inputs.defaults

# The number of diseases
agent.number_of_diseases = 1
# A list of strings of the names of the diseases, one for each disease. Will default to disease00, disease01, ...
agent.disease_names = default00
# The type of initialization: census or urbanpop.
agent.ic_type = census
# The input data file for census ic_type.
# no default, must be set when ic_type is census
# agent.census_filename
# The input worker flow filename for census ic_type.
# no default, must be set when ic_type is census
# agent.workerflow_filename
# The number of agents in a neighborhood.
agent.nborhood_size = 500
# The number of agents in a workgroup.
agent.workgroup_size = 20
# The input data file for urbanpop ic_type. Do not include the extension. There must be two files, with extensions .csv and .idx.
# no default, must be set when ic_type = census
# agent.urbanpop_filename
# The input data file containing the airports.
# no default, must be set when agent.air_travel_int != -1
# agent.airports_filename
# The input data file containing air traffic.
# no defalut, must be set when agent.air_travel_int != -1
# agent.air_traffic_filename
# The nnumber of time steps (days) for the simulation.
agent.nsteps = 1
# The plotting interval in time steps; set to -1 for no plotting.
agent.plot_int = -1
# The time steps between random travel events; set to -1 for no random travel.
agent.random_travel_int = -1
# The probability of an agent traveling randomly in any travel event.
agent.random_travel_prob = 0.0001
# The time steps between air travel events; set to -1 for no air travel.
agent.air_travel_int = -1
# The time steps between writing aggregated data; set to -1 to disable writing.
agent.aggregated_diag_int = -1
# The prefix to use when writing aggregated data.
agent.aggregated_diag_prefix = cases
# The random seed used in the simulation.
agent.seed = 0
# The time step on which to start shelter-in-place; set to -1 to disable.
agent.shelter_start = -1
# The time steps that shelter-in-place lasts.
agent.shelter_length = 0
# The compliance rate for shelter-in-place, i.e. the probability of an agent actually sheltering.
agent.shelter_compliance = 0.95
# The probability of an agent withdrawing on day 0, day 1 and day 2 for age groups u5, 5-17, 18-29, 30-49, 50-64, 65+
agent.symptomatic_withdraw_compliance_day_0 = 0.3 0.3 0.3 0.3 0.3 0.3
agent.symptomatic_withdraw_compliance_day_1 = 0.8 0.6 0.5 0.5 0.5 0.5
agent.symptomatic_withdraw_compliance_day_2 = 0.9 0.8 0.7 0.7 0.7 0.7
# The compliance rate for children when schools are closed. This reduces the probability of transmission in the neighborhood.
agent.child_compliance = 0.5
# A factor for increasing transmission by children within households when schools are closed.
agent.child_HH_closure = 2
# The ratio of educators to students for school levels none, college, high, middle, elementary, daycare. Ignored for none.
# This is only used for the census data.
agent.student_teacher_ratio = 0 15 15 15 15 15
# The maximum grid size used for MPI domain decomposition. Adjusting this can change the computation time and load balance.
agent.max_box_size = 16

# A list of file names, one per disease, each one of which will be the output for the counts of the statuses for that disease.
# defalut for one disease
diag.output_filename = output.dat
# default for multiple diseases
# diag.output_filename = output_[disease name].dat

# Disease options. Use disease.[key] = [value] with only one disease.
# Use disease_[disease name].[key] = [value] with multiple diseases.

# The process to set the initial cases. Random means allocate randomly, and file means allocate from a file of data inputs.
disease.initial_case_type = random
# Input data file containing initial cases, one per disease. Only used if the initial_case_type is random.
# no default, must be set when disease.initial_case_type = file for a single disease
# disease.case_filename
# The number of initial cases for each disease. Not needed when reading initial cases from files.
# no default, must be set for each disease when disease_[disease name].initial_case_type = file for multiple diseases
# disease.case_filename_[disease name]
disease.num_initial_cases = 0
# no default, must be set for each disease when disease_[disease name].num_initial_cases = random for multiple diseases
# disease.num_initial_cases_[disease name] = 0
# The fraction of agents (0.0 to 1.0) that are initially immune for each disease.
# This sets agents as immune at initialization. Each initially immune agent is placed at a random
# point in their immunity period. The immunity period duration is sampled from a Gamma distribution
# using the immune_length_alpha and immune_length_beta parameters, and the agent's remaining immunity
# is set to a uniform random value between 0 and that duration.
# This feature works for both Census and UrbanPop initialization types.
disease.initial_immunity_fraction = 0.0
# For multiple diseases, use disease-specific parameters:
# disease_[disease name].initial_immunity_fraction = 0.0

