Back to Flu Math Games
1- Exponential Growth, Sampling without Replacement
2- Sampling with Replacement
3- Super Spreaders
4- R_{0} = 1.5
5- Initial Immunity
6- Statistical Flu Spread Simulation Tool

The following simulation was custom developed and designed specifically for the MIT BLOSSOMS Project to build on the concepts covered in the video lectures.

Parameter |
Description |
Allowed Values |
---|---|---|

N | Population Size | Input Value: Between 4 and 10,000 |

R_{0} |
Basic Reproductive Number | Input Value: Between 1.00 and 10.00 (up to 2 decimal points) |

I | Initial Immunity | Input Value: Between 0 and N |

Runs | The number of simulation runs | Input Value: Between 1 and 10 |

In this simulation, you will experiment with flu spread by varying several parameters involved using a statistical tool. For each set of parameters, you can specify the number of times you want the simulation to run in order to compare the results. At the end, you will have a tabular representation of the results along with a graphical representation, in addition to a summary of the runs.

R_{0} is calculated based on its floor and the probability of the fraction. For example, when R_{0} = 2.3, then when infection occurs, a person could infect 2 or 3 people (based on a random number generator) while keeping a 30% probability of infecting 3.

- You may wish to switch to full-screen view using the icon on the top right corner.
- Throughout the simulation, you will be directed to next steps.
- The top bar shown above has the following items:
- List of parameters used and their values
- A summary of the results for the simulation runs.
- At the end of a simulation run, click on the tab representing the number of the run for a report on the flu spread statistics along with a graphical representation.
- You may re-run the simulation on a different set of parameters by pressing the 'Reset' button.

Powered by: e-Learning Arabia