[ TRACK // GARAGE LAB & HOBBY ]ID: sir-markov-chain
SIR Markov Chain — Stochastic Epidemic Simulation
Academic project (UniBo) for simulating epidemic spread. Replaces classic differential equations with Markovian transition matrices to capture random fluctuations in small groups.
PythonNumPyMatplotlibUniversity
FIG: SIR Markov Chain
Epidemiological Models: Determinism vs Stochasticity
The classic SIR model uses differential equations that work well on large populations but fail when numbers are small and random fluctuations take over. This academic project tackles the problem by simulating epidemic spread as a Discrete-Time Markov Chain.
How It Works
- Time advances in discrete steps (days).
- Individuals transition between Susceptible, Infectious, and Recovered states based on calculated probability distributions.
- Monte Carlo Simulations: Runs thousands of trajectories to output statistical confidence intervals and outbreak probabilities.