autoemulate.simulations.epidemic

class EpidemicSimulator(param_ranges={'beta': (0.1, 0.5), 'gamma': (0.01, 0.2)})

Bases: Simulator

Simulator of infectious disease spread (SIR).

sample_forward(params)

Parameters:

params (dict[str, float]) – Dictionary of input parameter values to simulate: - beta: the transimission rate per day - gamma: the recovery rate per day

Returns:

infection – Peak infection rate.

Return type:

np.ndarray

simulate_epidemic(x, N=1000, I0=1)

Simulate an epidemic using the SIR model.

Parameters:

• x (array-like) – The parameters of the SIR model. The first element is the transmission rate (beta) and the second element is the recovery rate (gamma).

• N (int, optional) – The total population size.

• I0 (int, optional) – The initial number of infected individuals.

Returns:

peak_infection_rate – The peak infection rate as a fraction of the total population.

Return type:

float