions about SARS-CoV-2. A commonly mentioned percentage is 60% relating to a value of R0 = 2.5. The formula applies to a steady state, but the problem with a steady state is that infections continue: whence there is not really the protection that is supposed to be offered. A herd may have a stable size while youngsters are born and elderly fall victim to predators, but there are still such victims. The basic S(E)IR(D) models do not have a steady state but only an asymptomatic end state. For those models, the limit values are relevant, but those have a quite different formula. For R0 = 2.5 the limit value is almost 90%, whence there is an “overshoot” of 30%. If you promise herd immunity at 60%, with protection for the remaining 40%, while there are still 30%-points unprotected, then you are off by 3/4 and your promise of protection (“immunity”) doesn’t make sense. My diagnosis is that many persons who have been speaking about herd immunity for the SARS-CoV-2 pandemic actually did not know very well what they were speaking about.

The latter actually also applies to a large degree to my weblog of April, in which I used the formula 1 – 1 / R0 = 75% for the value of R0 = 4. I did not claim that this was sufficient since the vulnerables were also submitted to a protective regime of quarantine. But I did not explain the situation with adequate clarity, and this has now been revised in this redesign of the didactics of those models.

It remains to be seen whether epidemiologists will be open to such redesign of these elementary models, which they have been using and teaching for the last 50 years. The proof is in the eating of the pudding.

Revision of the rejected scenario for using the virus as its own vaccine

While I changed my viewpoint, the earlier viewpoint, now scrapped, still can be updated to the news. Earlier in April I suggested:

  • to segment society in vulnerables (elderly and younger with comorbidity) and less vulnerables
  • to protect the vulnerables with systems of quarantine
  • to deliberately infect the less vulnerables, using the virus as its own vaccine, albeit in cohorts in order to remain within the capacity of the ICU system.

This scheme can be updated with the following main points:

  • Earlier I counted only the 60+ as the vulnerables (4.4 million) but now I have found data on comorbidity in the younger age groups as well (3.4 million in 2011, say 3.5 in 2020). Unfortunately, the infection fatality factor (IFF) for the latter are not given. I take the same value as the IFF as for the 60+, in below table 5.1%.
  • For the less vulnerables, the target now is no longer 75%. We rather take the limit value for R0 = 4. However, a limit is never reached, and let us settle for 95% of the limit value of R0 = 4, which is 95% * 98% = 93.1%.
  • The testing and SCT capacity in Holland has been much improved. The quarantine status of the vulnerables can be improved so that the larger group still has only a 1% failure of quarantine with infection by the less vulnerables.

The excel sheet is here. The relevant table is below. It would take 10.2 months to infect some 8 million less vulnerables, using the virus as its own vaccine, in cohorts of size 323,801 every 1.5 weeks, spread out over the different hospital service areas. The mortal cost would be 9,335 deaths, of which 4,005 in the vulnerable group and 5,330 in the less vulnerable group. This compares to the 9,000 deaths that actually occurred in the first half of 2020, in chaotic manner and without the building up of this immunity by the less vulnerables. However, we may actually be better off by not having had this scenario, because the table below does not mention the nasty effects of the virus also for the less vulnerables.

As said, I no longer propose to investigate this scheme for actual implementation, at least for Holland. It still seems useful to have it available, in case testing and SCT would actually not work (perhaps in other countries too).

There has been discussion whether SARS-CoV-2 (Covid-19) can spread via aerosols, i.e. by particles much smaller than droplets from the mouth and sneezing. The main study is Van Doremalen et al. (2020) (April 16), who write:

“Our results indicate that aerosol and fomite transmission of SARS-CoV-2 is plausible, since the virus can remain viable and infectious in aerosols for hours and on surfaces up to days (depending on the inoculum shed).”

The study was done with a rotating Goldberg drum that turned for 3 hours so that the virus made quite some distance. These authors clearly state: “SARS-CoV-2 (…) can remain (…) infectious in aerosols

On the other hand, there is RIVM, the Dutch CDC, and its outbreak management team (OMT). The view by RIVM is here (OMT May 15 and RIVM May 27). They refer to studies that would not prove influence with certainty, in particular for SARS-CoV-2, and then they conclude that, while there is some evidence, there still is insufficient evidence for such influence.

“In conclusion, there is currently insufficient evidence whether the virus can be spread over a longer distance, then is infectious indeed and can lead to infections.” (“Concluderend is er op dit moment nog onvoldoende bewijs of het virus over langere afstand verspreid kan worden, dan daadwerkelijk infectieus is en tot besmettingen kan leiden.”)

Remarkably, OMT / RIVM refer to Van Doremalen et al. (2020) but do not provide counter-evidence that the latter would be insufficient. Thus it is false when OMT / RIVM state that there would be “insufficient evidence”. OMT / RIVM gives a wrong summary of the literature.

What is happening here ?

Confusion by minks / ferrets at a small distance

Apparently OMT / RIVM got itself into a tangle on the situation that minks / ferrets in Holland were found to infect humans, see Richard et al. (2020) here. The researchers put ferrets in cages 10 cm apart and observed transmission by air. One of the authors of the Richard et al. (2020) is Marion Koopmans, who is also member of the OMT. OMT / RIVM state:

“In both studies, however, the distance between the ferrets was small, making it impossible to determine with certainty whether the dispersal was via aerosols or droplets.” (“In beide studies was de afstand tussen de fretten echter klein, waardoor niet met zekerheid kan worden vastgesteld of de verspreiding via aerosolen of druppels heeft plaatsgevonden.”)

However, here OMT / RIVM focus on the laboratory setup of Richard et al. (2020) with the limited range of 10 cm,  while they forget about the wider implications of the Van Doremalen et al. (2020) study valid for a larger distance. Apparently Richard et al. want to make sure that everybody understands that 10 cm is not 1.5 meter. However, they lose perspective.

It is rather curious that the Van Doremalen et al. (2020) study gets so misrepresented.

Distinction between having a property and showing a property

Both Richard et al. (2020) and OMT / RIVM refer to Van Doremalen et al. (2020). Richard et al. (2020) infer from the Van Doremalen et al. study:

“In a recent study, SARS-CoV-2 remained infectious in aerosols for at least 3h after aerosolization at high titers in a rotating drum, comparable to SARS-CoV [ref]. Although it is informative to compare the stability of different respiratory viruses in the air, our study provides the additional information that infectious SARS-CoV-2 particles can actually be expelled in the air and subsequently infect recipients.”

Thus, while Van Doremalen et al. (2020) speak about being “infectious“, Richard et al. (2020) claim that “actually infect” would be something different, as if “infectious” does not mean that the virus can infect.

It is like the distinction of an apple being nutritious and an apple actually nourishing me.

The verbal distinction of course exists. However, it has no material impact here.

Conclusion: OMT / RIVM distort the scientific evidence. Let them please repair.

Other evidence

For completeness, let us look at some other evidence.

1. In the actual mink / ferret farms, the corridor between the cages may well be 1.5 meters wide, see this picture. There was no report that ferrets got only infected in particular rows. Likely there was wholesale spread over entire barns, perhaps though spread by humans walking in the alleys.

2. There is the air ioniser. Dutchman Ton Rademaker claims that he alerted some Chinese hospitals to the problem of ventilation and the solution of ionisation and that they tried this and that it worked. Rather than dismiss this, one would want this checked. The wikipedia article on the air ioniser refers to this peer reviewed article on reducing air-borne transmission: Hagbom et al. (2015), who state: “Most importantly, we demonstrate that this technology can be used to prevent airborne-transmitted influenza virus infections.” See from there to articles about airborne infections.

Scientific curiosity

Potentially the discussions of OMT / RIVM involve so many people and aspects that the result becomes something like the product of a legal accountant. Instead, a scientific researcher would check the observational or experimental setups, check what information is missing, and design an experiment to prove or disprove the hypothesis. One would not take SARS-CoV-2 because of its potential lethal property but a common cold. Okay, if you want to kill ferrets, then you have a license to use SARS-CoV-2, and see whether you can create aerosols for a distance of 1.5 meter. One could calculate how much the experiment would cost and how long it would take. It is remarkable that OMT / RIVM does not show this scientific interest and doesn’t commission such research. One gets the impression that they were asked about their earlier view, and that they are only interested in restating their earlier view, instead of opening up to alternative views and searching for contrary evidence. In the above I only supposed that they were distracted by the 10 cm distance between the ferret cages, and wanted to make it really clear that 10 cm is no 1.5 meter. Still, it is a remarkable scientific error and perhaps there were also other influences.

(One might propose that if they really think that it hasn’t been proved, then infect the air conditioning system of the university with some virus, and see what happens. Ah yes, you cannot experiment on people, even if it is the common cold, but it is fully acceptable to allow a potentially lethal virus to run around in society with the purpose of “building up herd immunity”.)

Employer associations on air ventilation

It must be mentioned that Techniek Nederland and NVKL, organisations of producers and installers of ventilation systems, refer to the RIVM report. These organisations repeat the conclusion that it hasn’t been proven that such systems can transfer the virus. This is very much like arguing that it hasn’t been proven that the Virgin Mary didn’t have an immaculate conception because nobody, and especially not the Pope, provided evidence that it happened differently. Precisely the organisations that should provide customer support join RIVM in what runs against common sense. It is not necessarily in their interest: because adapting such installations would provide for much employment. Perhaps they are afraid for legal action that they are guilty of causing infections by selling unsafe installations ? Dutch TV on the evening of June 24 had the railways CEO explain that people cannot open the windows in the train but that the railways were looking for improvements of the ventilation system (apart from opening doors at stations). It is a serious issue, and RIVM makes a curious scientific error here.

Maurice de Hond

I came upon this topic via Maurice de Hond, an opinion pollster with a background in “human geography”. He is livid that RIVM denies the importance of aerosols, ventilation and air conditioning.

