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Select disease:

Set degree of vaccination:

The epidemic is over, there are no more infected people
(make new selections in the top-left menu or scroll on)

All susceptible people have been ill
(make new selections in the top-left menu or scroll on)

sick & contagious
the simulation
Picture this
Picture a busy schoolyard. The children in that yard are the dots in this story. With that picture in mind, we will show how vaccination forms a barrier against widespread epidemics.

Why is this important?
The majority of children in The Netherlands - about 93% - is
against diseases such as diphtheria and the measles. It protects these individuals ánd nips the wave of disease in the bud before it reaches many unvaccinated,
people - still more than one hundred thousand individuals among primary school kids only. In spite of this, some people question the necessity to vaccinate and over the past few years their number has actually grown.

Give it a try!
In the virtual world below, you can investigate how vaccination slows the spreading of various diseases. The risk of
, when you encounter
someone ill
, is different for each of the diseases in the top-left selection menu. The risk is largest for the measles: no less than 90%. After people have
they are no longer susceptible.

Scroll on to the next step after finishing your exploration.

step 1 of 6

Too few shots

Not everywhere in The Netherlands the number of shots given is that high. Especially in bible belt counties, like Staphorst, Ede and Tholen, the degree of vaccination is low (less than 80 - 90%) for religious reasons. There, the collective protective effect disappears and diseases continue to circulate among unvaccinated people. For instance, the years 2013 and 2014 saw an epidemic of the measles among orthodox-protestant kids and in 2008 there was an epidemic among anthroposophic youth.

Press 'START' again to see what happens when the degree of vaccination is only 75%. Scroll on after to the next step.

step 2 of 6

Critical vaccination rate

The more contagious a disease, the more people need to be vaccinated to keep it under control. The measles are highly infectious and in The Netherlands the critical vaccination rate for this disease is approximately 85 – 95%. The critical level for the relatively slowly spreading diseases mumps and rubella is 80 – 85%.

You probably won't find the exact same values back in our simple model, because in reality not all vaccines are as effective and people come together in a less random manner. But it does give a good impression of how 'fast' and 'slow' diseases spread at different degrees of vaccination (top-left menu).

Try raising, for instance, the degree of vaccination in steps until a wave of disease extinguishes spontaneously, before it reaches all of the susceptible people. Then scroll on to the next step.

step 3 of 6

Individual decision?

Our virtual world is only an approximation of reality, of course. But it does demonstrate that the decision to (not) vaccinate your child is not just a choice for individual protection. It is also a choice to maintain the collective protection or 'herd immunity', which protects people that cannot be vaccinated. Young babies or people with a compromised immune response, due to medical disorders or chemotherapy, for example.

Scroll on to see what fraction of the Dutch children is vaccinated and to read more about the recent debates around vaccination.

step 4 of 6

The Dutch vaccination rate

In 2016, one out of eleven counties had a low degree of vaccination - less than 90% - among two year olds. This is after the first few rounds of vaccination, that provide a basic protection for infants. At the age of eleven, after repeat vaccinations that should provide complete protection, one out of eight counties had a low vaccination rate. Especially in the bible belt relatively few children are vaccinated.

The map below shows the situation for the DKTP- (diphtheria, whooping cough, tetanus, polio) and BMR- (mumps, measles, rubella) vaccines. The darker a county's color, the smaller the relative number of people that have been vaccinated.

Vaccination rate of 11 year olds

step 5 of 6

Explanation of our model

We simulate the spreading of various diseases based on three characteristics:

  • the risk of infection when you encounter a sick person
  • the number of days before you become contagious to other people, from the moment you have been infected ('infection interval')
  • the number of days you remain contagious to other people, before you are fully recovered

These three characteristics determine how many people you will infect during your illness (the 'reproduction number'), together with the number of social interactions you have. For simplicity, we assume that you only become contagious to others when you start to experience the first symptoms of sickness. In reality, this can be a few days earlier already. We further assume that everyone recovers and we ignore the risk of dying.

We only know the risk of infection fairly accurately for the measles, as well as its other characteristics. We use this to set the speed of the dots in such a way that the simulation generates on average the right reproduction number. We then use the same speed to set the infection risk for the other diseases, again aiming for the right reproduction number. We use the average results of several tens of simulation runs, because we are dealing with chances of infection and random motion of the people. Every simulation run will thus have a slightly different outcome.

We do not show the exact duration of an epidemic in the graph of infected people, because our model is a simplification of the real propagation. Our model is most useful to compare the dynamics of fast and slow spreading infectious diseases, not to draw hard conclusions about the exact course of any specific infection.

Parameters used in the simulation
R: reproduction number, Int: infection interval (days), BD: days contagious to others, BK: risk of infection upon contact, *approximation of our model
Source: Washington Post

disease R Int BD BK
measles 15 12 9 0.90
chicken pox 10 15 7 0.77*
influenza 4 4 7 0.13*
whooping cough 15 24 21 0.20*
mumps, rubella 6 18 12 0.13*
diphtheria 6 26 14 0.10*