The spread of the virus is already virtually under control


In this article I show how the COVID-19 virus spread before 15 March, before we took measures in the Netherlands. The overviews per municipality show, that the speed of the virus spreading increased enormously when a so-called “super spread event” was held. Without superspread-events, the virus spread quite slowly. And that even though no measures had been taken at that time. I repeat: none!

After the Netherlands decided on measures around mid-March, we saw in many infected municipalities, that the R0 factor (the speed of reproduction) gradually decreased. Partly due to those measures, but partly also due to the fact that no meetings/events were allowed to be organised.

These findings from the first weeks of March indicate, that the chance of another major outbreak if we mitigate measures is very small. As long as we keep (larger) meetings prohibited for the time being. That is why the government can already take quite a few steps to reduce the measures taken without major risks. I discuss this at the end of the article and give some advice on how we can pick up our lives wisely again without ending up in a 1.5 meter society.

The findings

Below I show you that the COVID-19 virus spreads much less without “superspread events”. This should have major consequences for the exit strategy decision making. Especially because it also shows that the chance of a new outbreak -with the right choice of measures- is virtually nil.

It is important to realize that there are two main ways in which the virus jumps from one human being to another:

  1. A non-infected person comes into close contact with virus droplets, which have escaped from the mouth or nose of a virus carrier. The WHO and RIVM assume that if you stay 1.5 metres away from another person and everyone complies with the instructions on a good personal hygiene, the chance to get infected is very small. In addition, new research shows that the chance that the virus is transmitted via objects is also very small.
  2. An infected person also excretes micro droplets (aerosols). These can remain floating in the air, so that micro droplets from one infected person, can infect many others. In the past month, more and more information has become available about large-scale and small-scale gatherings, where this has happened to a large extent. I call these events “super spread events”. A Canadian journalist has posted an interesting article documenting 58 of these super spread events.

I have already described the effect of the super spread events on the spread of the COVID-19 virus. I described what happened around the Atalanta Bergamo-Valencia’s soccer match on February 19th and what happened after a benefit evening in the Dutch town of Kessel on March 5. But we also know about super spread events in for example Daegu (Korea), Madrid, Mulhouse, Kuala Lumpur and New Orleans (Mardi Gras). And recently I also saw on television that there has been a big New Year’s Eve meeting in Wuhan on 25 January.

The conditions are apparently such that those small particles of the virus can remain in the air for a long time and then infect many of those present. It seems that when attendees sing, the risks are greatest, amplified by poor ventilation and/or low humidity. (Comparable patterns can also be recognized in the case of massive infections of passengers on cruise ships, crew on naval vessels, and in care institutions).

Around 15 March, measures were taken in the Netherlands to slow down the spread of the virus. This means that its effects must be reflected in the figures from 21 March onwards. The previous figures therefore reflect the period in which we were still living together in a normal way. The virus still had free rein then.

Fortunately there are figures available for the development of the number of infections per day per municipality. It is important to realize that the estimation of the number of infected people, all over the world, is a big underestimation of the number of real infections. In the Netherlands, I estimate that in reality the number of people infected is a factor of 50 higher than the test shows. (This is in line with the results of a random survey in LA County). That would mean that by the end of March around 600,000 people in the Netherlands were infected (more than 3%).

Here you will find maps and graphs with figures per municipality. These come from the RIVM and are beautifully processed by the Geodienst in Groningen and the Aletta Jacobs School of Public Health. Based on these figures, I have made the analyses, which you can see below.

So I want to delve deeper into the contamination spread in the Netherlands, before the measures that were taken, had any impact. Because we can learn a lot from when we phase out measures. The number of infections was monitored by the RIVM per municipality until 30 March, so the last 9 days of that month reflect the period that the measures should already have had an impact on the spread of the virus.

R0 is the important factor in a pandemic. The so-called reproduction factor indicates how quickly the virus spreads. The value 2 means that 1 carrier of the virus infects an average of 2 people in 6 days. After 18 days a total of about 18 people would be infected and after 30 days 78. The aim is to bring this R0 below 1. In that case there will be fewer and fewer new infections.

In the case of influenza, an R0 value of between 1.1 and 1.3 is maintained. On COVID-19 the consensus seems to be that the R0 without any measures is somewhere between 2.2 and 2.5. If it were 2.5 then 1 infected person would have infected up to 260 people after 30 days. The RIVM indicates that in the Netherlands, somewhere at the end of March, the R0 had come close to 1 and then went further down.

The big question is of course what exactly the risks are if measures are reduced. The mantra seems to be, that it could go wrong again if we take the wrong step or phase out too quickly. But how big are the risks? That seems to be pure speculation at the moment.

However, there is a way to look more rationally at how big the risks really are. Because before March 15th we just lived a normal life, so the virus could spread optimally. It is only with the observations from 21 March onwards that the measures must have had an effect.

If you then look at the figures from individual municipalities, there are important clues as to what could happen if we were to phase out measures.

Let’s focus on the municipality of Loon op Zand. At the end of February, the first Corona patient in the Netherlands was recorded there. These are the cases per day by 100,000 inhabitants.


(These graphs are the figures per 100,000 inhabitants. For our purpose we are especially interested in the increase factor of the development in time.

At the beginning of March there were 4 virus carriers in Loon op Zand, all in one family. On 21 March there were 14. But even if, as a calculation example, we pretend that at the beginning of March not 4, but only 1 person was infected, that would be more indicative of an R0 somewhere around 1.2.  In the last 9 days of the month, the number of infected persons only increased by a factor of 2. And that also indicates an R0  close to 1.0. (You should always take into account that an infected case detected represents on average 50 infected persons because of underestimation).

Also in the municipality of Altena near the Biesbosch there was already one infected person at the beginning of March.


After 21 days the number of infected persons in Altena stood at 22. This indicates an R0 of 1.2. In the last 9 days the number of infected persons doubled as well. And this also indicates an R0 value close to 1.0.

But how is it that in March the number of infected people in the Netherlands increased exponentially?

I show this by zooming in on a number of municipalities where a super spread event took place. Peel and Maas is a good example. In the village of Kessel (more than 4,000 inhabitants) there was a benefit meeting with more than 300 people on March 5th.


The event was on March 5. On March 11 the first infections in the municipality were registered and on March 21 there were already 63.  So in 10 days the number of infected people has increased significantly. Based on the underestimation of the number of people actually infected, that would mean that on March 21, 16 days after the event, more than 3,000 people in that municipality (with a centre of gravity in Kessel) had already been infected.  This is an R0 that is significantly above 5.0. However, between 21 and 30 March, the number of infected persons in this municipality increased by just over a factor of 2. And that resembles the figures of Loon op Zand and Altena. So the effect of the measures taken around March 15th!

While in Peel en Maas the super spread event of March 5th was the starting point of the big outbreak, in Uden it was Sunday March 1st. We can see that in the graph below. Almost certainly someone was present at one or more church services who was infected at that time and sang along.

The first infection was detected on March 6th. On March 21 the number of infected persons in Uden was 76. An increase in 15 days by a factor of 76. That too is an R0 that is far above 5.  And also in Uden we see that between 21 March and 30 March the increase was only a factor 2. So an R0 that came close to 1.0.

Emmen is a municipality, which has an even slower spread than Altena. On March 8 the first infection was detected and only 4 on March 21. So without any measures in Emmen with 100,000 inhabitants there was only an R0 of just over 1.0 !!!

Here we see in the last 9 days a somewhat larger increase than in the other municipalities. It increases by a factor of 3.5. At the end of the month Emmen (via that multiplication factor of 50) had an estimated 0.7% infected persons in the municipality, whereas in Uden it must have been 15% already.

Also when we look at other municipalities it is striking that in quite a few municipalities we recognize the influence of super spread event. Church services on March 1 and 8 and the “afternoons for the crop”celebrations on 11 March seem to qualify as super spread events in those congregations. But I have also been notified of outbreaks of the virus after choir rehearsals or – performances.

Below is a selection of these municipalities:


For comparison a number of municipalities that already had an infection in the first 10 days of March, but where the spread was much slower, apparently because no super spread event had taken place.


If you look at the development in larger municipalities, with 5 to 20 times more inhabitants than those small ones, then by the law of the large numbers it becomes a mix of superspread events and the “normal” spread from person to person. And you can’t recognize them separately anymore.

In Tilburg (not far from Loon op Zand) the first infection was on March 1st. On March 21 the number was 154. That indicates an R0 of over 4. It is very likely that also in Tilburg between March 1 and 8, through church services, choir rehearsals or parties, super spread events took place.

Between March 21 and 30 we also see an increase of only a little more than the factor 2 in Tilburg. Breda shows, with a delay of a few days, the same pattern as Tilburg.

If you only look at the total figures in the Netherlands per day, you can see an exponential growth until the end of March. But if you look at the municipalities separately, you see a much more nuanced picture. While in most municipalities where the virus had been circulating for some time, the increase between 21 March and 30 March was only around a factor of 2, for the whole of the Netherlands it was a factor of 2.8. And that’s because on mid-March there were still 120 municipalities where no infection had yet been detected and most of them only got going in the last part of March.



The study of the development in the municipalities between March 1 and 21, shows that super spread events, when no measures were in place, led to a very sharp increase in the number of infections. Without these events and without any measures such as social distancing and banning visits to the hospitality industry, hairdressers, manicures, etc., the R0 seems to be somewhere between 1.1 and 1.5. A value that resembles that of influenza.

In this blog I have explained why in case of flu epidemics, we cannot easily recognize the influence of super spread events. But with COVID-19, with no historical immunity among the attendees, you immediately notice a week after the event that it had a major impact.

If we were to live our lives again, exactly as we did before 15 March (something I absolutely do not advocate) and we would only forbid meetings of more than 3 people, then the R0 alone would drop to a value of around 1.2 to 1.3. For the record, that’s just by living our normal lives as we did before March 10 and certainly not as a “1.5 meter society”!

The Israeli chairman of the “National Council for Research and Development”, a mathematics professor, noted that a similar pattern can be recognized all over the world.  The first 40 days an increase and then a decrease. Which he indicated seemed to come to zero after a while.

In discussions he indicated that he had no explanation for this, but found it remarkable, that it seemed that the measures governments had taken, or not taken, had little influence on that curve. Wherever he looked, he saw more or less the same pattern, also in a country like Sweden.

My analysis is the missing link in this professor’s finding. Because there is one measure that has been taken almost everywhere in the world:

Prohibiting meetings with a larger number of people.

Virtually all countries have, in addition to the measures they have taken (from a complete Lock down, via an intelligent Lock down, to a somewhat freer approach like in Sweden), decided that ‘super spread events’ can no longer take place. This alone has considerably slowed down the spread of the virus. The other measures taken by governments, push the R0 (well) below 1 and that is the image that the Israeli professor saw all over the world.

This should have major consequences for the exit strategy of governments worldwide and certainly to the Dutch!

As long as the meetings with a larger number of people remain forbidden, there is no chance that there will be another major outbreak of the virus “which will undo all our efforts” as Premier Rutte said, at the intercession of the Outbreak Management Team members.

We could already take steps now, which will keep the chance of new infections smaller than in many low infected municipalities before March 21 this year.

Of course with a smart policy. Just like Germany mandatory mouth protection in public transport and shops would already be a good step away from the completely unnecessary 1.5 meter society, as I have shown above. Making hairdressers, manicures, pedicures, beauticians (with mouth guards) work again can be done without any objections. Also the hospitality industry could start up again. Especially venues with outdoor terraces. But also others, with some extra facilities inside.