An important argument by De Hond refers to the observation that 10% of the cases might infect 80% of the next generation. Thus the R0 for the 10% will be much higher than the average. RIVM instead clings to the average:

“Also an R0 of 2-4 does not seem to indicate aerosol distribution and a substantial contribution to the direct human-to-human transmission of SARS-CoV-2 (ECDC rapid risk assessment April 23, 2020)” Dutch: “Ook een R0 van 2-4 lijkt niet te wijzen op aerogene verspreiding en op een wezenlijke bijdrage aan de directe mens-op-menstransmissie van SARS-CoV-2 (ECDC rapid risk assessment 23 april 2020)”

Conclusion

The above explains the error by RIVM. Let they please correct.

(It would be interesting whether RIVM has been presenting this view with ECDC and what their reaction has been.)

Addendum June 26

It now appears that KNAW had a webinar on the issue on June 4, with moderator Detlef Lohse, and four other speakers on fluid dynamics. The Guardian referred to a report on the air cooling system of a German slaughterhouse. One would hope that RIVM comes around soon, and before the Fall when people spend more time indoors. A Dutch magazine report is here.

Addendum July 6

(1) RIVM updated its argumentation on June 30. They rephrase to:

“We state that, based on current insights, it is unclear whether aerosol transmission plays a role in the spread of SARS-CoV-2. Dutch: “We stellen dat op basis van de huidige inzichten onduidelijk is of aerogene transmissie een rol speelt in de verspreiding van SARS-CoV-2.”

This is a vacuous statement, using their authority only, since they do not state what condition must be satisfied before things are clear to them. It is unclear why RIVM rephrased their position while they say the same on content.

(2) There are Morawska et al. (2020) with 239 scientists who argue for more attention to aerosol transmission in the regulations of the various countries. Sadly, they weaken the case, by stating, without clarifying what would be missing:

“The evidence is admittedly incomplete for all the steps in COVID-19 microdroplet transmission, but it
is similarly incomplete for the large droplet and fomite modes of transmission. The airborne
transmission mechanism operates in parallel with the large droplet and fomite routes, e.g. [16] that
are now the basis of guidance. Following the precautionary principle, we must address every
potentially important pathway to slow the spread of COVID-19.”

Thus we see 239 scientists shooting themselves in the foot. What evidence is incomplete ? It is absurd to invoke the precautionary principle against murder when the dead body of the victim lies before you. There is a crucial distinction between science and philosophy, as a philosopher might ask: “What is “dead” ?”

PM. My attention to the 239 scientists was drawn by this article by (unreliable) Maarten Keulemans. He spoke with one of the Dutch signatories, Philomena Bluyssen:

“We believe that especially as we return to the old situation, aerosol transmission should be recognized as an equally relevant route.” Dutch “Wij vinden dat met name nu we weer teruggaan naar de oude situatie, aerosole transmissie als volwaardige route moet worden erkend.”

(3) Ab Osterhaus agrees with De Hond that measures against aerosol transmission may help, must be tried, and must not be discounted as an investment loss (Medisch Contact). This again is the precautionary motive, while De Hond points to the superspreading events, and the option that direct human contact (say between family members who visit their grandparents in a care home) might be feasible if other precautions are taken.

Addendum July 7

Jack Schijven et al. (2020) have this (non-peer-reviewed) article on medRxiv July 5: “Exposure assessment for airborne transmission of SARS-CoV-2 via breathing, speaking, coughing and sneezing”. This is a Monte Carlo simulation that uses observed (boundary) profiles and phenomena and their estimated parameters to run a model of how actually unobserved airborne transmission might occur. It is quite remarkable how the human biology may be modeled. A remarkable meta-observation is that the authors are affiliated with RIVM that has been hesitant in acknowledging aerosol transmission. My comments are:

(1) They state:

“Similarly, van Doremalen et al. (2020) also found that SARS-CoV-2 remained viable for hours in experimentally generated aerosols (reduction in infectious virus particles from 3100 to 500 per litre air in 3 hours).” (lines 90)

However, Van Doremalen et al. (2020) state that the virus remains *** infectious ***. Indeed, Schijven et al. later state:

“Because short time frames are considered, and SARS-CoV-2 has been observed to remain infectious in aerosols for hours (Fears et al. 2020; van Doremalen et al. 2020), decay over time is not modelled in this study. The exposure assessment will, in that regard, be conservative. ” (lines 250)

My suggestion is that they replace the first “viable” with “infectious” too, because there is a risk that you might be quoted selectively. If they don’t believe Van Doremalen et al. (2020), and want to change the latter “infectious” with “viable” too, Schijven et al. should first check with Van Doremalen et al. whether they did use e.g. a culture plate with human cells or lab animal indeed, and Schijven et al. then should report about this check with these authors.

In general a person is infected until the immune system clears the person (even when e.g. HIV goes into hibernation), and the default assumption is that Van Doremalen et al. (2020) are aware of this convention, until peer criticism shows that they have made an untenable claim.

(2) They state:

“To conclude: aerosol transmission of SARS-CoV-2 is possible and should not be disregarded.”

In my judgement, this already shows from Van Doremalen et al. (2020). Schijven ea. do not clarify what their own study adds to this earlier finding. A new study must be more specific about the difference between the earlier finding of “infectious aerosols” and the new finding of the same. If a new study cannot state a relevant criticism, then the new study must state that its finding supports their finding. Please do not leave the puzzle to others.

(3) Schijven ea. first state:

“Furthermore, it should be noted that it is unknown what fraction of airborne RNA-copies is infectious virus. Observational data on infectious virus in aerosols in various settings are needed to validate modelling efforts. No dose-response model is, as of yet, available for SARS-CoV-2. “

and then conclude the same:

“5.As long as it is uncertain what fraction of the airborne RNA copies relate to virus particles and how much of these are infectious and as long as a dose response relation is lacking, it is recommended to be precautious.”

(3a) Basically they now again question whether Van Doremalen et al. (2020) have been competent enough about their use of the word “infectious”.

I can imagine that a particular line of research uses RNA and Ct values to score outcomes and then wonder about the dose response relation, but in general a person is infected until the immune system clears the person, and the default assumption is that Van Doremalen et al. (2020) are aware of this convention, until peer criticism shows that they have made an untenable claim.

Thus, in general my impression is that, the dose-response relation relates to the severity of the disease (e.g. whether healthy nurses may die too), and not to the fundamental point that a person becomes infected.

(3b) What kind of “observational data” would Schijven ea. imagine that can be generated to validate models here ? Follow individually marked aerosols by camera ? Are people (or e.g. trains) to take air samples before people report sick ? It seems that Schijven ea. are imposing an impossible condition. It may indeed sound logical, that you actually want to see proof for something. But if you cannot prove the issue in any practical manner, then this phrasing may cause a lot of confusion, as if first something impossible must be proven. My suggestion is that Schijven ea. state what a practical proof would be, or otherwise clarify that such condition is impractical.

(3c) Their use of the word “precautious” is also in the “discussion” of their abstract. What do Schijven ea. mean by being “precautious” ? Do they mean precautious in saving the economy by not requiring more ventilation, or do they mean precautious in saving people by further locking down the economy before air ventilation has been improved ?

Their ambiguous use of the word “precautious” can be abused by selective quotation by persons or agencies who want to advocate the one or the other.

My suggestion is that authors do not try to think for readers, on what they ought to do or not, but that they give information. It suffices to support the conclusion by Van Doremalen et al. (2020) that there can be aerosol infection, so that agents can adapt guidelines. Agents in the economy then will be alerted to the newly identified risk, and take their own measures and do research until there is more clarity about their own particular situations.

(3d) These authors work at RIVM. I am annoyed that Richard et al. (2020) on ferrets, that they refer to, and that RIVM maltreat the Van Doremalen et al. (2020) study before too. See here:

https://boycottholland.wordpress.com/2020/06/25/sars-cov-2-and-aerosols-and-ventilation/

RIVM has a tendency of making judgements about cost-effectiveness and economic impact without modeling such aspects or consulting with experts on those issues. If RIVM accepts that such aspects are relevant, then widen the circle of such experts, or restrict yourself to what you can say.

(4) Allow me to suggest that Schijven et al. also refer to the website of Maurice de Hond. When you refer to the point that there has been discussion about aerosol transmission then this might be a good place to refer to such discussion in the public domain. De Hond already linked superspreading events to the aerosols and that 20% of people may cause 80% of infections so that their R0 is high and so that the counterargument of RIVM on the average R0 has no relevance. If you are looking for observational studies then you can find some such evidence in that SARS-CoV-2 here is basically like SARS-CoV-1 (Peter Borger).

Addendum July 8

Apparently WHO is now rethinking the role of aerosols. The BBC:

“The World Health Organization has acknowledged there is emerging evidence that the coronavirus can be spread by tiny particles suspended in the air. The airborne transmission could not be ruled out in crowded, closed or poorly ventilated settings, an official said. If the evidence is confirmed, it may affect guidelines for indoor spaces.”

What would they mean by “if the evidence is confirmed” when it has already been confirmed many times over ?

RIVM and NICE provide new figures up to April 18. My earlier discussion of 14 days ago used data from April 2. The Dutch death toll has risen from 1339 to 3601: with one unspecified age, so I will use 3600.

The London Imperial College infection fatality factor (IFF) (they call it a rate) is still not useful for Holland, and the Canary in the Mine principle for the 70-79 age group still gives results that seem reliable – see the former weblog entry for the explanation. The excel sheet has been updated here. (Update June 1 2020: Indeed IFF instead of IFR. Took not only the IFF of 70-79 but also 80+ equal to the LIC values. Took the quarantine hospitalisation ratios as observed, see the text.)

Comparison of the main tables for now and 14 days ago gives these results:

  • The 80+ group has become much more unreliable in the Dutch data. Apparently GP doctors and families have a greater tendency not to send such patients to the hospital anymore, given the emotional and physical burden (no contact, low survival rate). This group has 12% more deaths than hospitalised cases, which means that testing is now done more often outside of hospitals. (Indeed, at the end of May, it appears that CBS has registered many “surplus deaths” outside of hospitals.) However, the 70-79 group still seems to opt for the hospital. (This also means that statisticians must check that their time series for the D / H ratio maintain the same definition. It is important to check the performance of hospitals.)
  • If the canary works okay, then the (cumulative) prevalence of infections has risen from 92391 (0.5%) to 248160 (1.4%). Officially reported infections were only 16% and are now only 13% of all infections.
  • The implied “registered” infection fatality factor (IFF) is about the same: was 1.4% and is 1.45%. (Some call the factor a rate.)
  • Deaths are still much underreported however. Deaths outside of hospitals are still hardly tested. The CBS mortality data indicate, as RIVM reported, that there might be another 2000 untested deaths. That is, the “surplus deaths” compared to other years are twice as high as the officially reported deaths attributed to Covid-19.
  • It is tempting to infer that the true IFF might also be 3% but this neglects the profile of infections, since people are not infected now randomly, but there are reports that the virus is spreading more rapidly in home-care for the elderly. The officially reported number of cases in the ICUs and the number of deaths is flattening, but if GP doctors and families have decided to avoid hospitalisation, then there might be no real flattening.
  • Thus, there still is no true indication that the reproductive number is below 1, though the national lockdown is of such quality that we may expect that it is, at least for the people outside of home-care for elderly. However, the economic cost of this lockdown is huge. There is something very bizarre about the official policy of locking down the country to save people but also allow that the virus spreads in home-care for the elderly who are precisely the most vulnerable.
  • While there were 0 deaths below age 50 at the beginning of April, there are now 23 such deaths. This still indicates that the virus works as its own vaccine for this group if we exclude comorbidity.

These new data only affect the left hand side (LHS) of the table. They do not change the fundamental insight on the right hand side (RHS) that the virus works as its own vaccine for the younger group without comorbidity. This means that the suggestion from the former weblog entry for an exit strategy with quarantine zones still stands. If we want to start with this on May 1 then only 11 days are left for planning, i.e. at all levels of government, agencies, companies and families.

Update April 21 and June 1: The table with the exit scenario did not yet contain the implied IFF’s. These have been included now, no longer using the factors from the Imperial Collega but those mentioned in the “canary section”, of which 70+ still is taken from the Imperial College. Of the implied deaths, only 75% applies for the younger group because of herd immunity, and only 4% applies for the elderly because of quarantine. I now assume that the overflow of infections from the exposed population of 12.4 million to the vulnerable group of 5 million will be 4% of the latter, with 25% of development of disease, so that still 1% is in the danger zone. The vulnerable above have an IFF of 4.8% and below an IFF of 5.1%. The less vulnerable above have an IFF of 0.06% and below an IFF of 0.06% too. The overall IFF above does not quite compare to the Quarantine-IFF below, since the weights of the groups have been adjusted (above has population weights and below has deliberate status of infections). Update June 1: The rates of hospitalisation above are 1.55% for the younger and 9.53% for the elderly. These rates have now been used below too. For the non-hospitalised “surplus” deaths, an IFF of 5% has been assumed.

All politics is local. Infections are local too. In the Covid-19 epidemic it makes sense to consider some sort of management of social behaviour, with attention to the local character of quarantine.

  1. Use information about disease status and risk.
  2. Insulate the vulnerable (elderly and diseased) by stricter rules.
  3. Allow a controlled gradual re-introduction of the virus as its own vaccine, so that the economy can recover.

Update 2020-04-07: (1) Sake de Vlas and Luc Coffeng had the same idea of gradually re-introducing the virus, see their preprint of April 1 2020. They use 10 regions of each 1 million people, with transport of ICU patients between them. I am thinking of hospitals and their own smaller service areas, and quarantined patches within those, so that transport is normal. There will be similar numbers of re-infected nationwide, and a same period of 16 months. De Vlas & Coffeng do not yet mention the death count of the strategy. (2) Paul Romer suggests daily testing of randomly 7% of the population, when those tests are available, and also considers daily randomly allocating 50% of the population to lockdown when there are no tests yet (and self-quarantine if you get symptoms). The latter are ways at containment / suppression of a homogeneous population while I would tend to look at isolation / immunity and ways to scale up ICU capacity for a heterogeneous population.
Update 2020-04-19: RIVM has reported more than 3,500 deaths now, as officially attributed to Covid-19, but also a rise of untested deaths overall. Official deaths below the age of 50 are 23, which corroborates below numerical setup. Table 3 is slightly adapted to better fit with table 2.

Colour coding

The idea of colour-coding for the status of infection is rather natural. Fruits and flowers already use the gimmick.

China now has this app: (1) green = travel relatively freely, (2) yellow = home isolation, (3) red = confirmed Covid-19 patient who must be in quarantine. (Guardian)  I had suggested this type of coding in 2004 for HPV that had no vaccine at that time yet – see this working paper – though this particular virus soon got a vaccine.

The last weeks I have been reconsidering the coding scheme. There are more groups to deal with. It is also better to use red for the quarantine borders between the different groups. My present suggestion is this overall scheme:

Covid-19 Colour Coded Groups

The reasoning behind the code is to use the natural combination of R, G and B as much as possible. This is the overall scheme.

Covid-19 RGB Colour Coding

The following is an example map. It contains two hospitals: one for the vulnerable and uninfected and one for the infected and infectables. The example has a geographic layout, but one would start out with a functional allocation, and then see how it would work out geographically. One would suppose that the homes of the elderly, or at least the entries and exits, are surrounded by red barriers, and guards checking who crosses the boundary. Basically one would try to identify larger regions that have the same code, so that people can move freely within their region. Indeed, villages that are unaffected would set up village border patrols again. Make visits by appointment: not only the doctor and hairdresser but also schools and cafes. Below calculation shows that a cohort of less-vulnerable (young and non-diseased) persons can be of size of 270,000 persons, such that if the virus goes rampant in that cohort then their allocated hospital would still have enough ICU beds to serve the severe cases amongst those less-vulnerables. It is an option to deliberately infect such cohorts, since for the less-vulnerables the virus has little effect and is basically a vaccine for itself (though it can hurt). For Holland, such a scenario would take 16 months. See the discussion below.

Covid-19 Colour Coded Map

Why would we consider such colour coding of the disease status ?

Findings by the Imperial College Covid-19 team

The Imperial College Covid-19 team estimates that R0 =3.87 from a study on European nations, with an Infection Fatality Factor (IFF) 0.66 (that they call a “rate”). For the UK they calculate an IFF 0.9. Their underlying estimates using data from China and the Chinese conventions at hospitalisation are not at their website but originally at the medical archive and now (shorter) in The Lancet. Their “impact paper” by Neil Ferguson et al. (March 16 2020) sums up the current message on Covid-19:

  1. Best is suppression of all infections down to the capacity of the health system, and there-after start with surveillance with tracing and isolating infections, for the whole period till we have a vaccine, which may take 12-18 months. This scenario fits with keeping R[t] < 1. Taiwan likely gives the best practice for containment / suppression of Covid-19. It will be quite a challenge for the health care system to set up such a surveillance system, e.g. requiring at least five investigators per suspected infection.
  2. Worse is the idea of mitigation, i.e. to try a combination with trying to get herd immunity. This plays with the idea that R[t] > 1 so that eventually a large majority of the population builds up immunity. This would come with a huge risk of overburdening the health care system. However, the Imperial College team has not yet considered an approach of structured quarantines, see below.

Perhaps not all arguments have been mentioned why Covid-19 will be with us for at least a year, and why it is best to plan for at least two years. The reasons are rather standard from an introductory course in infectious disease:

  • getting a vaccine takes time … and then give it to seven billion people on the planet
  • health care is under strain, will perform less well, thus allowing breaches and ever newer infections
  • the virus already shows mutations and is likely to continue to do so: every new mutation would require a swift reaction for new containment – but the health care system already is under strain.

We can expect waves of new infections, like with the flu, but then 10 times more infectious / deadlier than the flu, with the risk of shorter intervals because of faster mutations. The Northern hemisphere now benefits from the upcoming Summer, but in Autumn the reduced health because of the common cold and flu will combine with Covid-19, causing increased joint mortality. This upcoming Summer should rather not be wasted.

Hammer and dance

What the Imperial College proposes as “Containment” is called “Hammer & Dance” by Tomas Pueyo. Pueyo employs a slightly different terminology. He compares “Do nothing” with “Mitigation” (towards herd immunity) and “Containment / suppression“. He advises the latter for the USA, and presents his variant as a “hammer and dance” approach, which is still the Imperial College proposal:

  • first contain / suppress by lockdown to the level of health care capacity (likely not in a constant state of emergency),
  • and then follow the Taiwan and South Korea model of slow release but suppression by trace and quarantine of new infections.

In Pueyo’s graph, observe the distinction between the horizontal axis and the capacity of the health system just above it (the height of the green curve in the “ongoing” phase). Pueyo also points to the epidemic calculator by Gabriel Goh.

Containment and Hammer & Dance are not enough

Given the expectations above, the Imperial College “suppression” and Pueyo’s “Dance” are dubious. There is no way how we can currently reduce the number of infections down to the manageable level except by lockdown. Perhaps the USA and Europe with more resources can try to copy the Taiwanese example but can they really, and what about other regions ? Given that the world is not Taiwan, the world now has only the option of lockdown, continued hammering, and this has nasty effects:

  • In lockdown, there are the “collateral” deaths of persons who would normally receive care but who remain untreated. The Dutch Volkskrant newspaper reports that 40% of normal hospital care has been cancelled. (a) People with a disease are vulnerable to Covid-19 and may fear a greater risk of infection within the health system itself. (b) Health care resources are reallocated from normal care to Covid-19 related cases. The latter is rational, given that untreated infections are a risk for the whole population. Not treating infected cases (by hospitalisation or self-quarantine with supervision) creates such risk. We must compare the collateral deaths to the “avoided deaths by treating those with infections“. PM. See my earlier weblog about the value of life.
  • In lockdown, the economy is severely affected. Bankruptcies would strain the legal system. The government currently tries monetary, financial and tax arrangements, but real production would collapse, and more money chasing fewer goods will mean rising inflation and the need for price controls. Thus, we are getting a war time economy. For Holland, production already goes from expected positive growth of 1.7% to -1.2%, a loss of at least 2.9% of GDP, or some EUR 24 bn of EUR 800 bn – see the CPB-scenario’s of 2020-03-26. Each death has come along together with a loss of EUR 30 million. See also Richard Baldwin at VoxEU on preparing for the second wave.

The Imperial College team and Pueyo present the “mitigation / controlled infection” scenario as too risky with too many deaths. One tends to agree with them, except for above nasty effects that they don’t actually discuss.

If “mitigation” comes with a degree of control then there are some aspects that are worth considering. When Covid-19 is relatively harmless for a large low-risk group, it can work as its own vaccine. The objective of this present weblog is to show a way how to enhance control: by better identifying and handling of the various quarantine categories.

Dutch data about Covid-19: using the 70-79 group as the Canary in the Mine

The following uses data of April 2.

The Imperial College estimates give problems for the Dutch data. With 121 deaths in the Dutch 60-69 age group, the London age-specific IFF gives 5500 infected in the population while their “symptomatic cases per hospitalised” gives 7663 symptomatic cases in the population, which is too much since we are assuming that the flu season is over. Holland has 29 hospitalised children of age 0-9, and the London symptoms / hospital ratio for this group gives 29000 symptomatic children in the Dutch population, which would create panic if true. Looking the issue over, I cannot find a match. It must be remarked that the Dutch “reported number of cases” is rather useless, because of the lack of tests, and their preferred application to medical personel rather than patients. Also the death count is understated since non-hospitalised deaths are not tested. See Table 1 below.

However, the Dutch 70-79 age group may be used as canary in the mine. The number 2951 of “reported cases” will be accurate for this group, since they do not belong to medical personel. These patients will have some symptoms (like “feeling really sick”) and not be tested for nought. The reported number of 2951 means only 0.19% of the whole age group. The Imperial College IFF for this group gives an estimate that 8137 would be infected, or a share of 0.005346 or 0.5%. We arrive at the problem that we are not in the steady state. Either these elderly “infected but non-patients-yet” have a stronger immune system or they are due to arrive at the hospital at a later moment. With lack of other information, we can still presume that this is the overall prevalence of infection (haves and have-beens) in Holland. When we apply this prevalence to the whole population, then we get age-group specific ratios of hospitalisation and IFF that show the same pattern as in China and the London research group. Especially relevant is the “hospitalised per infected ratio” (H/I). See Table 2 below. NB. This uses IFR and CFR, namely as “rates” while it actually are factors IFF and sCFF (symptomatic case fatality factor).

Intermediate conclusions

The intermediate conclusions are:

  1. On April 5, Holland has about  92.391 infected persons, or 0.5% of the population. The reported number of cases by RIVM is 16% or 1/6 of the true number. The current IFF for Holland is 1.4% because of the high share of elderly people (with comorbidity). If you are younger than 60 then your IFF is 0.04% (4 basispoints) and for 60+ it is 5.5%.
  2. If 100% of the population would get the virus then there will be 20,945 deaths younger than 60 years and 197,896 deaths in the 60+ group. The normal deaths in 2019 were 151,737 persons. Life expectancy would roughly reduce by 1% – till there is the vaccine.

A scenario with a Dance with Managed Quarantine

Table 2 in the last column (at the bottom RHS) has the option of using the health care capacity for the coming two years:

  1. The group of 60+ is put under quarantine, so effective that at most 1% of them gets infected. This would cause the death of 1979 persons in that group. (Actually, it will be wise to also include the younger diseased in this vulnerable group, see below.)
  2. The group younger than 60 years is put under quarantine, but also: step by step exposed to the virus, in cohorts of size 271,360, using the virus as its own vaccine, so that eventually herd immunity at 75% of this group is attained (using R0 = 4 and 75% = 1 – 1/R0). This would cause the death of 15,709 persons in this group. (But there will be less deaths if we shift the younger diseased.)
  3. It would take 16 months to achieve this. By that time, there ought to be a vaccine, and the vulnerable people in the population can be vaccinated, while the less-vulnerable people already will have achieved herd immunity for their section.

More detailed calculations are in Table 3 and this excel workbook. I suppose that the population still will grow a bit. Blue letters and figures are parameters that can be adjusted. The other colour coding is taken from above. For this calculation, the vulnerable group consists of 60+ and the younger diseased, so that the protected group counts 5,000,000 people. Implications are:

  • A vulnerable person who gets infected anyway (slips through quarantine – the 1%) needs 3 weeks of ICU time, while a less-vulnerable person takes 1.5 weeks of ICU time. Given the required loads of service, 328 covid-beds serve the vulnerable and 1272 covid-beds serve the less-vulnerable. There are still 800 beds for non-covid ICU cases, allocated to the different quarantine areas. The parameters can be adjusted to different values, and then the scheme might take a different number of months.
  • In this scheme, the number of deaths is reduced from above 218,841 to 19,661 (a bit different from above rougher 17,688) over a 16 months period. The normal death count is about 150,000 per year, so this rises with 10% per year over a period of 16 months. The causes for the much lower death toll are: (a) the strict protection to the vulnerable group, (b) the shift of the group of younger vulnerables from the younger group to the vulnerable group.
  • While the less-vulnerable group would be the “economicially productive” group of society, they could restart their business in two manners: (1) first under the quarantine of “unsymptomatic and untested” (Cyan) group (with restricted number of contacts), then a pause for the phase of cohort infection and recovery (Blue, for some Magenta and some death (black, not shown)), then (2) secondly as recovered and likely immune and no longer a carrier (Green) (with restricted number of contacts even when no carrier, when it is not clear what the recent contacts have been).
  • For an evaluation, we need an estimate of how many “collateral lives” would be lost, if we do not restore some normality.

For people and goods crossing borders, testing is important (not only whether one carries the virus but also whether one once did). Such tests are now in short supply, and when they come in supply then the priority is for the health system. Overall, they would be important for the “dance” phase. However, with this scenario, they will also be important for the checking of the quarantine boundaries and the management of the deliberate infection of the cohorts.

(Table 3 not shown anymore since the one in the next weblog entry is better.)

Conclusion

Overall, it seems possible to start up the economy again in the beginning of May, without the risk of another wave of infections, provided that society finds a way to manage and control the states of quarantine.

NB. For an evaluation, we need an estimate of how many “collateral lives” will be lost, if we do not restore some normality.

PM. See the excel workbook for details and references to authors who inspired this kind of calculation. The CBS Statistics Netherlands StatLine tables do not provide five-year age groups of January 1 2020 yet, and beware that there are different subgroups of 95+.

Disclaimer. Limited earlier experience in research on infectious diseases

In 2002-2004 I collaborated at Erasmus Medical Center on the modeling of the Human Papilloma Virus (HPV) as the cause of cervical cancer. My background in modeling and also logistics was relevant because diseases may look like a Markov logistics process with stages and transition probabilities. There can be the same issues of test reliability, criteria of lives-saved or life-years-gained, and cost-effectiveness of screening and treatment. I also followed the discussion about the SARS epidemic of 2003. My period at Erasmus MC was too short to allow for publishing peer reviewed papers but let me mention two working papers.

  1. Working paper 2004: Modifying behaviour with a passport. At that time there was no HPV-vaccine yet. An option was to manage human behaviour. The status of infection can be recorded in the medical dossier: free (green) or carrier (red). While children can gets warts, an assumption might be that children start out uninfected by the harmful HPV variants (status green). When couples meet and want to get into a serious relationship – in the sense of sharing their germs – then they can show each other their status of infection in their medical dossier and discuss the implications. From this working paper, we may take the idea of recording the status of infection, and using colour coding for clear communication. For Covid-19, it is better to use “red” (alarm, or hungry in Chinese restaurants) for the barrier between zones and groups.
  2. Working paper 2003: On the value of life. This compares the lives-saved and life-years-gained measures, and develops a compromise: a “unit-square-root” measure, that regards each life as 100% and takes the square root of the relative gain. This is discussed in the former weblog entry.

The national lockdown causes the “collateral deaths” of persons who would normally receive care but who remain untreated. The Dutch Volkskrant newspaper reports that 40% of normal hospital care has been cancelled.

  • People with a disease are vulnerable to Covid-19 and may fear a greater risk of infection within the health system itself.
  • Health care resources are reallocated from normal care to Covid-19 related cases. The latter can be rational, given that untreated infections are a risk for the whole population.

This shift in the burden of disease and death might be acceptable to a large extent. We must compare these “collateral deaths” to the “avoided deaths by treating those with infections“. However, at issue is whether some elements in this shift of the burden are dubious. We can understand these aspects a bit better when we have a better grasp of what is called “the value of life”.

Below, I will discuss a particular theoretical case of “collateral death”:

Consider a person of 20 years of age, with a potential gain of 60 additional years of living, who might not get proper treatment because the Intensive Care Units (ICU) are occupied with Covid-19 patients, who are elderly and might perhaps gain 10 more years of living. PM. Women in Holland at age 80 still have a life expectancy of a bit more than 9 years on average (statline). (It is not known whether this changes or whether they will have a full recovery from Covid-19.)

There is my 2003 working paper: On the value of life. This compares the lives-saved and life-years-gained measures, and develops a compromise: a “unit-square-root” measure. This regards each life as 100% and takes the square root of the relative gain – see below. The paper was intended for macro-economic issues and not for triage at the micro-level, but let us now investigate how it would work at the micro-level. PM. Said paper still suffers a lot from being a working paper, and requires much editing for readability.

Let us first look briefly at the flu and then proceed with above theoretical case at the ICU.

