/Covid-19-Simulation

Corona Virus (COVID-19) spreading simulation in a close community with mathematical scaling and probability scaled according to the spread of infection, revovery and deaths.

Primary LanguageJupyter NotebookMIT LicenseMIT

Covid-19-Simulation

Corona Virus (COVID-19) spreading simulation in a close community with mathematical scaling and probability scaled according to the spread of infection, recovery and deaths.

Simulations are available on youtube and Linkedin in form of a video.

Youtube : https://youtu.be/3WJU6aZyeLg

LinkedIn : https://www.linkedin.com/posts/achaldixit22_socialdistancing-quarantine-coronavirus-activity-6649638030665711616-9c3S

Simulated visualisations showing the spreading of COVID-19 under different scenarios based on Random Walks. There are 6 scenarios :

  1. Spreading with 100% movement and no recovery.
  2. Spreading with 100% movement and recovery.
  3. Spreading with 100% movement, recovery and deaths at 11% rate.
  4. Spreading with 30% movement and no recovery.
  5. Spreading with 30% movement and recovery.
  6. Spreading with 30% movement, recovery and deaths at 11% rate.

What we need to observe is that what is the outcome after same period of time. At 100% movement all 11% die which are randomly chosen among all the particle, whereas at 30% movement only 4 particles die.

Visulaizations are made using Python3 and libraries like matplotlib, numpy, animation, pyplot, etc.

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Author : Achal Dixit | Jarach_2.0.9