I also think that it will be proven, that wearing mouth protection anywhere outside also means that we don’t have to keep a 1.5 meter distance. East Asia shows us the way. And in Jena in Germany they have been doing that for some time with very good results.  But if we don’t want to / can’t do that yet, then the 1.5 meter distance (except in public transport and shops) is still a good choice. And older people are indeed the most vulnerable and they should be more cautious for the time being. (Here, too, mouth protection for the elderly themselves and their visitors is a wise choice).

A number of other important lessons have been learned from those super spread events. Which we still have to apply as long as the COVID -19 virus is still present.

It is evident that in confined spaces where foreign people gather, the risk of the virus spreading via aerosols is greatest. Good ventilation and an air humidity of 45% at 20 degrees Celsius is an extra precaution against this spread via aerosols.

In offices, care institutions and schools, the way in which internal ventilation and heating/cooling is regulated is a risk factor. Here too, there are clear indications that aerosols spread via these types of systems if they are not properly regulated. How do you think that 900 people got infected on a naval vessel? Not because all those 900 people have moved within one and a half metres of an infected person. No, it’s mainly because of those floating aerosols.  The same risk was/is also present in care institutions. Usually little fresh air ventilation. Where many people are infected in a care facility, two causes are most obvious: church service and festive evening with many residents of the facility, or the internal heating/ventilation system.

Although it is undoubtedly true that children are less vulnerable to the spread of COVID-19, a day at school could also turn into a super spread event.  To avoid this, schools should do the following:

  • Ventilate as much as possible and teach in the open air if possible.
  • Bring the air humidity in the building to the level of 6 g/kg (that’s about 45% relative humidity at 20 degrees Celsius). Here you can calculate this value.
  • If the ventilation and/or air circulation or humidity inside the school is not good, use mouth protection.
  • And certainly stop singing in classes.

On that basis it is very well possible to keep a good balance between public health and the importance of the economy and society.

We have to get rid of the unfounded fear that the virus could re-erupt at any moment, when we know that we have banned the biggest source of the spread, the super spread events. Let’s use the energy together to start up society again quickly and smartly on the basis of good analyses and data and not on the basis of empty cries.

Last but not least, there are many indications that as it gets warmer and more humid, the spread of the virus will be further slowed down, including in this research by Homeland Security’s lab in the US. Not that the virus will disappear completely. In the autumn these conditions will become more unfavorable again. But then we have already learned a lot more (at least that should be the case), in order to prevent a large spread of the virus, as it has happened for the last month and a half.

There is a provable causal connection!

I remember well when in university I was first explained what a mock relationship is. In Denmark there was a strong correlation between the birth rate and the number of storks that had their nests there.

The explanation was that there are more storks in the countryside, where also more children are born than in the city. But of course storks do not bring babies.

A good lesson to realize that if certain things are numerically connected, it doesn’t have to be because there is a causal connection.  So if you find a numerical connection, then the next task is to find out if there is a causal connection. By changing one variable, the other one should change as well.

So I briefly go through the steps that have been taken and the evidence that has been found. With the links to where that information comes from.

A. There is a numerical correlation between the specific humidity and the number of deaths caused by COVID-19. This was already found in this study in early March. In the meantime, a statistical analysis of 69 areas in Italy, the US and the Netherlands has also been carried out. In this research report.

you will find the numerical analysis of those regions, which shows, among other things, that if the specific air humidity was between 4 and 6 g/kg on average in the previous 3 weeks, a region reached 1 death per million inhabitants per day, twice as fast as if that value was higher or lower. So the correlation has been established. But that does not mean a causal connection.

  1. Several scientists are giving explanations, which could lead to this. Two possible explanations that are given are:

In this article, Prof. Evengalista (microbiologist and virologist) gives this possible explanation:


And there is also this explanation suggested by a group of scientists mentioned in this article.

In the U.S., the government commissioned research at the University of Utah to investigate both possibilities in the lab. I hope they come up with their results soon. Personally, I think it’s quite possible that both statements are valid, but time will tell.

In 2013 there has been large-scale research, based on data from 48 locations around the world, into the relationships between the development of a flu epidemic at those locations and the weather. For each location, several years of information was used. The result of this research was, that based on the specific air humidity, it could be predicted with more than 80% accuracy, that there would be a flu epidemic one month later. This is the graph that shows this relation well. It can be found in this article.

We see as well, that there is a clear relation between the specific humidity (the grey columns) and the start of the flu epidemic (the black dot). And that the limit of 6 g/kg is really visible.

But this is still no proof that there is a causal relationship. Other factors may play a role as well.

D. Subsequently, evidence has been provided in various ways, that a viral infection can occur via micro drops in the air (aerosols). The Japanese chairman of the association of virologists shows this in a video. Ejected micro droplets remain in the air for a long time and can infect those present.  Here I report on it.

This would be an excellent explanation for the large-scale distribution (super spread events) at après-ski, carnival, large church gatherings, choir rehearsals, the distribution within care institutions (the air circulation system) and the distribution on cruise ships and navy ships. Incidentally, this is a way of distribution that is not (yet) recognized by the WHO and RIVM.

In that video, the Japanese professor indicates that ventilation is a good way to make these micro drops disappear.  Based on the previous three findings, it is now very plausible that humidity also has an influence, on whether or not those drops float for a long time. Prof. Evangelista (see point B) says this literally.

The final proof came from animal experiments in which it was established that animals that released the influenza virus, at varying levels of humidity, infect other animals and the extent to which they do so. Professors of micro-biology and virology in Switzerland and at Yale University have recently written an article in which they report on past experiments on air humidity and the spread of the influenza virus. I am reporting on this here. (I now have intensive contact with them).

Several researchers have conducted experiments with mice, guinea pigs and ferrets. Some of the animals were infected with influenza. The uncontaminated animals were separated from the sick animals. So there was no direct contact. So the only possibility of infection was through the air (micro drops).

In the experiment the infection of the other animals was measured at different humidity levels. The researchers found that there was a clear correlation between the air humidity and the degree of spread of the virus. This picture shows their findings.

These experiments demonstrate conclusively that there is a causal relationship between the humidity and the extent to which one can be infected with a virus via aerosols.

So the correlation found, mentioned under A, is not a mock correlation but a causal relationship: the degree of specific humidity has a direct influence on the speed of spread of the virus.

Nevertheless, there may also be other factors that influence the speed of the virus spreading. Many possibilities have been put forward: the vitamin D level of the population, the UV content of the sun, pollen in the air and the fact that one is more indoors in winter.

I don’t explicitly exclude those, but there might just as well be a mock correlation with humidity (as I think is the case with pollen). And it would be nice if also with regard to those alternative explanations an equally hard proof would come, as through the evidence given by me.

Because any well-founded knowledge of how the speed of the virus spreading is slowed down is an important weapon in this battle.

This is how the spread of COVID-19 generally takes place

I studied to become a social geographer. My specialty was research & statistics. In 1965 I learned how to program and have since always used computers intensively for my work.

In huge crises like the one caused by the COVID-19 outbreak it is of major importance to use a multidisciplinary approach. That explains my effort and approach.

For the past two months I’ve been studying the geographical patterns of outbreak the virus on a global scale. In doing so I used both old and very recent scientific studies to find answers to the following questions.

  • Why were the first big outbreaks in Wuhan, Daegu, Teheran, Bergamo, Madrid, Brabant and Seattle?
  • Why is the number of deaths in Lombardy higher than the total deaths in Africa and Latin-America combined?
  • Why does Japan have 1 death for every million citizens, and the Netherlands 160?
  • Why is the number of deaths in New York City 15 times higher per million citizens than San Francisco’s?
  • Despite weeks of pointing out the risks for refugee camps, townships and favela’s, how come we see no big outbreaks in these places?
  • no big outbreaks in refugee camps, townships and favelas
  • What’s so special about the outbreaks in New Orleans and the coastal town Guayaquil (Ecuador)?
  • How come so many people get infected and die in nursing homes?
  • What explains the decrease in number of new infections in the Netherlands?

Coincidence is certainly not the answer to these questions (although it plays a very small part) and neither is the fact that certain places register better or fairer. And it being a matter of time before the situation is the same worldwide is also false. There are clear explanations for the above. Understanding their consequences heavily influences which exit-strategy we choose/must follow (worldwide).

Very soon it became clear (I read it on Twitter already in January) that the R0, the reproduction factor of COVID-19, was very high. In February it showed to be around 2,25. (1,3 for regular flu). This means that when no measures are taken, 1 person could infect on average 400 others in a one-month time span.

Everywhere authorities tried to bring that R0 to below 1 as soon as possible, and they were right to do so. If they hadn’t, the number of new cases would only increase faster.

Three things stand out when we look at outbreaks that occurred up until one month ago:

  • Most of them occurred between 30- and 60-degrees latitude, in a climate zone where the weather at the time was between 4 and 11 degrees and the humidity between the 3 and 6 g/kg (grams of water in 1 kilogram of air).
  • There are big regional differences between countries with outbreaks. Lombardy has 20 times more deaths when comparing it to Naples and Rome. And the Netherlands, Spain and the US clearly show a similar pattern.
  • Often been gatherings of large groups that infected many individuals in one go. (The superspread events). Zooming in on these gatherings shows that it were mainly gatherings where people have yelled or sung. This involves both small and large scale ecclesiastical gatherings, parties (like après-ski and carnaval) and soccer games.

Looking at last month’s development shows:

  • Despite many countries located below 30 degrees latitude having been infected, very few of those places show outbreaks the size of Western Europe and New York. This doesn’t seem to relate to the quality of the taken measurements. (And don’t say that those countries are hiding their high death rates. If they had faced a severe emergency-situation then surely social media would have let the world known.)
  • All East-Asian countries have control over the outbreak. This doesn’t mean there will be no small areas with high spreading infection, but these will be eliminated very quickly. To illustrate, the number of deaths per million inhabitants on the 11th of April: Japan 1, Taiwan 0,3, Singapore 1, Thailand 0,50, Malaysia 2 and Korea 4. (Both the last two countries had a big outbreak during a religious event that lasted for multiple days and had over 1.500 infections, yet they managed to completely regain control over the spread.) The province in which Wuhan is located experienced 70 deaths per 1 million citizens. But in Beijing there were only 8. This looks like Korea’s pattern. The province of Daegu had a big outbreak, and faced 60 deaths per million, whereas Seoul only had 2. (Not per million but in total).
  • Many deaths are in nursing homes.
  • Many cases at ships (cruises and navyships)
  • Two to three weeks after lock downs show that the number of new cases stabilizes, and then drops.

There is an explanation for all the above. Supported by studies on influenza, including experiments with animals, and research about COVID-19.

This explanation is, that the spread of this virus takes places mostly through the air in (semi) closed off spaces. More so than any other way.

Forms of infection that the media so frequently mentions, could cause an R0 of 1,1 or 1,2. Measures like social distancing and/or wearing masks are aimed at getting that rate below 1,0.

Science also tells us that when people speak, couch or sneeze they emit microdroplets (aerosols) which stay airborne for a long time, thus meeting almost all people in that space. It only takes one single individual to be infected (that doesn’t know he/she is) and you’re done.

(Unfortunately, the WHO and RIVM thought up until recently that this form of spreading didn’t happen that much.)