# Probability of transmission given contact.
disease.p_trans = 0.2
# Probability of being asymptomatic.
disease.p_asymp = 0.4
# Relative infectiousness of asymptomatic individuals.
disease.asymp_relative_inf = 0.75
# Vaccine efficacy. Not yet implemented; leave at 0.
disease.vac_eff = 0
# Alpha parameter for the immume length Gamma distribution. The immune length is the length in days that agents are immune after recovery from an infection.
disease.immune_length_alpha =540.0
# Beta parameter for the immume length Gamma distribution. The immune length is the length in days that agents are immune after recovery from an infection.
disease.immune_length_beta = 0.33
# Alpha parameter for the latent length Gamma distribution. The latent length is the length in days from infection until an agent becomes infectious.
disease.latent_length_alpha = 9.0
# Beta parameter for the latent length Gamma distribution. The latent length is the length in days from infection until an agent becomes infectious.
disease.latent_length_beta = 0.33
# Alpha parameter for the infectious length Gamma distribution. The infectious length is the length in days of the time an agent is infectious.
disease.infectious_length_alpha = 36.0
# Beta parameter for the infectious length Gamma distribution. The infectious length is the length in days of the time an agent is infectious.
disease.infectious_length_beta = 0.17
# Alpha parameter for the incubation length Gamma distribution. The incubation length is the length in days from the time of infection until symptoms develop.
disease.incubation_length_alpha = 25.0
# Beta parameter for the incubation length Gamma distribution. The incubation length is the length in days from the time of infection until symptoms develop.
disease.incubation_length_beta = 0.2
# Alpha parameter for the hospital_delay length Gamma distribution. The hospital_delay length is the length in days after developing symptoms that agents seek treatment.
disease.hospital_delay_length_alpha = 1.0
# Beta parameter for the hospital_delay length Gamma distribution. The hospital_delay length is the length in days after developing symptoms that agents seek treatment.
disease.hospital_delay_length_beta = 1.0

# Number of days in hospital for age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.hospitalization_days = 3 3 3 3 8 7
# Alpha parameter for days in hospital Gamma distribution, for age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.hospitalization_days_alpha = 1.33 1.33 1.33 1.33 0.5 0.57
# Beta parameter for days in hospital Gamma distribution, for age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.hospitalization_days_beta = 1.5 1.5 1.5 1.5 4.0 3.5

# Transmission probabilites at the community level, for both work and home locations,
# for the age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.xmit_comm = 0.000018125 0.000054375 0.000145 0.000145 0.000145 0.0002175
# Transmission probabilites at the neighborhood level, for both work and home locations,
# for the age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.xmit_hood = 0.0000725 0.0002175 0.00058 0.00058 0.00058 0.00087
# Transmission probabilites at the household level, where the infectious agent is an adult,
# for the age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.xmit_hh_adult = 0.3 0.3 0.4 0.4 0.4 0.4
# Transmission probabilites at the household level, where the infectious agent is a child,
# for the age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.xmit_hh_child = 0.6 0.6 0.3 0.3 0.3 0.3
# Transmission probabilites at the neighborhood cluster level, where the infectious agent is an adult,
# for the age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.xmit_nc_adult = 0.04 0.04 0.05 0.05 0.05 0.05
# Transmission probabilites at the neighborhood cluster level, where the infectious agent is a child,
# for the age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.xmit_nc_child = 0.075 0.075 0.04 0.04 0.04 0.04
# Transmission probabilites within schools, where both agents are adults or both are children,
# for school levels none, college, high, middle, elementary, daycare. Ignored for none.
disease.xmit_school = 0 0.0315 0.0315 0.0375 0.0435 0.15
# Transmission probabilites within schools, where transmitter is an adult and receiver is a child,
# for school levels none, college, high, middle, elementary, daycare. Ignored for none.
disease.xmit_school_a2c = 0 0.0315 0.0315 0.0375 0.0435 0.15
# Transmission probabilites within schools, where transmitter is a child and receiver is an adult,
# for school levels none, college, high, middle, elementary, daycare. Ignored for none.
disease.xmit_school_c2a = 0 0.0315 0.0315 0.0375 0.0435 0.15
# Transmission probability within workgroups
disease.xmit_wwork = 0.0575

# Probability of hospitalization when disease symptoms first appear, for age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.CHR = 0.0104 0.0104 0.070 0.28 0.28 1.0
# Probability of moving from hospitalization to ICU, for age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.CIC = 0.24 0.24 0.24 0.36 0.36 0.35
# Probability of moving from ICU to ventilator, for age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.CVE = 0.12 0.12 0.12 0.22 0.22 0.22
# Probability of death when in hospital, for age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.hospCVF = 0 0 0 0 0 0
# Probability of death when in the ICU, for age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.icuCVF = 0 0 0 0 0 0.26
# Probability of death when on a ventilator, for age groups 0-4, 5-17, 18-29, 30-49, 50-64, 64+
disease.ventCVF = 0.20 0.20 0.20 0.45 0.45 1.0