A Pandemic on a Paper
Only with time, we will be able to observe the impact of the restrictions in our everyday life on the development of the pandemic. Then how can we know whether the restrictions will really slow down the pandemic? With this project you can find it out yourself. With pencil and paper, you will become a researcher and you will investigate, how fast a disease can spread and what the restrictions are that will slow down the spread of the disease.
On the right, you can find the description of the project as a PDF document. It contains an info text about pandemics and, starting on page 2, an instruction for the project ‘Pandemic on a Paper’.
Below, you will find the simulation program that you can run right here on the website. With this you can extend your research. What took very long on the paper, you can now accelerate with the use of your computer. You can also look at the different situation repeatedly. The graph visualizes all your simulation runs so that you can compare it with your own graph on page 10.
This program serves the purpose to increase the knowledge of the project ‘Pandemic on Paper’. With the project, you can find out, how different measures can slow down the spread of a virus.
First, we will outline the general situation (Situation1, (No Restrictions)). A detailed description can be found in the project description, starting on page 2. We consider a population of 100 individuals, given by a table with 10 rows and 10 columns. Each field in the table is occupied by one person. Not infected people are displayed with a field in light grey. In the beginning, a randomly chosen person will be infected (blue field). In this simulation, unlike as in reality, all people will be infected. We are only interested in observing, how fast the disease will spread. Therefore, we will only consider the infection step and not the recovery step. It should be mentioned that, due to herd immunity, in reality not all people will get infected. After a while some proportion of the population will be immune so and – if this proportion is sufficiently high – the virus gets eradicated. As a result, control measures also lower the total number of infected people during a pandemic. This effect is not shown by the model presented here.
In our model in the scenario ‘Without Restrictions’, all direct neighbors of an infected person will be infected in each time step. Their fields will be marked in orange. These people are now infected themselves, so that the color of their field will change from orange to blue. Now all infected will move to a new field, which is randomly chosen. Then a new time step begins. We can now consider other situations with social distancing (Situation 2), with social distancing and less movements (Situation 3) or with the isolation of infected (Situation 4). The situations are described in detail in the project.
The measured are set by the different situations. Additionally, they can be individually chosen in a user-defined setting.
Just recently infected person