Scientific experiments have shown that

  • The effect of these aerosols is much less in well ventilated spaces.
  • The aerosols stay afloat for a long time in air with low humidity. They float the least at a humidity of around 6 g/kg (at 20 degrees that is a relative humidity of 45%.
  • Above this level of 45% the risk of getting infected increases again. However, above 80% humidity and/or 30 degrees there is no infection through air at all. (see graph below)

When we apply this information to the previously asked questions, we can answer them all.

  • Big outbreaks have (mainly) occurred in poorly ventilated spaces with a relative low humidity where many people gathered enthusiastically. After these so called superspread-events the spread has continued at smaller gatherings in the first two weeks of March (like church meetings, choir repetitions and parties like weddings and festivities). The maps of the Netherlands and Germany below clearly show the relation between COVID-19’s outbreak and the distribution of Catholics in the country. The first superspread-event was carnaval. Then the infected that attended the Catholic church infected the rest of the Catholic people.
  • After that, thanks to “Day of Prayer of the Crops” on the 11th of March, in the Netherlands the entire Bible Belt got infected.
  • Gatherings where people sung (churches, parties) and -mind- the internal air circulation, which spreads aerosols through the building, are responsible for much more victims in nursing home outbreaks than direct infection via visits or caretakers/nurses.
  • The main reason East-Asia has such low death rates is because they started wearing masks very quickly (if they didn’t already). This did not only prevent infection of those wearing the masks, but it also prevented the wearers of intentionally infecting others. That’s why there haven’t been as many deaths in regions outside of the outbreak epicenters.
  • The fact that refugee camps, townships and favelas didn’t have any big outbreaks is partly because people don’t live in closed spaces, often without windows so ventilation is good. Plus, the humidity helps against spreading the virus, and the temperature is often above 30 degrees. This also counts for many parts of Africa and South-Africa.
  • Australia too shows outbreaks smaller than Western Europe or the US. New South Wales (where the first cases were reported even sooner than in the Netherlands) had 3 deaths per million inhabitants. (On March 21st we saw on TV in the Netherlands how many Australians went to the beach. 23 days later there is definitely no big outbreak, opposing to what the Dutch media almost explicitly predicted.)
  • Few hot and humid places do show large outbreaks, Louisiana being the best example. At Mardi Gras, over a million (!) people gathered. It is not unrealistic to think that during this event tens of thousands of people got infected. The number of deaths in Louisiana, 7 weeks after Mardi Gras is now at almost 200 per million inhabitants. I think that after Mardi Gras the churches played a big role as well in further spreading the virus over there. In Georgia the number is already up to almost 40 per million.
  • Finally, German research has shown that the chance of people infection one another by touching the same surface (like supermarket trolleys, door handles, elevator buttons) is very small.

When looking at how the number of people ill or dead in the Netherlands develops approximately three weeks after the intelligent lockdown, we can first see stabilization and then a clear drop. Especially in Brabant and Limburg. (Some other provinces seem to have had new areas of fast infection due to “Biddag van het Gewas” on the 11th of March, which caused the drop in numbers to come later.)

Especially when we realize that far from a small part of the current victims in the Netherlands are in nursing institutes (I’m estimating at least half of all daily deaths), we can estimate that the rate of infection outside of these institutions has dropped significantly. This is also because since a couple of weeks there have been no gatherings of big groups of people anymore.

Taking all the above into account tells us how we can taper off the measurements and keep the risk of further spreading at a minimum. And also to succeed as a society revive our economy and social life. Like the lockdown, this can be done in a smart way too.

That’s what I’ll write about tomorrow.

What social geography adds to the containment of COVID-19

As a result of my Dutch TV performance last Saturday, I get two kinds of reactions.

There are people who are (very) positive about what I publish and tell. And there are people (often with some kind of anger), that dismiss me for not being a virologist or epidemiologist, so how I dare to investigate COVID-19’s behaviour, write about it and take a stand on it.

I do understand the latter reaction, but at the same time it indicates that there is no recognition of how different fields of expertise can cooperate to battle the challenges we face as a society.

I hope those people will read my explanation below. Not because I hope that they will think a bit more positive about me, but mainly because I hope that they will better understand what those challenges.

I’m not a doctor and I’m not a virologist. I don’t pretend to be. Of course I read a lot about the virus and how to fight it, but I do that as an interested citizen. Moreover, I have great respect for the commitment of all doctors and virologists and I really am the very last person who wants to work against these dedicated professionals. In fact, I try to help them. And the great thing is that my contacts with the virologists (and the RIVM) show that what I do is best appreciated. During the interview Ab Oosterhuis, a leading virologist in the Netherlands, even largely agreed with my conclusions and findings.

Why does my profession/specialism and experience fit in so well with solving the problems we face?

Because social geography reveals patterns that help the government, OMT and RIVM to choose the optimal strategy to reduce the rate of spread of the virus as quickly as possible.

There is something special about the spread of COVID-19, something that is different from the annual spread of the influenza virus. Differences we can identify through social geography research.

In normal influenza epidemics, the pattern of spread is not easy to determine. And that is because many people in the population have already built up immunity to all kinds of influenza strains in previous years. That’s why older people, among others, are less likely to get the flu. So suppose that in November 2017, 200 people were in a room and all of them could actually have been infected. If you don’t know who has already built up some form of immunity, you can’t really determine how that infection really happened.

Then you would have to test everyone present to understand and analyze that.

That is not the case with this COVID-19 virus. No one was immune during the outbreak. So in the case of the spread, it is – for the time being – irrelevant to determine whether someone was/is already immune. It’s, as it were -and unfortunately- as if the whole world has become some kind of laboratory.

Per country, but also per region and even per city, we see patterns of distribution and an approach by governments, which are partly different and partly similar. This provides insight into how the spread proceeds (e.g. via the super spread events) and what works or does not work to slow down the spread of the virus.

