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Build Infection Process Model

Source: R/hestia_functions.R
make_infection_model.Rd

Build Infection Process Model

Usage

make_infection_model(..., mult_ih_inf_probs = FALSE, mult_eh_inf_probs = FALSE)

Arguments

...

a series of progress or transmit function calls

mult_ih_inf_probs

If FALSE then all intra-household infection probabilities are shared across infectious compartments. If TRUE, each infection compartment has a distinct probability.

mult_eh_inf_probs

If FALSE then all extra-household infection probabilities are shared across infectious compartments. If TRUE, each infection compartment has a distinct probability.

Value

A data frame with a row for each unique transition in the infection process model and the following columns:

  • "from", the name of the origin compartment

  • "to", the name of the destination compartment

  • "source", NA (so output columns match with transmit)

  • "rate_name", name of transition rate parameter if fitting

  • "rate_value", numeric value of transition rate if not fitting

  • "split_name", name of split parameter if fitting

  • "split_value", numeric value of split if not fitting

  • "source", names of compartment(s) that are the source of new infections

  • "mult_ih_inf_probs", a logical indicator for whether infectious compartments have separate (TRUE) or shared (FALSE) intra-household infection probabilities

Examples

# Basic SIR model with recovery rate gamma to be fit
make_infection_model(transmit(from = "S", to = "I"),
                     progress(from = "I", to = "R", gamma = NA))
#>   from to split_name split_value source rate_name rate_value mult_ih_inf_probs
#> 1    S  I         NA          NA      I      <NA>         NA             FALSE
#> 2    I  R         NA          NA   NULL     gamma         NA             FALSE
#>   mult_eh_inf_probs
#> 1             FALSE
#> 2             FALSE

# Split the infectious compartment into symptomatic (I_s) and asymptomatic
# (I_a) infections, with separate intra-household infection probabilities.
make_infection_model(
  transmit(from = "S",
           to = c("I_s", "I_a"),
           source = c("I_s", "I_a"),
           split = "phi"),
  progress(from = "I_s", to = "R", gamma_s = NA),
  progress(from = "I_a", to = "R", gamma_a = NA),
  mult_ih_inf_probs = TRUE)
#>   from  to split_name split_value   source rate_name rate_value
#> 1    S I_s        phi          NA I_s, I_a      <NA>         NA
#> 2    S I_a      1-phi          NA I_s, I_a      <NA>         NA
#> 3  I_s   R       <NA>          NA     NULL   gamma_s         NA
#> 4  I_a   R       <NA>          NA     NULL   gamma_a         NA
#>   mult_ih_inf_probs mult_eh_inf_probs
#> 1              TRUE             FALSE
#> 2              TRUE             FALSE
#> 3              TRUE             FALSE
#> 4              TRUE             FALSE