Relation to the flu

RIVM provides the following data for two flu-periods in Holland. Rather than the infection fatality factor (IFF) (deaths per infected) we have the symptomatic case fatality factor (sCFF) (deaths per symptomatic). A well-known statement is that the flu is “an old man’s friend” – but this is disputed by some. I did not find the percentage at ICU. The Dutch health system is accustomed to the flu and some categories of (elderly) patients with the flu and comorbidity are no longer sent to the ICU.

Table 1. Flu incidence in Holland 2017-2019

RIVM data

Winter 2017 – 2018

Winter 2018 – 2019

Length of period (weeks)

18

14

Reported symptomatic people

900,000

400,000

Hospitalisation

16,000

10,000

Surplus deaths

9,500

2,900

Symptomatic Case Fatality Factor (sCFF)

1.05%

0.73%

Covid-19 is “at least ten times deadlier than the regular flu” (quote) – a recent estimate is 7 times – and likely more contagious and more prone to mutation. At issue is whether the properties of Covid-19 warrant a different treatment at the ICU as is happening in these weeks. The Dutch health system is not accustomed to Covid-19 yet, and very likely they now admit Covid-19 patients who would not be admitted in the future. Let us consider the admission criterion.

The ICU admission criterion

Dutch ICU currently have the “incremental probability of survival” admission rule (document). This is the Δp = p b between the probability of survival of the treatment at the ICU (p) and the probability of surviving not at the ICU (b = background risk). Observe:

  • Patients with Covid-19 tend to have a worse Δp at the ICU than similarly diseased patients without Covid-19. Normally, we would not see many people with Covid-19 at the ICU (with comorbidity). Apparently, the health care system is not used to Covid-19 yet. They try to save patients who in retrospect wouldn’t have a chance at admission. (An aspect is that it is reported that 80% of the patients requiring breathing machines are overweight – an aspect of the obesitas health crisis.)
  • A comparable situation exists with influenza. I did not find a report about the use of ICU for flu patients. Quite likely, the availability of beds made it possible in the past that also categories of patients with influenza were admitted, also with comorbidity. The difference with Covid-19 is the increase in the case fatality factor – but this points to fewer admissions.
  • However, people have little reason to go to the hospital when they will not be treated. Untreated infections are a risk for others and thus it is better to present some scope for treatment. Keeping patients at the ICU is a form of quarantine, though an expensive one.

My 2003 paper On the value of life assumed a p = 100% chance of success of treatment (with a known subsequent life expectancy). Let us now discuss the case with a different value of p.

PM. The term “lives saved” might be emotionally biased. It seems better to say “lives extended”. Eventually everyone dies, and the term “lives extended” indicates that the important information of “how much” is not mentioned.

A treatment criterion in general

The general setup is: (i) maximise performance given costs, or (ii) minimise costs given a level of performance. Public Health budgets tend to be given, so we choose the first approach.

Let there be two types of treated patients in numbers n1 and n2. We select these treated numbers from the pools waiting for treatment n*1 and n*2. Costs of treatment per patient are c1 and c2, for example because of different lengths of stay at the ICU. Available resources are C, and these can be time of medical personel or plain costs. The probabilities of success are p1 and p2, with performance outcomes s1 and s2. All variables are nonnegative.

We can impose an additional (moral) condition that one type of patient gets a weight λ. The weight λ means that a person in that group in the new objective function becomes λ times as important as a person in that same group in the old situation. The effect depends upon the success criterion, see below. Sometimes this condition is imposed by making different beds for different types of patients. We might also manipulate the pool sizes. When a pool of cheap patients with a high treatment score is large, so that they get all the treatments, we may restrict the pool size in order to allow treatments for the other type.

The above gives the linear programming model for the variables n1 and n2:

Maximise    p1.s1.n1 + λ p2.s2.n2

Subject to  n1 ≤ n*1    and    n2 ≤ n*2    and    c1.n1 + c2.n2 ≤ C

The following diagram presents the C-simplex and the feasible region restricted to the n* pool-variables. Due to linearity, the objective function will tend to select one of the end-points. The shown optimal point is {n°1, n*2}. When the objective function and the feasible region have the same slope, then –c1/c2 = – p1.s1 / (λ* p2.s2), and λ* = s1/s2 (p1/p2) / (c1/c2). In this case we would select patients at random, but still keep representative numbers for the types of patients.

Figure. Linear programming for triage

Let us use this model for the theoretical example case from above, namely of the patient of 20 years without Covid-19 and the patient of 80 years with Covid-19. Let type 1 be the youngsters and type 2 be the elderly.

Simplification by using costed-patients

Each type of patient comes with a standard cost, and the linear programming problem becomes a bit more tractable by using this constancy.  Above problem can be simplified by looking at “costed-patients” qi = ci.ni. The conditions on the pool size become qi = ci.nici.n*i = q*i. Then we get:

Maximise (p1.s1/c1) q1 + λ (p2.s2/c2) q2

Subject to q1 ≤ q*1 and q2 ≤ q*2 and q1 + q2 ≤ C

For this formulation it may be easier to calculate the randomisation value of λ* = (p1.s1/c1) / (p2.s2/c2).

Since the maximand can be scaled arbitrarily, we may divide by the coefficient of the second group, and get this expression, so that it is fully clear that taking λ = λ* gives a maximand that is parallel to the cost condition. The shadow price of the cost condition will be max[λ , λ *].

Maximise    λ* q1 + λ q2

Subject to q1 ≤ q*1 and q2 ≤ q*2 and q1 + q2 ≤ C

Cohort size

The “direct gain ratio” is s1 / s2. For lives-extended, the direct gain ratio is 1 / 1 = 1, while for life-years gained above example gives 60 / 10 = 6, meaning that treating one younger person successfully gives the same effect as treating 6 elderly persons successfully.

By comparison λ* is the “effective gain ratio”, in which the direct gain ratio is corrected for the relative risk p1/p2 and the relative cost of treatment. The effective gain ratio means that treating 1 younger person (with the given chance of success) has the same effect as treating λ* elderly patients (with their chance of success) (and excluding the manipulation with λ).

Assuming that all costs are depleted, we can write c1.n1 + c2.n2 = as n2 (c1.n1/n2 + c2) = C. Taking μ = n1 / n2 as the “selected ratio”, then we can take a single cohort as consisting of μ youngsters + 1 elderly, or μ  + 1 persons. The cost per cohort is k = c1 μ + c2 = C / n2, using that there are n2 cohorts.

While above manipulation of choosing λ at λ* obviously can be done, it still leaves the problem of randomisation. The manipulation of the maximand is not so effective in this kind of problem. It is more effective to manipulate the pool of youngsters n*1. Above we tended to assume that this pool was exogenously given, but when this pool is so large that they claim all treatments, and we want to put a limit to this, then we effectively reduce the pool size. A relevant variable to consider is the selected ratio μ or the composition of the cohorts. If μ is chosen, then n2 = C / k, and then n*1 = n1 = μ n2 = μ C / k = μ C / (c1 μ + c2).

The choices of λ and μ are different since they apply at different aspects of the problem, i.e. the maximand or the boundary condition. Yet we can conceive of some combination. The value of λ does not always mean a representative cohort size. Only when the slopes happen to be equal and there is randomisation, then, in some cases, we might first treat μ = λ* youngsters before treating an elderly patient again (which single person also weighs as λ*).

Case 1. Using mortality only

The success criterion of lives-extended gives s1 = s2 = 1. The objective function is parallel to the feasible region when λ = λ*[lives] = (p1/p2) / (c1/c2), or p1 / p2 = λ c1 / c2.

The “incremental probability of survival” is a subcase that only compares p1 and p2.  This neglects costs, or sets c1 = c2, e.g. neglecting duration of treatment, or in fact sets λ = c2 / c1, i.e. compensating for duration of treatment (so that there is randomisation when the two probabilities are equal). The rule is also silent about the pool sizes. (In practice ICU have more criteria, with some implied λ.)

We would not discriminate patients when λ = 1, i.e. without additional moral judgement and when only the lives-extended criterion and the parameter values determine who is to live and who not. (We do not decide who dies: nature does.) The choice of  λ = 1 still allows for the happenstance that the slopes would be equal by chance. For example, when the younger person costs 2 financial units (or weeks) and the older person costs 3, then the slopes are the same when the survival probabilities have the same ratio: p1 = 2/3 p2. For other values of the survival probabilities, however, one type of patient is preferred to the other type.

E.g. when p1 = 0.80% and p2 = 0.51%, the maximand is 0.80 n1 + 0.51 n2 or 0.40 q1 + 0.17 q2, and then clearly the first type will be preferred. Only an additional quantitative restriction n*1 might prevent the neglect of all patients of type 2.

For another value than λ = 1, the objective function is 0.40 q1 + λ 0.17 q2. We randomise if λ = λ* = 40 / 17 = 2.35. This means that one old patient in the new maximand is valued as 2.35 old patients in the original maximand. If we take λ* as the cohort parameter μ, then after randomly choosing 2.35 youngsters, we would randomly choose 1 person from the elderly (who has weight 2.35 too).

The lives-extended measure neglects the “how much” of the life-expectancies.

Case 2. Using life-years-gained

The success criterion using life-years-gained gives s1 = 60 and s2 = 10. We find λ = λ[lys] = 60 / 10 (p1/p2) / (c1/c2) = 6 λ[lives].

We may also find the maximand of 24 q1 + λ 1.7 q2, and the objective function is parallel to the feasible region for λ*[lys] = 24 / 1.7 = 14.1. The latter means that 1 old person in the new maximand counts as 14.1 old persons in the original maximand. Perhaps with a bit more freedom, we might say that 1 year of life for an elderly person counts as 14.1 years for a younger person. For the cohort size, we might treat μ = λ* = 14 youngsters and then treat an elderly person (who counts as 14 too).

PM. The 10 life-years actually gained for an elderly person are regarded in the new maximand as 14.1 * 10 = 141 life-years gained. This reflects 141 / 60 = 2.35 youngsters. But the elderly are not really such youngsters, and we must also account for the the effect of the other parameters.