And let that just be the subject I studied; social geography (and demography and statistics). You study regional patterns and developments over time and you look at how that relates to other factors.

Historical geographical research, for example, has shown how important railway routes were/are for the patterns with which cities and regions developed. Both economically and where cities flourished. A geographer can investigate this without knowing how to drive a train or lay railroad tracks.

And the same goes for the analysis of the spread of the Corona virus. There are interesting geographical patterns in the spread of the virus. In some places it goes many times faster than in others. In Lombardy, Spain, Brabant, New York, the process is very different from Naples, Groningen and San Francisco.

By researching and explaining this from my field, it can be very supportive for those who face the great challenge of slowing down the spread and bringing the reproduction factor below 1.

And in this geographical research I also use scientific literature from microbiologists, virologists and epidemiologists for my explanations. In my contacts with various international experts in the field (microbiologists and virologists and authors of interesting papers on the subject), I notice that they are particularly pleased with my work, because it is so complementary to theirs. And with that, their own findings are further substantiated.

Recognize that after this first phase of the global spread of the virus, in which the expertise of virologists and doctors is crucial, we have now entered another phase. This is a phase in which, on the one hand, it is about getting and keeping the virus under control, and on the other hand, it is about rebuilding our economy and society.  Every expertise can play an important role in this. Or certain experiences of citizens who, shared with experts, can contribute to finding the right solutions.




Interesting international comparisons

Financial Times has a page with a nice way to read international comparisons regarding the changes in the spread of the virus.

It is important to understand what figures they show in those international comparisons.

  • They use the average number of deaths over the last 7 days.
  • As day zero for their graph, they use the first day with 3 deaths on average in that country/region,
  • The graph display is logarithmic. This is the usual way of showing the development of the spread of a virus.
  • The star indicates when a country went into Lock down.

Although the countries vary greatly in size -and most other statistics use the number of deaths per million inhabitants- this approach shows how the reproduction factor develops in that country. If the lines would not turn to the right, the virus would continue to spread unrestrainedly.

It is important to realize as well, that in smaller countries it takes longer to exceed the limit of 3 deaths per day, which may mean that measures are already in place before that country reaches that amount per day. In much larger countries the 3 deaths per day are reached quickly and therefore measures were usually not introduced until later.

From the charts that are alphabetically listed per country on the website, I have made a selection. And I rearranged them a bit differently.


Spain, France, Italy and England show the fastest increase up to and including the 25th day. In the other countries, including the Netherlands, we see a deflection sooner.  Sweden is a special case, because they have taken few measures, and I’ll go into that in another blog.

We see that the US has the steepest increase of all countries, including Western Europe. I myself am rather charmed by the alertness of the Czech response. Here you can read what happened there. From the 18th of March it is mandatory to wear mouth protection outdoors in that country. Since April 12th this is also the case in Israel.

With regard to the warmer and more humid countries, I think their curve is positively influenced because the weather has contributed to a slower spread than in the colder and less humid Western Europe and New York.

Finally, above we see the four Asian countries that immediately started to wear mouth protection en masse. There are many indications that as a result, people are less likely to infect other people. The number of deaths per million inhabitants is currently more than 100 times smaller in these countries than in Western Europe. So Japan with 100 million inhabitants has fewer deaths in total than France, Spain or Italy now have every day.

A number of countries are not listed (such as Singapore and Taiwan). That’s because they have not realized 3 deaths a day yet. In case they would be listed, the line goes straight down.

So these figures are on country level. But I also have the figures per region in Italy. And then it’s interesting to see that there are big differences there as well. At the beginning of March they had already taken restrictive measures in Lombardy. On 9 March all over Italy. When looking at the graphs per province it should be kept in mind that day 1 per province was sometimes well before the start of those measures and in other regions even after the start of those measures.

Below you can see the regions in Italy. The top four lines are regions in the North of the country. You can choose regions yourself and then only view that curve.

We did the same for the Dutch provinces.

The problem with the Dutch figures compared to those in other countries is that the RIVM does not register the provinces’ casualties per day that they announce that figure, but per date that the persons actually died, which implies that the figures may change for another week.

The curve seems to flatten out a bit more than in other countries. But that is also related to something else. Since a week, doctors try to register better, so we see an increase in death toll numbers, but that increase doesn’t seem to be accurate, because hospital admissions and the influx to the ICU’s is decreasing. While around 27 March the number of hospital admissions per day was around 500, it is now just over 100.

Here too, we see a pattern like in Italy, where the regions in the North of the country have a much more steeper line than in the rest of the country. Here we see that North Brabant developed steeper than the other provinces.

As I have often said (and this is also the case in the US, where I am still working on a similar chart), I think the most important factors are differences in distribution patterns between regions and countries:

  • Whether or not there have been major super spread events
  • The level of humidity in the air which has caused the spread of the virus to be faster or slower. (And in countries with very high humidity and the vast majority of people living in houses without windows, the rate of spread will approach zero).
  • The government measures. (And as for the latter, there are many indications that wearing mouth covers has a greater effect on slowing the spread than the 1.5 meter rule).

Personally, I think the first factor has been the most important in the major outbreaks we’ve seen. Now that these kind of gatherings are on hold worldwide, we see a clear flattening of the growth everywhere.

In countries south of the 20th parallel North we see relatively low numbers of infected people and generally flatter growth curves.

In countries where mouth protection is worn, the number of deaths per inhabitant remains a factor of 100 or more times lower than in Western Europe and New York.

