Difference between revisions of "Simulation of pandemic spread"
(→Introduction and problem definition) |
(→Method) |
||
| Line 11: | Line 11: | ||
=Method= | =Method= | ||
| + | An agent-based model in NetLogo is used to simulate the spread of the pandemic. This allows us to code our own scenario using different variables and helps us to get closer to the real pandemic evolution. | ||
=Model= | =Model= | ||
Revision as of 19:54, 10 January 2024
Title: Simulation of pandemic spread
Author: Daniel Kopecký
Method: Agent-based model
Tool: NetLogo
Contents
Introduction and problem definition
Not so long ago we had the COVID-19 pandemic, which showed us the shortcomings in dealing with this type of problem. Pandemic propagation simulation can be a key tool to model, analyse and predict the evolution of a pandemic. This model deals specifically with viral diseases. The aim of this simulation is to be able to predict the spread of a pandemic virus, whereby using appropriate values, it can simulate the approximate development of a pandemic in the Czechia.
Method
An agent-based model in NetLogo is used to simulate the spread of the pandemic. This allows us to code our own scenario using different variables and helps us to get closer to the real pandemic evolution.
Model
Environment
Agents
Movement
Spread of infection
End of the simulation
Variables
- init-population - Population at the beginning of the simulation
- init-infected - Number of infected at the start of the simulation
- recovery.rate - Rate of recovery of infected individuals
- init-immune - Number of immune individuals at the beginning of the simulation
- quarantine.effort - Quarantine effort (affects the chance of infecting an individual)
- transmission.rate - Rate of virus transmission between individuals
- infected-mortality - Virus mortality rate
- healthcare.capacity - Capacity of health facilities (affects the rate of death of individuals)
- immunity? - Turns immunity on or off
