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Parse MetaRVM Configuration File

Source: R/parse_config.R
parse_config.Rd

Reads and parses a YAML configuration file for MetaRVM simulations, extracting all necessary parameters for epidemic modeling including population data, disease parameters, mixing matrices, vaccination schedules, and simulation settings.

Usage

parse_config(config_file, return_object = FALSE)

Arguments

config_file

Character string. Path to a YAML configuration file containing model parameters and settings.

return_object

Logical. If TRUE, returns a MetaRVMConfig object for method chaining and enhanced functionality. If FALSE (default), returns a named list for backward compatibility.

Value

If return_object = FALSE (default), returns a named list containing:

N_pop

Number of population groups

pop_map

Data.table with population mapping and demographics

S_ini, E_ini, I_asymp_ini, I_presymp_ini, I_symp_ini, H_ini, D_ini, P_ini, V_ini, R_ini

Initial compartment populations

vac_time_id, vac_counts, vac_mat

Vaccination schedule data

m_wd_d, m_wd_n, m_we_d, m_we_n

Contact mixing matrices

ts, tv, ve, dv, de, dp, da, ds, dh, dr, pea, psr, phr

Disease parameter matrices (nsim × N_pop)

start_date

Simulation start date as Date object

sim_length

Simulation length in days

nsim

Number of simulation instances

random_seed

Random seed used (if any)

delta_t

Time step size (fixed at 0.5)

chk_file_names, chk_time_steps, do_chk

Checkpointing configuration

If return_object = TRUE, returns a MetaRVMConfig object with methods for parameter access and validation.

Details

The function processes a comprehensive YAML configuration file with the following main sections:

Simulation Configuration:

  • random_seed: Optional random seed for reproducibility

  • nsim: Number of simulation instances (default: 1)

  • start_date: Simulation start date in MM/DD/YYYY format

  • length: Simulation length in days

  • checkpoint_dir: Optional checkpoint directory for saving intermediate results

  • checkpoint_dates: Optional list of dates to save checkpoints.

  • restore_from: Optional path to restore simulation from checkpoint

Population Data:

  • mapping: CSV file path containing population mapping with demographic categories

  • initialization: CSV file with initial population states (S0, I0, V0, R0, N)

  • vaccination: CSV file with vaccination schedule over time

Mixing Matrices: Contact matrices for different time periods:

  • weekday_day, weekday_night: Weekday contact patterns

  • weekend_day, weekend_night: Weekend contact patterns

Disease Parameters: Epidemiological parameters (can be scalars or distributions):

  • ts: Transmission rate for symptomatic individuals

  • tv: Transmission rate for vaccinated individuals

  • ve: Vaccine effectiveness

  • de, dp, da, ds, dh, dr: Duration parameters for different disease states

  • pea, psr, phr: Probability parameters for disease transitions

Sub-population Parameters: sub_disease_params allows specification of different parameter values for specific demographic categories (e.g., age groups, races).

The function supports stochastic parameters through distribution specifications with dist, mu, sd, shape, rate, etc.

Parameter Distributions

Disease parameters can be specified as distributions for stochastic modeling:

  • lognormal: dist: "lognormal", mu: value, sd: value

  • gamma: dist: "gamma", shape: value, rate: value

  • uniform: dist: "uniform", min: value, max: value

  • beta: dist: "beta", shape1: value, shape2: value

  • gaussian: dist: "gaussian", mean: value, sd: value

File Requirements

Population mapping file must contain columns:

  • population_id: Unique identifier for each population group

  • age: Age category (e.g., "0-4", "5-11", "12-17", "18-49", "50-64", "65+")

  • race: Race/ethnicity category

  • hcez: Geographic zone identifier

Population initialization file must contain: N (total population), S0, I0, V0, R0 (initial compartment counts)

Vaccination file must contain: date (MM/DD/YYYY format) and vaccination counts for each population group

See also

metaRVM for running simulations with parsed configuration MetaRVMConfig for the configuration object class process_vac_data for vaccination data processing

Author

Arindam Fadikar

Examples

if (FALSE) { # \dontrun{
# Parse configuration file and return list (backward compatible)
config <- parse_config("path/to/config.yaml")

# Parse and return MetaRVMConfig object for method chaining
config_obj <- parse_config("path/to/config.yaml", return_object = TRUE)

# Access parameters from config object
config_obj$get("N_pop")
config_obj$list_parameters()

# Use with MetaRVM simulation
results <- metaRVM(config_obj)
} # }