The life-years-saved criterion is biased in age and sex: it gives advantage to the young and women. Both criteria of lives-extended and life-years-gained have their drawbacks. There is scope for a compromise.

Case 3. Unit-square-root measure

The unit-square-root (UnitSqrt) measure uses:

a = age

d = life expectancy with disease, without treatment (for the ICU: d = 0)

x = expected life-years-gained when treatment is successful

patient score = Sqrt[x] / Sqrt[a + d + x] = Sqrt[x / (a + d + x)]

Substituting all parameter values gives the maximand 34.6 q1 + λ 5.7 q2.

For above young person the score is Sqrt[60 / (20 + 60)] = 0.866. Above Covid-19 patient has Sqrt[10 / (80 + 10)] = 0.333. We get λ = λ[sqrt] = 0.866 / 0.333  (p1/p2) / (c1/c2) = 2.6 λ[lives]. We thus have a compromise value between the ratio of only survival 1 / 1 = 1 and the ratio of life-years of 60 / 10 = 6, namely 0.866 / 0.333 = 2.6. For the example case, the “middle of the road” character of the UnitSqrt measure also shows from the randomisation value of λ* = 6.1: this lies between the earlier other two values of 2.4 and 14.1.

Collecting results

We can tabulate our findings for the discussed example. Obviously, this table applies to this particular example only. There can be quite some discussion about what kind of success measure, and possible “correction” or “discrimination” by means of the n* and λ and μ. In practice, an ICU may have quite different reasoning as well, like on the availability of medical personel for particular treatments.

While it remains possible to select one of these objective functions and be neutral with λ = 1, and allow an extreme outcome (except for the happenstance of parallel lines), it seems more likely, as said, that the more relevant choice concerns the cohort size μ + 1. Above discussion gives considerations for a reasoned choice of μ as one of the “gain ratio’s” mentioned in the table. Above discussion suggests the compromise value, for this particular example case, of μ = 6, i.e. treat first 6 youngsters of said type and then treat an elderly person of said other type.

Table 2. Comparing success measures for triage, a = {20, 80} and x = {60, 10}

p = {0.80, 0.51}
c = {2, 3}
Lives extended
Life-years gained
Unit square root
Success measure s = {1, 1} s = {60, 10} = x s = Sqrt[x / (a + d + x)]
Direct gain ratio (only s1/s2) 1 / 1 = 1 60 / 10 = 6 0.866 / 0.333 = 2.6
Maximand 80 n1 + λ 51 n2

40 q1 + λ 17 q2

48 n1 + λ 5.1 n2

24 q1 + λ 1.7 q2

69.3 n1 + λ 16.9 n2

34.6 q1 + λ 5.7 q2

Weight formula
λ[lives] λ[lys] = 6 λ [lives] λ[sqrt] = 2.6 λ[lives].
Randomisation,

Effective gain ratio (λ*)

λ* = 40 / 17 = 2.35 λ* = 24 / 1.7 = 14.1 λ* = 34.6 / 5.7 = 6.1

Queuing

The 2003 paper originated from a macro-economic context of the allocation of the budget over different types of treatment. At the micro-level, a hospital is faced with a queue of patients with all their own characteristics of age a, life expectation d, effect of treatment x, now extended with probabilities and costs c. We could order patients on their costed scores p / c Sqrt[/ (a + d + x)], and apply a λ per category. Obviously this is only a suggestion from theory.

Conclusions

Some conclusions are:

  1. The 2003 paper did not look at a probability of survival p other than 100%, and now we have found an useful adaptation, namely above maximand with the LP properties.
  2. The current admission criterion for the ICU of “incremental probability of survival” would tend to favour youngsters because of their better conditions and survival probabilities. The current admission of many elderly Covid-19 patients must derive from other considerations, like inexperience with Covid-19 and the effect on quarantine and containment. The creation of additional ICU beds might be seen as additional only.
  3. The admission criterion of the “incremental probability of survival” looks at “lives saved”, or rather “lives extended”. This causes questions about cost comparisons (e.g. length of stay at the ICU), pool sizes (n*) and moral values (λ). Switching to “life-years gained” comes with a larger information load and partly provides answers to those questions, but also causes more questions, since this criterion is biased on age and sex. The UnitSqrt measure takes each life as 100% and would remove the latter bias. It would eliminate this aspect in the choice of λ (except for the choice of other functions than the square root), so that its choice would be more dependent upon the parameters on costs and survival probabilities.
  4. While the original paper derived from the macro context, and this present weblog entry explored the micro context, the latter also highlights that the present public discussion about Covid-19 deaths does not yet consider the aspects on the life-years. The latter will be required for an evaluation of the wider consequences, like on the “collateral deaths” and on how to “prepare for the second wave”. However, the life-years are a biased criterion and it would seem to be advisable to see more statistics that use the unit square root too.

Disclaimer

(1) In 2002-2004 I collaborated at Erasmus Medical Center on the modeling of the Human Papilloma Virus (HPV) as the cause of cervical cancer. My background in modeling and also logistics was relevant because diseases may look like a Markov logistics process with stages and transition probabilities. There can be the same issues about test reliability, criteria of lives-extended and life-years-gained, and cost-effectiveness of screening and treatment. I also followed the discussion about the SARS epidemic of 2003. My period at Erasmus MC was too short to send in papers for peer review. (2) Now I am an elderly male and advantaged by the lives-extended and disadvantaged by the life-years criterion.

PM.

PM 1. We did not use “quality adjusted life-years” (qaly). The application with the UnitSqrt would be the same but the information load would be larger, and likely not available at an ICU.

PM 2. A bit more about the additive character in this weighted averaging: The current setup is that the patient with age a has a life expectancy of d without treatment, and supposedly also when the treatment would fail. If d = 0 then p is the acute probability of survival due to the treatment (relevant for an ICU). Some possible variants provide an indication that above linear weighted averaging is the relevant approach.

  • xeabt = p (xd) + (1 – pd = p x + d is the life expectation when admitted but before the treatment. This variable is less useful, see PM 3. Also Sqrt[p x / (a + d + p x)] for this state is not so useful.
  • scorexp = p Sqrt[x / (a + d + x)] + (1 – p) Sqrt[0 / (a + d + 0) is the expected score (relevant)

PM 3. Suppose that the outcome measures at failure are f1 and f2, and that s1 and s2 are measured incremental to such failure. Then we might consider maximising the total effect:

Maximise    {p1.(s1 + f1) + (1 – p1).f1}  n1 + {p2.(s2 + f2) + (1 – p2).f2}  n2

Which becomes:

Maximise    p1.s1.n1 + p2.s2.n2  + f1.n1 + f2.n2

With this maximand, there is a bias towards patients who would already have a good score when the treatment fails. This maximand is not the relevant one, because the failure outcome does not depend upon the treatment. Another maximand would include the background risk b, but this is also not affected by the treatment.

To the International Association for Official Statistics (IAOS),
Royal Statistical Society (RSS),
American Statistical Association (ASA),
Société Française de Statistique (SFdS) and
International Association for Research in Income and Wealth (IARIW)

Dear presidents Pullinger (IAOS), Ashby (RSS), Martinez (ASA), Marin (SFdS) and Reinsdorf (IARIW),

Your societies and associations have made public statements in support of Andreas Georgiou, former president of El.Stat Statistics Greece.

I have looked at the case and arrived at the conclusion that Georgiou was guilty as charged for the violation of duty, as was indeed confirmed by the Greek Supreme Court in 2018. It appears that Andreas Georgiou, Hallgrimur Snorrason (representative of Eurostat at El.Stat in 2010) and Walter Radermacher (Eurostat 2008-2016) have provided you with false testimonies about the Greek law of March 9 2010 that created El.Stat and the European Code of Practice of 2005 that was in force in 2010. They knew about the true legal situation and in fact worked to make changes in both the law (December 2010) and the Code (2011).

The documentation is in my new book “Forum Theory & A National Assembly of Science and Learning“. My discussion of the actual figures in national accounting of Greece 2009 is on pages 200-206, and there seem to have been made some arbitrary choices that are not fully clear to me. My discussion identifies many more points where important information is lacking. Overall, I advise that there will be a thorough investigation. I hope that you will indeed apply due diligence.

I already informed ISI and FENStatS via this letter, now online in slightly edited form to make it quotable for others. I regard the now online letter to ISI and FENStatS as an integral part of my letter to you now. I have the same requests for you as stated in that letter. Please inform your membership but please refer to my book instead of trying to rephrase the points in your own words because points might get lost in translation again. This letter to you is online now too.

Reading parts of my book, Richard Gill, emeritus professor in mathematical statistics in Leiden, and former chair of VVSOR (a founding member of FENStatS), informed me that he has revised his view, from an earlier signing of support to a (now disputed) statement by ISI. Klaus Kastner, retired banker who blogs on Greece, also has revised part of his view.

My disclaimer: I would like to see a thorough investigation in Dutch economics.

Sincerely yours,

Thomas Cool / Thomas Colignatus
Econometrician (Groningen 1982) and teacher of mathematics (Leiden 2008)
Scheveningen, Holland
http://thomascool.eu/
http://econpapers.repec.org/RAS/pco170.htm
https://zenodo.org/communities/re-engineering-math-ed

PS. At IARIW, Peter van de Ven (formerly CBS now OECD) was IARIW president in 2010-2012, when the issue of El.Stat case arose. Van de Ven proposed to IARIW in 2016 to support Georgiou, apparently with deficient study of the underlying events. At CBS in 2009, Van de Ven removed the Tinbergen & Hueting figure of environmentally Sustainable National Income (eSNI) from the Dutch monitor on sustainability, using fallacies, see THAENAES Chapter 25 p289. I copy to Van de Ven at OECD and Kees Zeelenberg at CBS who is involved in IAOS – OECD.

