run.py

import covidmodel


#from covidmodel import Stage
#from covidmodel import AgeGroup
#from covidmodel import SexGroup
#from covidmodel import LockGroup

from covidmodel import *


cr_age_mortality = {
    AgeGroup.C80toXX: 0.148,
    AgeGroup.C70to79: 0.08,
    AgeGroup.C60to69: 0.036,
    AgeGroup.C50to59: 0.013,
    AgeGroup.C40to49: 0.004,
    AgeGroup.C30to39: 0.002,
    AgeGroup.C20to29: 0.002,
    AgeGroup.C10to19: 0.002,
    AgeGroup.C00to09: 0.0
}

# Observed distribution of mortality rage per sex
cr_sex_mortality = {
    SexGroup.MALE: 0.62,
    SexGroup.FEMALE: 0.38
}

cr_age_distribution = {
    AgeGroup.C80toXX: 0.023,
    AgeGroup.C70to79: 0.03,
    AgeGroup.C60to69: 0.078,
    AgeGroup.C50to59: 0.109,
    AgeGroup.C40to49: 0.128,
    AgeGroup.C30to39: 0.169,
    AgeGroup.C20to29: 0.169,
    AgeGroup.C10to19: 0.148,
    AgeGroup.C00to09: 0.146
}

# Observed distribution of mortality rage per sex
cr_sex_distribution = {
    SexGroup.MALE: 0.496,
    SexGroup.FEMALE: 0.504
}

# Value distribution per stage per interaction (micro vs macroeconomics)
cr_value_distibution = {
    ValueGroup.PERSONAL: {
        Stage.SUSCEPTIBLE: 1.0,
        Stage.INCUBATING: 1.0,
        Stage.SYMPDETECTED: -0.2,
        Stage.ASYMPTOMATIC: 1.0,
        Stage.ASYMPDETECTED: -0.2,
        Stage.SEVERE: -5.0,
        Stage.RECOVERED: 0.8,
        Stage.DECEASED: 0
    },
    ValueGroup.PUBLIC: {
        Stage.SUSCEPTIBLE: 10.0,
        Stage.INCUBATING: 10.0,
        Stage.SYMPDETECTED: -20.0,
        Stage.ASYMPTOMATIC: 10.0,
        Stage.ASYMPDETECTED: -25,
        Stage.SEVERE: -250.0,
        Stage.RECOVERED: 5,
        Stage.DECEASED: -1
    }
}

model_params = {
    "N":50,
    "width":10,
    "height":10,
    "distancing": False,
    "amort": cr_age_mortality,
    "smort": cr_sex_mortality,
    "adist": cr_age_distribution,
    "sdist": cr_sex_distribution,
    "avinc": 9,
    "avrec": 20,
    "pasympt": 0.2,
    "pcont": 0.04,
    "pdet": 0.0,
    "plock": 0.0,
    "peffl": 1.0,
    "psev": 0.10,
    "ddet": 35,
    "dimp": 7,
    "stvald": cr_value_distibution,
    "tcost": 200,
    "aper": 1.0,
    "apub": 1.0}



model =CovidModel(**model_params)

for i in range(2):
    model.step()

output = model.datacollector.get_model_vars_dataframe()

print (output)