https://github.com/ajithksenthil/epidemic-simulation
Customizable Simulation that models SIR variables in Epidemics
https://github.com/ajithksenthil/epidemic-simulation
modeling simulation
Last synced: 5 months ago
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Customizable Simulation that models SIR variables in Epidemics
- Host: GitHub
- URL: https://github.com/ajithksenthil/epidemic-simulation
- Owner: ajithksenthil
- License: mit
- Created: 2021-02-18T01:10:10.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2023-11-08T20:50:06.000Z (over 2 years ago)
- Last Synced: 2025-02-08T12:31:28.675Z (over 1 year ago)
- Topics: modeling, simulation
- Language: CMake
- Homepage:
- Size: 23.4 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Infection Prediction: An SIR Model Epidemic Simulator
**Author**: Ajith Senthil
Overview
Infection Prediction is a sophisticated epidemic simulation tool that employs the Susceptible-Infected-Recovered (SIR) model to analyze and predict the spread of infectious diseases. This project encapsulates the intricate behaviors of disease transmission, offering a simulated environment that mirrors real-world scenarios of epidemics.
Key Features
Dynamic SIR Modelling: Simulates the three critical variables of epidemic modeling: Susceptible (S), Infected (I), and Recovered (R) or deceased individuals.
Transition Rate Analysis: Calculates the rate of change between the SIR variables over time, providing insights into the disease's progression.
Visualization Tools: Utilizes libraries like CairoBasic, matplotlib-cpp, and VboMesh to generate informative graphs.
User Interactivity: Allows modification of external variables such as vaccination rates and public health interventions to observe their impact on the epidemic's trajectory.
Real-Time Simulation: Aims to include a GUI that shows the interactions between individual agents and the effects of environmental changes.