NetLogo User Community Models

(back to the NetLogo User Community Models)

Download If clicking does not initiate a download, try right clicking or control clicking and choosing "Save" or "Download". Try It in NetLogo Web

## WHAT IS IT?

This is a model that shows how the speed of spread of a virus changes according to the amount of immobile population and how it contributes to what has been colloquially called "flattening the curve."

## HOW IT WORKS

There is a healthy population (green circles), of which a percentage does not move emulating the "stay at home" restriction and the rest moves randomly. A person in the mobile population is sick (red circle) with a virus that infects when it comes into contact with healthy people. These newly infected people in turn infect other healthy people.
Infected people are removed from the screen, enter a hospital and occupy a bed. The time that passes between a person is infected and finally decides to hospitalize is random. After a certain time of occupying a bed, the person becomes immune, leaves the bed and reappears mobile on the screen (gray circle). This dynamic occurs in a context of a limited number of hospital beds.
The simulation stops when there are no longer any sick people or when there are no more beds available.

## HOW TO USE IT

1) Assign total population amount in the "population" slider.
2) Input the percentage of population that will remain fixed in "%fixed-population".
3) Input the total number of hospital beds in "beds".
4) Press the "setup" button to generate the assigned population.
5) Press the "go" button to start or pause the model.

## THINGS TO NOTICE

Observe in the plot if at any time the number of sick population exceeds the number of available beds, which is an undesired scenario.

Observe how the curve "flattens" as the percentage of fixed people increases.

## THINGS TO TRY

Try with different percentages of fixed people and compare the outputs of the amount of sick population.
Test with these percentages until the number of sick population does not exceed the number of beds available, which is a desirable scenario.

## CREDITS AND REFERENCES

This model was inspired by the Washington Post article titled Why outbreaks like coronavirus spread exponentially, and how to “flatten the curve” by Harry Stevens (https://www.washingtonpost.com/graphics/2020/world/corona-simulator/)