1. A blue cell becomes red cell at the next step (iteration) if at least one neighboring cell is red (has virus).
2. Each red cell has a certain chance (like 60%) of becoming blue cell (healthy person) at the next step.
3. If a blue cell does not have at least one healthy neighbor, it does not survive.
4. If a blue cell has more than 3 neighbors (healthy or unhealthy), it is infected.
Let us start with some healthy people and certain number of infected people. Let us also create a neighborhood with some cluster of people, some quarantined persons, a crowd, random people etc.
Let us write a simple computer program and run it to find out if the virus spread dies out or goes on forever.
Program in simple language:
Do n times:
Scan all the cells in the grid one by one.
1. For each cell: Count the healthy neighbors and unhealthy neighbors.
2. carry out the four rules.
3. move to next cell.
If n iterations are not completed, go to beginning.
After the execution of the program, look at the screen. If the grid is mostly blue, the viral infection is dying out. If it is reddish, adjust rules, initial conditions, and rerun the program.
Arrive at proper rules and conditions and implement in your neighborhood.
This is not a correct mathematical model. But an attempt in that direction. The highlight is visual representation. Anyone can experiment with it.
This process is derived from "game of life" based on cellular Automata.
Game of life is used to study self-organizing systems. It is the study of how elaborate patterns and behavior can appear from quite simple rules. It helps us to understand, how the petals on a rose or the strips on a zebra can arise from a tissue of living cells growing together.
Note: The principle can be applied not only for people but for healthy cells and infected cells also.
Suppose you include any resistance to spread of virus like temperature, medicine, etc., the picture will completely change.
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