In the coming weeks we will see almost everywhere, that measures are being weakened. And we will see what happens then. I wouldn’t be surprised if we don’t see many new major outbreaks. But let’s agree that if there are any new increases in cases anywhere in the world, we’ll thoroughly analyze what’s going on and what the extent is. The past few weeks I’ve seen too much (also in statements by virologists on television) of claiming that there was a huge new outbreak, where a simple analysis showed that the extent of what was happening was not that dramatic at all

Especially in this day and age it would be important when it comes to the numbers of infected persons, hospitalizations, deaths, etc. that everyone sticks to the facts. And if you want to factcheck any for yourself, I advise you to just Google on “wikipedia, Covid-19” followed by the name of the country you want to know more about. And you will get a wealth of material.



The superspread event on March 5th in Kessel

The municipality of Peel en Maas is the municipality with the most hospitalizations in the Netherlands. TV newscast EenVandaag devoted a report to it on 19 March.

A meeting on 5 March in community center De Poart in Kessel was the superspread event for the outbreak there. The available data give a good impression of the impact of that event. It was a meeting to raise money for the muscular disease of a fellow villager.  This is the report that broadcaster P&M made of it. Here we see a picture of another meeting in that community center, which gives an impression of what it looks like inside.


And this is a photo taken at the actual event.

It’s not really a large venue. There would have been 500 people present, most of them from Kessel. A village with 4,000 inhabitants in the municipality of Peel en Maas. From the video it is clear that people of all ages were present. Through the weather information for that evening we have determined that the specific humidity was 5.8 g/kg.

In this blog I will have to make several assumptions, because the specific numbers for the village of Kessel are not known. Plus we also know that the number of deaths and infections in the Netherlands are underestimated. But there is a very important reason why I do the following.

First I show the estimated figures, to give an impression and then I come to an important conclusion.

In March, the RIVM recorded the number of infections per municipality. These are the figures for the municipality of Peel and Maas until the end of March: 310 infections per 100,000 inhabitants.




In the meantime, this number has risen to 550 with the note that because relatively few tests are carried out in the Netherlands, the actual number of infections can be a factor of 15 to 20 times higher. This could therefore mean that the percentage of infected people in this municipality is 8 to 11%.

In terms of population, Kessel is one tenth of the municipality of Peel en Maas. But it is clearly the source of the wildfire in that municipality. In the adjacent municipality of Horst aan de Maas we see figures that are one third of the municipality of Peel en Maas. If we assume that the municipality of Peel en Maas, excluding the village of Kessel, has the same figures as Horst aan de Maas, this would mean that at least half of all infections of the municipality of Peel en Maas have occurred in the village of Kessel. And that would mean that by the end of March, the proportion of infected people in Kessel must have already reached 2,000, which is 50% of the population!

Since then, the number of victims in that municipality has only increased. And that’s interesting because Peel & Maas seemed to be on its way to reap the benefits of the group immunity strategy initially propagated by Dutch Prime Minister Rutte.

Since April 1st, the RIVM only displays the number of hospital admissions per municipality. And these are the figures for Peel and Maas. At the beginning of the month the number was around 220, and on April 19th, 310 per 100,000 inhabitants.




The number of deceased inhabitants of this municipality is 56 on 19 April (129 per 100,000 inhabitants). This puts the municipality in 6th place in the Netherlands. Boekel has almost 200 per 100,000 inhabitants. (Experience shows, based on CBS civil registry counts, that there is an underestimation of about 100% of the number of COVID-19 deaths. So maybe the number of deceased in this municipality is double as well).

With all this information, it is now possible to give a picture of the result of this super spread event.

There were several hundreds present. It can be assumed, that there were people present who were infected during Carnival 2 weeks earlier, without realizing that they were infected.

10 days after the event in Kessel, the municipality had 30 “officially” infected people. However, taking into account the underestimation of the infected cases, I estimate that at that time around 300 people in the municipality were already infected. That would mean that 75% or more of those present had become infected that evening.

According to the regular course of the spread, each infected person may have infected another person after about 7 days. So even without a super spread effect, 50% of the inhabitants of Kessel could already be infected by the end of March. It is also interesting whether church services were held between 5 and 20 March and whether they also led to additional infections. After 23 March the rate of the infections decreased considerably due to the announced measures.

Considering the given numbers, the number of Corona deceased in Kessel seems to have been somewhere between 40 and 60. (The pastor mentioned in the report of EenVandaag the number of 30, but I don’t know if any people died in Kessel who were not buried at the church.) It is also well possible that there are still people in Kessel who are very sick and may still die.

I estimate that at the super spread event on March 5th in Kessel about 50 to 75% of the people present were infected with the virus. And that in the following weeks between 40% and 60% of the municipality was infected. (That would be 1,600 to 2,400 people). This now leads to 40 to 60 deaths. 10% of the inhabitants of Kessel are over 75 years of age. The mortality risk of infected elderly people is significantly higher than that of people under that age. (75% of all deceased people in the Netherlands are over 75 years of age!). It seems not unlikely to me that a similar pattern is visible in Kessel.

This gives a good impression of the enormous effect of the super spread event on 5 March in Kessel, even if the actual figures would be a bit lower.

Last but not least: Precisely because the number of infections and casualties in Kessel has been so high and it is also certain that there was a super spread event, I would urge the RIVM and the Ministry of Health, Welfare and Sport to start an investigation in the municipality.

I would like to know of all the victims (dead and infected) whether they have been at that meeting on 5 March and, if not, whether someone from their families has been there. In addition, I would carry out a random sample survey of approximately 500 people in Kessel to determine how many people were found to be infected.

I would also take a questionnaire to establish whether they had any complaints and if so, which ones and for how long. Whether they have been at that meeting on 5 March, or whether they had had contact with people who had been there. Did they visit church between 5 and 20 March? Plus I’d like to find out when the complaints started and when they ended.

Doing so will provide a wealth of information about all the facets of the spread of this virus and also what is actually the maximum percentage of people that can be infected.

I would say, do it as soon as possible.