To the President of [the International Statistical Institute (ISI)] and the secretary general of [the Federation of European National Statistical Societies (FENStatS)]

Dear professor Bailer (ISI) and dr Silva (FENStatS),

There is this new (open access) book by me:

Forum Theory & A National Assembly of Science and Learning

The idea is that scientists and scholars create an assembly of their own, to improve the quality and impact of science and learning. The book discusses various problems. Some main problems are about national accounting and official statistics. There is the Tinbergen & Hueting approach on environmentally Sustainable National Income (eSNI). There is the El.Stat / Georgiou case.

The book webpage is [here].

The PDF of the book is open access [here].

A short text (discussing 2 of 7 storylines) is [here (pdf)].

Though the Tinbergen & Hueting case is much more important, it so happens that ISI and 80 former chief statisticians around [IAOS and FENStatS] put out statements of support for Georgiou, and it may be that you are alerted on this problem in more accessible manner just now.

Allow me to invite you to look at my deconstruction of “Greek statistics” in Part 6, starting p153.

My diagnosis is that the statistical associations, including you, have been misinformed by Walter Radermacher (Eurostat and current president of FENStatS), Hallgrimur Snorrason (representative of Eurostat and associated with ISI) and Andreas Georgiou (El.Stat). They knew in 2010 that the Greek law was that Georgiou had to seek approval by his board. He is guilty as charged for the conviction of violation of duty. I copy to them but do not have the email address of Georgiou.

One might regard this as an old case, but Eurostat also arranged that the National Statistical Offices of the EU are now under a single head, while CBS Statistics Netherlands since 1892 was under supervision by a multiperson board. This change in governance has risks for the future. My book indicates that CBS likely did not protest strongly enough because the Dutch government managed to appoint a leadership that had no background in official statistics itself.

Since the Part on “Greek statistics” is lengthy, let me also point to p200-206 for some formulas en tables on the calculation of the 2009 debt and deficit.

[…] Richard Gill, former chair of [VVSOR] (a founding association of FENStatS), already informed me that he revised his opinion now (from signing an earlier ISI statement), see below under (1). (PM. I copy to Fred van Eeuwijk, current [chair] of [VVSOR].) Klaus Kastner, a retired banker who blogs on Greece, also has revised part of his view, see under (2). They may not have digested my book fully since it is just in print.

I already informed Walter Radermacher about my finding, since his background is in environmental statistics, and around 1990 he had friendly contacts with Roefie Hueting. Unfortunately, Radermacher did not comprehend the Tinbergen & Hueting approach, and has misrepresented it too. My criticism on the work by Radermacher is restricted to these two issues that I have looked at. I [expect him] to correct when errors are clarified to him. While I informed Radermacher earlier this week, he indicated that he had no time for this, and this is a complication.

Another complication is that Radermacher currently is the President of FENStatS. The Vice-President of FENStats is professor Maurizio Vichi, who also happens to be the thesis supervisor for the Radermacher thesis of 2019. I checked the thesis on the two issues of eSNI and the Georgiou affair. In my judgement, the thesis is biased and misrepresenting on these two issues. It should be retracted. Radermacher knew in 2010 that Georgiou was in violation of the Greek law, and as director of Eurostat assisted him in breaking the law of an EU Member State. He should have insisted that Georgiou would come clean with his board instead of helping him to bypass them. Subsequently, see my discussion of the actual debt and deficit calculations.

Thus, my request to Radermacher and Vichi and FENStatS is that Radermacher and Vichi step down from their positions at FENStatS, to that there is no conflict of interests between FENStatS and their positions on the thesis and Radermacher’s position in this case ueberhaupt. Hopefully Radermacher might reorganise his priorities and consider the criticism in my book.

After sending this email to you, I will relay it to some journalists, so please do not be surprised if they would contact you and know about this email. It also seems best that I include this email on my website, and check there for the upcoming link.

Earlier, see under (3), I already informed the DG CBS dr. Tjark Tjin-A-Tsoi about my book, and the finding that the erroneous ISI declaration had also been signed by some CBS researchers who had failed to check upon the Greek law, European Code of Practice 2005 [in force in 2010], and the particular data, and the false testimonies by Georgiou, Snorrason and Radermacher. I have been supplying the DG CBS with drafts of my book in the last month[s], and I offered CBS a final week to consider the argument, and provide for a more structured approach in informing the world of statistics about my book and finding. Alas, CBS did not indicate to me that they would take this opportunity. Thus, I am left with no other option than inform the world of statistics myself. The most efficient way to do so, at least for me, likely is to inform the media, though generally the media can be quite chaotic overall.

Let me also express that I am very annoyed concerning ISI. In 2012 I wrote to ISI with a request of an investigation, in which there was also attention for the views of the (other) board members. Instead, ISI apparently listened only to Snorrason at ISI. It strikes me as very unprofessional to allow someone to be judge in his or her own case. In BCC I will copy to some former El.Stat board members. My 2012 letter to ISI is [here].

Let me also express my [appreciation] to CBS for inviting Hueting and De Boer in 2019 to present their new book on national accounting and eSNI, which lecture was attended by some sixty statisticians at CBS. CBS also made a video (in Dutch) available, and since De Boer was late I myself had to step in for a moment. We must clearly distinguish the open and unencumbered discussion of issues on content at the “statistics work floor” and the issues of governance and management which gain more attention in my book. The link to the Hueting & De Boer lecture in 2019 is [here].

If you were to write on this, then my advice to you is to inform me with a draft text, to allow me to comment on possible errors. Please revise your (online) texts that contain erroneous statements, by heading them with clearly visible “Retracted, see link…” while keeping the remainder “as is” so that others can check the history of your errors. Please send your apologies to the Greek government, with copies to the press, for trying to infringe upon the separation of powers. Please inform your membership about this email and my book. Please do not try to restate my book in your own words, thereby taking attention away from my book, but simply correct and refer to the book for the details. Please respect my analysis that the Greek case is only an example, while the real issue is the creation of said assemblies, that also are intended for a better anchor for future governance of official statistics.

Sincerely yours,

Thomas Cool / Thomas Colignatus
Econometrician (Groningen 1982) and teacher of mathematics (Leiden 2008)
Scheveningen, Holland
http://thomascool.eu/
http://econpapers.repec.org/RAS/pco170.htm
https://zenodo.org/communities/re-engineering-math-ed

(1) ================================

From: Richard Gill
To: Thomas Cool / Thomas Colignatus
Cc: […]
Subject: Re: N.a.v. uw ondertekening van de ISI verklaring uit 2013 over Andreas Georgiou
Date: Sun, 26 Jan 2020

Ik wil best zeggen dat mijn mening veranderd is. Ik heb het gezegd. Je mag me citeren.

(2) ================================

https://klauskastner.blogspot.com/2020/02/andreas-georgiou-was-it-breach-of-trust.html

(3) ================================

Date: Sun, 09 Feb 2020
To: DG CBS dr. T. Tjin-A-Tsoi, Kees Zeelenberg, […]
From: Thomas Cool / Thomas Colignatus
Subject: Published “Forum Theory & A National Assembly of Science and Learning”

Dear dr Tjin-A-Tsoi and dr. Zeelenberg and […],

My book is now online for all:

Forum Theory & A National Assembly of Science and Learning

[pdf relocated]

The printshop will take some more days.

You might enjoy the national accounting on page 200-206. I just included this this weekend, while finishing the book, and it appears that finishing touches can be quite important.

If you would have comments, feel welcome to send them. I can include additions and corrections in a file with “Reading Notes”, and eventually there might be a 2nd edition.

Let me call your attention to some CBS employees mentioned on p292 who did not properly check the Georgiou case and who signed the erroneous ISI declaration. Allow me to request the DG to forward this email to them. […] is an appreciated contact of mine from the student days in Groningen, and I send him my regards.

I also wonder whether you would have some advice as to how to approach the world of official statistics on this book and its findings. It is easy for me to dispatch some emails to some of the associations and persons involved. It might be less effective and needlessly chaotic. If there would be scope that the CBS would take a week to digest the book and formulate a statement, and be willing to discuss the draft of the statemnet with me (with me only giving advice), then this would seem to be advisable. Please let me know in the coming days whether you would be willing to do so.

Sincerely yours,

Thomas Cool / Thomas Colignatus
Econometrician (Groningen 1982) and teacher of mathematics (Leiden 2008)
Scheveningen, Holland
http://thomascool.eu/
http://econpapers.repec.org/RAS/pco170.htm
https://zenodo.org/communities/re-engineering-math-ed

Science and scholarship are much appreciated in our societies when we consider the lavish funding by tax payers and private donors. In contrast there is also a structurally weak position in the very functioning of our democracy. Our best research minds are allowed to discover the wonders at the frontier of knowledge but their findings might not be actually used. In examples like climate change, overpopulation, miseducation, inequality, political science of electoral systems, and the revolutions in computing, biology and medicine, and so on, and even in the issue of Greek statistics of the national debt and deficit of Greece around 2009, we see that science and learning are hardly listened to, and that policy makers and opinion leaders follow their own illusions, leading the world towards foreseeable disasters. Humanity as a whole acts mindless, drunk or crazy.

Trias Politica versus Tessares Politica

There is a system to the madness. Our democracy has the Trias Politica separation of powers between de Executive, Legislative, and Judiciary branches of government. What is lacking is the Epistemic branch. This means that the Trias Politica model allows too much room for manipulation of information. The alternative is a High Definition Democracy that has this Epistemic branch to protect information. This would give a Tessares Politica – from the ancient Greek “foursome”.

Epistemic branch

The Epistemic branch has two elements.

  • The first aspect concerns economic planning and the management of the State. The national budget is crucial for policy making. The Legislative branch or Parliament votes on the national budget to authorise the Executive to tax and spend funds. The economic planning agency resides currently under the Executive. However, planning is systematically abused. We better create an Economic Supreme Court at the same constitutional level, with the task to control the quality of information, and the power to veto the budget if it contains misleading information according to the court. This leaves all freedom for politicians to determine policy but they will lose the room they have now for manipulating information.
  • The second aspect concerns all fields of research. Parliament currently has the Senate and the House of Commons. In the French Revolution of 1789 the Chamber of the Clergy was abolished. In an alternative path of history, the clergy could have developed into scientists and scholars, and the revolution avoided, and then nowadays we would have a Chamber for Science and Learning.

