def simulation_setup(cb,
species_details,
site_vector_props,
max_larval_capacity=4e8):
site_dir = os.path.join('sites', 'all')
# directories
cb.update_params({
"Demographics_Filenames": [
os.path.join(site_dir, "demographics.json"),
os.path.join(site_dir, "demographics_net_overlay.json")
],
"Air_Temperature_Filename":
os.path.join(site_dir, "air_temperature_daily.bin"),
"Land_Temperature_Filename":
os.path.join(site_dir, "air_temperature_daily.bin"),
"Rainfall_Filename":
os.path.join(site_dir, "rainfall_daily.bin"),
"Relative_Humidity_Filename":
os.path.join(site_dir, "relative_humidity_daily.bin")
})
# Find vector proportions for each vector
set_params_by_species(cb.params, [name for name in species_details.keys()])
larval_habs_per_site = {"NodeID": site_vector_props["node_id"]}
for species_name, species_modifications in species_details.items():
set_species_param(cb, species_name, "Adult_Life_Expectancy", 20)
set_species_param(cb, species_name, 'Vector_Sugar_Feeding_Frequency',
'VECTOR_SUGAR_FEEDING_EVERY_DAY')
for param, val in species_modifications.items():
if param == "habitat_split":
new_vals = {
hab: hab_prop * max_larval_capacity
for hab, hab_prop in val.items()
}
set_species_param(cb, species_name, "Larval_Habitat_Types",
new_vals)
larval_habs_per_site.update({
".".join([species_name, hab]):
site_vector_props[species_name]
for hab in val.keys()
})
else:
set_species_param(cb, species_name, param, val)
scale_larval_habitats(cb, pd.DataFrame(larval_habs_per_site))
def update_vector_params(cb):
set_params_by_species(cb.params, ['minimus', 'dirus'])
update_species_param(cb,
'minimus',
'Larval_Habitat_Types', {'WATER_VEGETATION': 2e7},
overwrite=True)
update_species_param(cb,
'minimus',
'Acquire_Modifier',
0.8,
overwrite=False)
update_species_param(cb,
'minimus',
'Adult_Life_Expectancy',
25,
overwrite=False) # target: 12
update_species_param(cb,
'dirus',
'Larval_Habitat_Types', {
'CONSTANT': 1e7,
'TEMPORARY_RAINFALL': 7e7
},
overwrite=True)
update_species_param(cb,
'dirus',
'Adult_Life_Expectancy',
30,
overwrite=False) # target: 14
update_species_param(cb, 'minimus', 'Anthropophily', 0.5, overwrite=False)
update_species_param(cb, 'dirus', 'Anthropophily', 0.5, overwrite=False)
capacity_dist_per_year = {
"Times": [0, 1, 245, 275, 364],
"Values": [0.2, 0.2, 0.7, 3, 3]
}
linear_spline = {
"LINEAR_SPLINE": {
"Capacity_Distribution_Number_Of_Years": 1,
"Capacity_Distribution_Over_Time": capacity_dist_per_year,
"Max_Larval_Capacity": 3e7
}
}
update_species_param(cb,
'minimus',
'Larval_Habitat_Types',
linear_spline,
overwrite=False)
def __call__(self, cb):
return set_params_by_species(cb.params, self.species, 'MALARIA_SIM')
"HEG_Homing_Rate": 0.0,
"HEG_Fecundity_Limiting": 0.0,
"HEG_Model": "OFF",
"x_Temporary_Larval_Habitat": 1,
"Egg_Hatch_Density_Dependence": "NO_DENSITY_DEPENDENCE",
"Enable_Temperature_Dependent_Egg_Hatching": 0,
"Enable_Egg_Mortality": 0,
"Enable_Drought_Egg_Hatch_Delay": 0,
"Temperature_Dependent_Feeding_Cycle": "NO_TEMPERATURE_DEPENDENCE",
"Genome_Markers": []
}
params = cohort_params.copy()
params.update(disease_params)
params.update(larval_habitat.params)
set_params_by_species(params, ["arabiensis", "funestus", "gambiae"])
# --------------------------------------------------------------
# Individual-mosquito model (rather than cohort-based model)
# --------------------------------------------------------------
individual_params = cohort_params.copy()
individual_params["Vector_Sampling_Type"] = "TRACK_ALL_VECTORS"
# --------------------------------------------------------------
# Using VECTOR_SIM as a vivax model
# --------------------------------------------------------------
vivax_semitropical_params = disease_params.copy()
vivax_semitropical_params.update({
"Incubation_Period_Distribution": "FIXED_DURATION",
# Malaria disease + drug parameters
# --------------------------------------------------------------
disease_params = {
"Malaria_Model": "MALARIA_MECHANISTIC_MODEL",
"Malaria_Strain_Model": "FALCIPARUM_RANDOM_STRAIN"
}
disease_params.update(infection.params)
disease_params.update(immunity.params)
disease_params.update(symptoms.params)
params = copy.deepcopy(disease_params)
params["PKPD_Model"] = "CONCENTRATION_VERSUS_TIME"
params["Malaria_Drug_Params"] = drug_params
params["Genome_Markers"] = []
set_params_by_species(params, ["arabiensis", "funestus", "gambiae"],
"MALARIA_SIM")
# --------------------------------------------------------------
# Innate immunity only
# --------------------------------------------------------------
innate_only = copy.deepcopy(params)
innate_only.update({
"Antibody_Capacity_Growth_Rate": 0,
"Max_MSP1_Antibody_Growthrate": 0,
"Min_Adapted_Response": 0
})