SIR Modelling of spread of COVID-19 🦠

Model 1. SIR model for an infectious disease:

The SIR model breaks down the population into three-subgroups on the basis of infection.

• Susceptible. The subpopulation at risk of contracting the disease
• Infectious. The subpopulation that has become infected.
• Recovered. The subpopulation that has recovered from infection and is thought to be immune to the disease.

Model 1

Model 2. SEIR model:

The SEIR model extends the SIR model by adding an additional population compartment containing those individuals who have been exposed to the virus but not yet infective.

• Exposed. The subpopulation that has been exposed to the disease but not yet infective.

Model 2

Model 3. SEIR model with Control:

With vaccines and social distancing norms designed to reduce transmission of the virus from individuals in the infective state to susceptible individuals. We provide a control parameter u to indicate the success of these attempts for modelling purposes. u=0 denotes no controls, while u=1 denotes complete isolation of infective individuals. The goal of this model is to see how a social distancing approach influences an epidemic's outcome.

Model 3

Simulation of SIR model using Mesa Agent-based modelling: 📺

Model the spread of COVID-19 using a model based on the SIR model (susceptible, infectious, recovered). The cells are arranged in a grid and several agents (people) migrate between adjacent cells, potentially infecting one another.

Assumptions:

• We have a set number of agents (adjustable parameter) who are given random cells in the grid at the start.
• Throughout the simulation, a fixed percentage (adjustable parameter) of the agents are masked or unmasked.
• At every step, an agent either stays at his/her cell or moves to an adjacent one.
• When a susceptible agent is in the same cell as an infected agent, the chance of infection (adjustable parameter) differs between masked and unmasked agents.
• If an agent is infected, he/she recovers and becomes immune after a certain number of simulation steps (adjustable parameter).
• Immunity goes away after a certain number of steps (adjustable parameter) and the agent becomes susceptible once again.

Visuals:

• Agents will be represented as circles in our grid.
• Susceptible agents are blue, infected are orange, recovered and immune are green.
• If a circle is (not) filled it means the agent is (not) masked.

Simulation	Line Chart
	The following line chart dynamically shows us the number of susceptible, infected, and recovered agents throughout the simulation: