Loss of immunity for immunized and recovered nodes

Here, we immunize the 500 nodes with highest eigenvector centrality, using a vaccine with 90% efficacy. We also apply different immunity-loss probabilities to vaccinated nodes (0.1) and naturally-recovered nodes (0.01).

import networkx as nx
from contagion import contagion

network = contagion.ContactNetwork(
    nx.barabasi_albert_graph(1000, 5))

immunization = contagion.Immunization(network)
Im_array = immunization.generate_centrality_immunization_array(
    Q = 500,
    centrality_type='eigenvector',
    order='highest')

network.immunize_network(
    Im = Im_array,
    im_type = "vaccinate",
    im_starts_after = 5,
    efficacy = 0.9)

sim = contagion.Contagion(
    network = network,
    beta = 0.15,
    gamma = 0.05,
    omega = (0.01, 0.1))

sim.plot_simulation(steps = 50)