Huo2017 - SEIS epidemic model with the impact of media Lab

{
  "io": {
    "inputs": [
      {
        "name": "transmission_rate",
        "label": "Transmission Rate",
        "maps_to": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.transmission_rate"
      },
      {
        "name": "recovery_rate",
        "label": "Recovery Rate",
        "maps_to": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.recovery_rate"
      }
    ],
    "outputs": [
      {
        "name": "state",
        "label": "Model state",
        "maps_to": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.state"
      },
      {
        "name": "summary",
        "label": "Simulation summary",
        "maps_to": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.summary"
      },
      {
        "name": "species_labels",
        "label": "Species labels",
        "maps_to": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.species_labels"
      },
      {
        "name": "exposed_individuals_e",
        "label": "Exposed Individuals (E)",
        "maps_to": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.exposed_individuals_e"
      },
      {
        "name": "infected_individuals_i",
        "label": "Infected Individuals (I)",
        "maps_to": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.infected_individuals_i"
      },
      {
        "name": "susceptible_individuals_s",
        "label": "Susceptible Individuals (S)",
        "maps_to": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.susceptible_individuals_s"
      },
      {
        "name": "message_m",
        "label": "Message (M)",
        "maps_to": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.message_m"
      },
      {
        "name": "total_population_n",
        "label": "Total population (N)",
        "maps_to": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.total_population_n"
      }
    ]
  },
  "title": "Huo2017 - SEIS epidemic model with the impact of media Lab",
  "models": [
    {
      "path": "owned/models/epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model",
      "alias": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model",
      "parameters": {
        "model_path": "data/BIOMD0000000715.xml",
        "integration_step": 0.1
      },
      "provenance": {
        "owned_path": "owned/models/epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model"
      }
    },
    {
      "path": "owned/models/visualisation",
      "alias": "visualisation",
      "provenance": {
        "owned_path": "owned/models/visualisation"
      }
    }
  ],
  "wiring": [
    {
      "to": [
        "visualisation.epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model_state"
      ],
      "from": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.state"
    },
    {
      "to": [
        "visualisation.epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model_summary"
      ],
      "from": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.summary"
    },
    {
      "to": [
        "visualisation.epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model_species_labels"
      ],
      "from": "epidemiology_sbml_huo2017_seis_epidemic_model_with_the_impact_of_m_biomd0000000715_model.species_labels"
    }
  ],
  "runtime": {
    "duration": 10,
    "initial_inputs": {},
    "communication_step": 0.1
  },
  "description": "Single-model lab wrapper for Huo2017 - SEIS epidemic model with the impact of media. Hai-Feng Huo, Peng Yang & Hong Xiang. Stability and bifurcation for an SEIS epidemic model with the impact of media.",
  "schema_version": "2.0"
}