“We are collectively committing hara-kiri”

The theme is that there is a complete mismatch between the threat of the virus and the measures taken in many countries. Actually, macroeconomist Lars Juning best describes this with the expression “We are collectively committing hara-kiri“. He wrote a report for the EU in 2006 on the economic impact that a pandemic could have on the EU.

Because of the way governments are now reacting, the damage will be many times greater than he wrote in that report. He had not taken into account that many countries would be completely locked down, as in fact happened in the Netherlands.

If you really think, as the IMF has indicated, that economic growth in the Netherlands will only go down 8% this year, then you are living in dreamland. It gets much worse.

There is just a domino effect. If this crisis was only the case in one or two countries, the other countries could, as it were, pull those two countries out of the equation. But it’s the same everywhere. Soon Statistics Netherlands (CBS) will see by far the biggest drop in consumer confidence ever. And that also means a huge drop in consumer willingness to buy.

Even if, with a magic wand, we could make sure that we would no longer have any restrictive measures from 1 June next, the economic devastation would still be enormous. Especially since consumer behavior will change dramatically as a result of everything we are now experiencing. Will people gave enough confidence in the future, to resume old spending habits? Plus that this lockdown also brings a revaluation of what is important in life and what is not.

And even if you value the latter positively, it will still have huge consequences. Not only economically, but also socially. Companies at home and abroad go bankrupt. Employment is lost en masse. Self employed people get (much) less work.

I wouldn’t be surprised if 10% or more of employment is lost in the Netherlands. I am convinced that this year the record number of bankruptcies will be exceeded.

This will also lead to sharply increasing social tensions within society at home and abroad, but also between countries. It is waiting for the first major looting by hungry people in a hopeless situation in one of the countries in the world. And can’t we skip that?

History has shown that such a major global crisis (wars, famines) often leads to many tensions and revolutions.

The problem is that the Outbreak Management Teams in most countries in the world, are occupied only by doctors and epidemiologists (just like in the Netherlands). These are expert and great people, who (rightly) focus on the delay in the spread of the virus from their field of expertise.

And fortunately now (and in almost all countries, by the way) we are seeing a weakening of that increase in new infections. Fortunately, we did not make it to the 2400 people in our Dutch ICUs. We are now at 1,200 and that number is falling every day. Even though there are still quite a few problems in the care institutions, partly because people do not understand the role of ventilation and air circulation in the spread of the virus. This is also the explanation for the outbreaks on cruise ships and naval vessels. If so many people are infected at the same time, it is not because someone is infected, who then sneezes in the face of 500 others. That’s because of the aerosols floating around.

But no matter how acrimonious it may sound: precisely because there is unfortunately still a lot going on in the institutions, we do not notice that it is better under control outside those institutions than we already think.

That OMT and the government have a blind eye for an at least as important patient, who is also in the ICU and whose situation is critical: the Dutch economy and society. The Dutch economy and society are suffering major (and partly irreparable) damage.

It is high time that the OMT will expand to include people who know a lot about this important patient. And who understand that what Minister Wiebes proposes as a “1.5 meter society” is not only unfeasible, but also unnecessary. Nowhere in East Asia do you see such a nonsensical approach.

Look for example at how the Czech Republic has done the approach almost exemplary from the beginning. And on 18 March, for example, made mouth protection on the streets mandatory. With a population of 11 million, they have only lost an average of 3 people a day for the last three days! Do you think they continue as a 1.5 meter society?

The research of that will be published tomorrow, shows that a quarter of all workers indicate that it is impossible to work in their company/organization on the basis of a 1.5 meter society. And another 15% indicates that it is possible, but not without major consequences.

What Minister Wiebes has announced is unfortunately a proposal from a chamber scientist, who has little experience with what the real world looks like on a daily basis.

I hope Prime Minister Rutte and his Cabinet will soon come to their senses. And that he will realize that this patient also needs attention and care. And that the consequences, if that patient does not recover well, will be many times more serious (also with regard to public health) than reducing the number of patients in the ICU with COVID-19.

We must quickly come up with an intelligent exit strategy that strikes the right balance between reducing the increase in COVID-19 patients and giving the economy and society air to breathe again. If we don’t do that, Lars Juning is right. Then we have committed hara-kiri.

To conclude an e-mail I received from a Dutchman from Phuket in Thailand. He gives the perfect example of the imbalance between the scale of the threat of the virus and the approach of governments. And this is the case in almost all countries.

“I’ve been living in Phuket, Thailand, for 20 years now, since 2001. My experiences here: April 17, 2020. Casualties in Phuket by Corona: 0, we’ve been in a Lock down for two weeks.

On March 17, 2020 (4 weeks ago) I spent another 4 hours in a government building, because we had to renew our driver’s license. Picture this government building: with 150-200 man waiting for hours in a building. Almost everyone has to stand because there are only 10 seats. Then you have to go into a classroom with a group of 60 people where they play a 50 min video.

Nobody was wearing a mask at that moment. The term “social distancing” was unknown.

Thousands of Chinese tourists have landed in Phuket every day since Nov-Dec. Jan, Feb. It’s full house. Hardly anyone in Phuket wore a mask in mid-March. We certainly had no shortage of Chinese people.

Spread of the virus almost zero (or a spread but without any symptom, we don’t know).

2 weeks ago everything closed down here. The death toll was still 0. Lock down, hardly allowed to leave my house, masks on the street are mandatory. No alcohol sales. Almost everything’s closed. Don’t leave or enter my neighborhood.

That’s when I saw your quote: “humidity above 80% the virus can’t spread.”

I don’t know if it’s true, but I’ll take it as “true” for now.

In Phuket, we hardly ever get below 80% humidity.

That’s outside on the street. So transfer probability is or falls to zero. And yet we’ve been in a Lock down for two weeks.”