A COVID-19 Interim Report (5): Phantom Knowledge and 3 policy brands

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Reading the Data

Fig. 1 COVID-19 in the Netherlands for 45 weeks

In Fig. 1, the numbers of new registered COVID infections and the numbers of new COVID deaths per week are given, as observed for the Netherlands. The black line (for the dead) represents the raw data. The red line (for the infections) shows the numbers in percentages (or: the raw contamination data divided by 100 – so they fit together in one graph). If the red and black lines intersect (as in week 23 and week 46), the number of new deaths is exactly 1% of the number of new infections. If the black line is above the red, the number of new deaths is greater than one percent of the number of infections for that week. If the black line is below that, the number of deaths is less than one percent of those infections.

Phantom Knowledge

It’s tempting to play with those lines. For example, in such a way that you can show from the factor by which the red line has been multiplied how that ratio has shifted from the start of the pandemic in the Netherlands to that of the present. Fig. 2 shows that the death rate in the first weeks was 12.75%, while it was around 1% in the last weeks.

Considering that no drugs or vaccines became widely available in the past 45 weeks, I am assuming for the time being that there have been no huge differences in the way the virus works and that the percentage of infections that result in a death is more or less constant, at least during these two periods. How then explain the differences?

  • Between those two periods, improved treatment methods could have been found and implemented. That should have happened in weeks 20-35.
  • It is plausible that in the initial period the registration of infections largely coincided with the display of serious symptoms, as a result of which the numbers of new registered infections would have been well below the actual numbers, while testing was much broader in the second period. Such could have started from week 23 onwards.
  • It is plausible that the measures introduced and re-introduced respectively in week 12 and week 42 (one and a half meters, stay at home, limited group size, sort of soft lock-downs) are effective, at least when they are adopted by the population.

Anyway, when reading the data, it becomes apparent that too much is unknown in order to be able to conclude with certainty. Because it is now known that the virus can be transmitted by those who are infected but do not show symptoms, the naive view of the data in Fig. 2 especially invites to read misinformation from it. For example, there are those who choose the interpretation of Fig. 2 on the left: more than 12% of infections are fatal. So it is crisis. And that is true, but we can best measure that against the need for IC capacity, not with very incomplete data about infections. There will also be those who opt for the interpretation of Figs. 2 on the right side: about 1% of the infections are fatal, or even less. So the measures are exaggerated. But that is only true if we think it is excessive to prevent our intensive-care capacity filling up and overcrowd with COVID patients when we can prevent that.

Both interpretations are therefore based on phantom knowledge.

Comparison – 9 countries and three policies

With the proviso that the data must be interpreted with great caution, I now look at the kind of overview given in Fig. 1, for 9 countries concurrently (see Fig. 3.) I have arranged them in three columns.

The first contains three major jurisdictions. They fail to control the virus. They have large numbers of victims. They are the US, Brazil and India. A political role could be that the jurisdictions are divided into federal states that have their own responsibilities and can / must pursue their own policies. This column contains the countries with fragmented policies.

The next column lists three countries that managed to control the pandemic around week 20 after a first wave only to face a second wave around week 35. They are three European countries: Germany, the Netherlands and Austria. They have now all set a lock-down again and are hoping for the best. This concerns (with regard to recurring pandemic waves) an anti-cyclical policy.

Finally, the column with the three countries that are keeping the pandemic short and banned to the outside world with strict border controls, strict quarantine rules and universal testing. These countries are China, South Korea and New Zealand. This type is a control-oriented policy. In results in very low numbers of COVID casualties per week. Remarkable are the differences and similarities in cultural and administrative forms: China with its collectivist, totalitarian and neo-liberal blend, South Korea with its collectivist, democratic and neo-liberal mixture, New Zealand with its neoliberal and western-democratic cocktail. All three mixtures did agree with the controlling approach. The New Zealand government even gained an absolute majority in recent elections.

Fig. 3 Nine countries compared: fragmented, anti-cyclical and controlling policy characteristics

The Difficulty

Fig. 4 Exponential growth

Figure 4 illustrates the difficulty. Without a policy, the number of deaths follows an exponential curve until the number of people who can be infected is actually infected. And that curve will continue to apply when the immunity that follows with infection is short-lived. An uninhibited first wave with a death rate of 1% and an R0 of around 2 would lead to, in the Netherlands, the death of 1% of the population within a few months, which amounts to 171,348 fellow citizens.

When it is the case that COVID mortality can be curbed with measures, a need arises to weigh the costs involved in the measures against the benefits of the measures.

The first attempts at this have now been published in the ESB. It is to be feared that these economic cost-benefit analyzes will result in the pricing of years of life and that this will weave another haze of science to cover reality.

Such cost-benefit thinking will obscure the normative debate about how the weight of non-economic values of structures and possibilities that rest on the use of social, political and scientific assets can and should be taken into account also.

Or should we (continue to) hand over that debate to whom can best shape the universal merits of the financial invisible hand to serve their personal gain?