Set up a model

Initialize a model (agents and network).

setup_model(
  agent_count,
  age_dist,
  p_female,
  seir_dist,
  p_med_cond,
  p_symptomatic,
  trans_df = NULL,
  prog_df = NULL,
  home_nw_params = NULL,
  social_nw_params = NULL,
  work_nw_params = NULL
)

Arguments

agent_count	The number of agents to generate parameters for.
age_dist	A function to sample from a probability distribution or else a vector or list of ages. The vector will be repeated if necessary to produce enough agents.
p_female	A probability of being female or else a vector or list of sexes ("M" or "F") or logical (TRUE for female, FALSE for male). The vector will be repeated if necessary to produce enough agents.
seir_dist	A function to sample from a probability distribution or else a vector or list of SEIR statuses ("S", "E", "I", or "R"). The vector will be repeated if necessary to produce enough agents.
p_med_cond	A probability of having a medical condition or else a vector or list of medical conditions (logical: TRUE or FALSE). The vector will be repeated if necessary to produce enough agents.
p_symptomatic	A probability of being symptomatic if infectious, or else a vector or list of symptomatic status if infectious (logical: TRUE or FALSE). The vector will be repeated if necessary to produce enough agents.
trans_df	A data frame of parameters for disease transmission probability distributions. Columns are: age_bkt: The age bracket (ordered factor). sex: The sex (factor with levels "M" and "F"). med_cond: Has a medical condition (logical). sympt: Has symptoms of COVID-19, if infectious (logical). mu_shed: Mean of the shedding parameter distribution. sigma_shed: Scale (standard deviation) of the shedding parameter distribution. mu_susc: Mean of the susceptibility parameter distribution sigma_susc: Scale (standard deviation) of the susceptibility parameter distribution.
prog_df	A data frame of parameters for disease progression probability distributions. Columns are: age_bkt: The age bracket (ordered factor). sex: The sex (factor with levels "M" and "F"). med_cond: Has a medical condition (logical). sympt: Has symptoms of COVID-19, if infectious (logical). shape_ei: Shape parameter for progression from "E" to "I" compartment. scale_ei: Scale parameter for progression from "E" to "I" compartment. shape_ir: Shape parameter for progression from "I" to "R" compartment. scale_ir: Scale parameter for progression from "I" to "R" compartment.
home_nw_params	A named list with parameters for the home-contacts network. The list should have elements: freq: The frequency of contacts in the network (contacts per day) intens: The intensity of contacts in the network topol: The topology of the network: "smallworld" or "Barabasi Albert". nbrw: The size of the neighborhood (small world) or the number of edges to add per time step (BA). p_rewire: The probability of rewiring an edge (small world) or the power of the preferential attachments (BA).
social_nw_params	A named list with parameters for social contacts.
work_nw_params	A named list with parameters for work contacts.

Value

A named list of the model: agents, network, contagion probabilities for disease transmission, and transition probabilities for progress to the next stage of the disease.

Examples

# ADD_EXAMPLES_HERE