If we want to improve the world and democracy then these are the two structural positions to consider.

Forum Theory

Forum theory is the approach by the Dutch cognitive psychologist, student-achievement tester, methodologist and philosopher of science Adriaan de Groot (1914-2006), also famous for his study of chess grandmasters. Forum theory provides us with the diagnosis that science and learning operate as a forum, i.e. a market subject to particular conditions. The approach investigates processes that enhance quality of science and learning, and formulates ways to protect and encourage those. Forum theory suggests that science and learning will be improved by a National Assembly. This contrasts with the current dominance by the National Academies of Science and Scholarship.

Such Academies tend to consists of mainly elderly researchers who have made their mark years ago and who are selected by co-optation. This leaves the mass of researchers out of the picture, currently at the front of research and making their mark. The common researchers on the work floor, e.g. in the laboratory or at the computer terminal, are locked up between a stone wall and a firy pit, and tend to be quite frustrated that the existing knowledge is neglected or misrepresented by politics, while the elevated colleagues at the Academy tend to focus on their next conference. Jonathan Swift (1667-1745) in his Gulliver’s Travels already made fun of the Royal Society.

This situation can be changed by the creation of a National Assembly of Science and Learning, with a Floor for the mass of researchers, while the National Academy forms the Senate of the Assembly. The Assembly improves governance of the forum, the forum itself, and research integrity. Researchers in science and learning can create their National Assembly actually quite simply. They can set up a foundation, give rules of operation, recruit members, organise elections and have a constitutional meeting. With sufficiently large membership the operating costs can be covered. The next step is to show results.

The difference between the current Academy and the sketched Assembly is that the latter has the full weight of the collected research body in a country, with the legitimacy of having been elected by them. The Assembly can do investigations and support conclusions, and speak for science and learning with an authority that now is lacking for the Academy. Over time Parliament could accept the National Assembly of Science and Learning as its third chamber, e.g. called The Study.

Greek national accounting and statistics in 2010

My book with above analysis and proposal also looks at the example of 2010, when Statistics Greece (El.Stat) director Andreas Georgiou sent figures on the 2009 Greek national debt and budget deficit to Eurostat without first seeking approval by his board. The Greek court system judged that he was in violation of duty, irrevocably by the Greek Supreme Court in 2018. Today there is an international uproar in national accounting and statistics that Georgiou’s conviction is a miscarriage of justice and an attack on the independence of Official Statistics.

However, these protesting statistical societies and associations have failed to check the Greek law of March 2010 that created El.Stat, and they also refer to the European Statistics Code of Practice of 2011 or 2017 while the code in force in 2010 was from 2005. Georgiou is guilty as charged.

By all looks of it, he also – advised by Eurostat – added the Simitis swaps of 2001 to the deficits, thus increasing the deficit of 2009 by about 2% points, instead of using the proper stock-flow adjustment. The deficit figure has the purpose to show the operating difference between income and expenditure, and is not the place to record hidden debts that fall from the closet. It is remarkable that these sobering points have not been recognised in all comments and protests. Also the Financial Times and the Wall Street Journal supported Georgiou while overlooking these facts.

People can bet their reputation on false information though. Georgiou and the leadership of Eurostat knew about the Greek law of March 2010 and the Code of Practice of 2005, because it was their job to know this at the time. In 2010 they even undertook a change of those very regulations. They however did not say so to the courts and their international colleagues.

Instead, board member and professor of econometrics Zoe Georganta, while lacking full information because of Georgiou’s obstruction, still pointed to crucial questions on content, and those were considered by the Greek courts but inadequately treated by those protesting statisticians and media.

Impact on the EU statistical system

Cause for worry is that the European Union has now restructured its statistical system so that each national statistical office has a single head with full authority, while we know that a single person is much more sensitive to political or commercial pressure or own illusions than a multiperson board.

Warranting the quality of scientific and learned information

This is one of more information scandals that my book deconstructs. The Greek case is peanuts compared to the discussion about climate change. Overall, the world is served not only by a better position of science and learning in our system of democracy, but also by a better internal functioning of the forum of science and learning itself. There is a clear need for a National Assembly of Science and Learning that can investigate such issues without interference by political interests and mistaken hierarchies that exist now.

Thomas Colignatus is the scientific name of Thomas Cool (1954), econometrician (Groningen 1982) and teacher of mathematics (Leiden 2008). See the book “Forum Theory & A National Assembly of Science and Learning” (2020) at https://mpra.ub.uni-muenchen.de/98568 and on his website http://thomascool.eu

Today, January 31 2020, at midnight Central European Time, Brexit will happen, even though it is unclear what the British voters think about it. Brexit is neither “by the will of the people” nor “against the will of the people” but merely “without the will of the people“.

A proto-democracy generates uncertainty

The UK is only a proto-democracy and no proper democracy, see this evaluation in the APS Newsletter Physics and Society, January 2020, p18-24, which looks at the USA but the argument for the UK is quite similar.

On Brexit, uncertainty abounds:

  • The Brexit Referendum Question of 2016 was a political manipulation and unacceptable for a decent statistical questionnaire, see here p14. The situation was “garbage in, garbage out”, with ample opportunity for populism.
  • The UK preferences were rather dispersed about the options for Leave or Remain, see here p6.
  • See my summary about Brexit’s deep roots in confusion on democracy and statistics p18.
  • The UK election of December 12 was for the House of Parliament and not about Brexit. Boris Johnson had all candidates for the Conservative Party pledge to support Brexit, which runs against the principle that members of the House must represent their district. These elections thus violate the very principle of the UK proto-democracy.

The UK proto-democracy has “district representation” with “first past the post“, which means that a party may get a majority in the House of Parliament without a majority in the electorate. In the UK 44% voted for the conservatives but they still got 56% of the seats. Thus 56% of the UK voters do not want a government by the Conservatives.

Thus we still do not know what voters think about Brexit too. While Brexit was much discussed, and caused voters to switch to the Conservative Party, it still was not the only issue on the table, and it still is unclear what voters think about Brexit on balance.

The UK has the curious phenomenon of the “Re-Leavers”. These voters chose Remain in 2016 but now switch to Leave merely because this was the majority outcome in the referendum, and they “want to respect the outcome”. However, this is not how democracy works. A vote is about what you think yourself and not about what the former outcome was. Obviously these Re-Leavers are free to exercise their democratic right to think whatever they want, but this kind of thinking destroys the possibility to determine what people actually want.

YouGov tracker

The YouGov tracker is the best summary information about the general sentiment on the issue, but it is a poll and no electoral statement. Let me quote the tracking at this moment, because it always changes:

Between party dynamics

Adam McDonnell and Chris Curtis of YouGov discuss a post-election survey of December 17 2019, and here are their underlying data (for us page 3). The dynamics between the UK parties are remarkably large. Their key graph for our purposes is the following. For example 27% (figure not printed) of the Conservatives voted Remain in 2016: 22% (shown) of those switch to the LibDem, likely because LibDem are Remain. However, 65% of the Remain Conservatives stick to their party, perhaps because they regard the issue less relevant than other issue of the Conservatives, or perhaps they are ReLeavers. Of the LibDem who voted Leave in 2016 still 46% voted LibDem though it had become a Remain party, perhaps because they thought that LibDem would not gain power anyway.

Labour and LibDem could have made a deal to oppose the Conservative candidates with only one candidate from Labour / LibDem, in proportion to the forecasted vote shares. In that case, the LibDem could have assured a referendum on Brexit. During the elections, Jeremy Corbyn was criticised that he did not take a stand on Brexit, but his party was clearly divided, and his offer of a referendum was a fair option. At most five years from now there will be new elections. These are the Conservative “battlegrounds“, where this party could lose a seat by small number of voters.

Beware of John Curtice

John Curtice’s diagnosis on Channel 4, November 27, was:

“This is pretty much a binary election. Hung parliament, then we’re almost undoubtedly heading towards an extension and a second referendum, and lord knows what the outcome of that will be. Or we get a majority and we go out on January 31 and Boris is charged with the task of negotiating an alternative outcome. Ironically at the end of the day we’ve kind of stumbled into this election, but as the way it’s turning out, it’s actually providing us with a fairly clear binary choice.”

The latter is clearly nonsense, already before the election outcome. Above dynamics of UK voters shows that voters did not see a binary vote on Brexit and clearly had various considerations other than Brexit.

John Curtice is a renowned professor who on Election nights predicts the district outcomes with amazing accuracy. The problem however is that Curtice doesn’t see or explain that the true problem for the UK lies in the lack of equal proportionality in the general election. Curtice is locked in his electoral worldview like a hamster in a running wheel. Whatever he thinks and says here is in service of the current disproportionate electoral system in the UK, and then still produces nonsense.

In sum, it is the current electoral system that created the mess on Brexit and its misleading referendum question in 2016. If the UK had had equal proportional representation (EPR) like in Holland to start with, then Nigel Farage could have gotten his 12,5% of the seats in the House, and then the political discussion would have had greater restraint on the truth of the matter.

Brexit is still a mess, and now the eggs are scrambled

The solution for the present mess lies not in a new referendum on Brexit, as Curtice accepts, but in equal proportional representation (EPR). Referendum questions are manipulative, and voters cannot negotiate in polling stations. With EPR, representatives in the House can deconstruct manipulation and can negotiate. The current UK system gives only district winners, and they may be locked to a party line and cannot represent the diversity of views within their districts. The latter was already a fairy tale in 1900 and even more in 2020. Again, see my evaluation in the APS Newsletter Physics and Society.

Let the UK reboot itself. A big problem for UK voters now is: if the UK would rejoin the EU then it would have to accept the euro.