Description

1. First, take a look at this code here:
https://colab.research.google.com/github/AllenDowney/ModSimPy/blob/master/chapters/cha p11.ipynb
2. Now, tweak the values of 𝛃 (=1/tc) and 𝛄 (=1/tr) and generate the graph of time against infection for eight (8) pairs of these values. Mark the maximum infection moment with a blue dot.
3. Next, read the code in this link carefully:
https://colab.research.google.com/github/AllenDowney/ModSimPy/blob/master/chapters/cha p13.ipynb
4. Now, generate graph of 𝛃 against fraction of infection for 𝛄 in {0.2, 0.4, 0.6, 0.8, 1.0}. Likewise, generate graph of 𝛄 against fraction of infection for 𝛃 in {0.2, 0.4, 0.6, 0.8, 1.0}. See the code in the link to see how to do it.
5. Lastly, imagine you divide the population into four compartments: S, I, R, and V (for vaccinated). If the vaccination rate is 𝝰, then 𝛅V/𝛅t should be 𝝰S2, and 𝛅S/𝛅t should be -𝛃SI – 𝛅V/𝛅t. Implement this SIR-V model, i.e. SIR model with vaccination. Your code should not implement vaccination like this code here:
https://colab.research.google.com/github/AllenDowney/ModSimPy/blob/master/chapters/cha p12.ipynb
Your code should be well-commented.
The programming language should be Python 3.
1. Robert M. Grell, A Di erential Equations Analysis of Pandemic Disease Spread in an Apocalyptic State. Source: https://dra.american.edu/islandora/object/1112capstones%3A33/datastream/PDF/view
http://www.math-cs.gordon.edu/courses/mat225/projects/p2/duke-sir.pdf
4. 3Blue1Brown, Playlist: “COVID-19”. Source: https://youtube.com/playlist?list=PLZHQObOWTQDOcxqQ36Vow3TdTRjkdSvT
5. Primer, Video: “Epidemic, Endemic, and Eradication Simulations”. Source: https://www.youtube.com/watch?v=7OLpKqTriio
6. David Randall Miller, “I programmed some creatures. They Evolved.” Source: