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🦠 Epidemic Dynamics

β (transmission)
γ (recovery)
σ (incubation)
Vaccination %
Quarantine %
Speed
R₀ = 0.0
Basic reproduction number
Susceptible
0
Exposed
0
Infectious
0
Recovered
0
Susceptible
Exposed
Infectious
Recovered
Vaccinated
← Time →

🦠 Epidemic Dynamics — SEIR Model

A single infected person in a city. How many will fall ill? When does the wave peak? The SEIR model — Susceptible, Exposed, Infectious, Removed — is the mathematical engine behind every public health response, from influenza to COVID-19.

🔬 What It Demonstrates

The model divides population into four compartments connected by differential equations. The key parameter is R₀ (basic reproduction number): infections grow if R₀ > 1, die out if R₀ < 1. Herd immunity requires a fraction 1 − 1/R₀ of the population to be immune.

🎮 How to Use

Adjust Transmission rate β, Recovery rate γ and Incubation period σ and watch the epidemic curve reshape. Try setting vaccine coverage to cross the herd immunity threshold. The live graph shows each compartment over time.

💡 Did You Know?

During the 2014 Ebola outbreak in West Africa, models with R₀ ≈ 1.5–2 predicted exponential growth. WHO interventions that cut β by 50 % were enough to suppress the epidemic. The difference between an R₀ of 1.1 and 0.9 is the difference between a pandemic and extinction.