rename incfn to incubation_period

Author: joshwlambert

R/aux_functions.R

@@ -42,7 +42,7 @@ inf_fn <- function(inc_samp = NULL, k = NULL) {
 #'   disp.com = 0.16,
 #'   disp.iso = 1,
 #'   onset_to_isolation = \(x) stats::rweibull(n = x, shape = 1.65, scale = 4.28),
-#'   incfn = \(x) stats::rweibull(n = x, shape = 2.322737, scale = 6.492272),
+#'   incubation_period = \(x) stats::rweibull(n = x, shape = 2.322737, scale = 6.492272),
 #'   k = 0,
 #'   quarantine = FALSE
 #' )
@@ -86,7 +86,7 @@ extinct_prob <- function(outbreak_df_week = NULL, cap_cases  = NULL, week_range
 #'   disp.com = 0.16,
 #'   disp.iso = 1,
 #'   onset_to_isolation = \(x) stats::rweibull(n = x, shape = 1.65, scale = 4.28),
-#'   incfn = \(x) stats::rweibull(n = x, shape = 2.322737, scale = 6.492272),
+#'   incubation_period = \(x) stats::rweibull(n = x, shape = 2.322737, scale = 6.492272),
 #'   k = 0,
 #'   quarantine = FALSE
 #' )

R/outbreak_model.R

@@ -24,10 +24,11 @@
 #' @param onset_to_isolation a `function`: a random number generating
 #'   `function` that accepts a single `integer` argument specifying the
 #'   length of the `function` output.
-#' @param incfn a `function`: a random number generating `function` that
-#'   samples from incubation period distribution, the `function` accepts a
-#'   single `integer` argument specifying the number of times to sample
-#'   the incubation period (i.e. length of the `function` output).
+#' @param incubation_period a `function`: a random number generating
+#'   `function` that samples from incubation period distribution, the
+#'   `function` accepts a single `integer` argument specifying the number of
+#'   times to sample the incubation period (i.e. length of the `function`
+#'   output).
 #' @param num.initial.cases a nonnegative `integer` scalar: number of initial
 #'   or starting cases which are all assumed to be missed.
 #' @param cap_cases a positive `integer` scalar: number of cumulative cases at
@@ -63,7 +64,7 @@
 #'   disp.subclin = 0.16,
 #'   k = 0,
 #'   onset_to_isolation = \(x) stats::rweibull(n = x, shape = 1.65, scale = 4.28),
-#'   incfn = \(x) stats::rweibull(n = x, shape = 2.32, scale = 6.49),
+#'   incubation_period = \(x) stats::rweibull(n = x, shape = 2.32, scale = 6.49),
 #'   prop.asym = 0,
 #'   quarantine = FALSE
 #' )
@@ -73,8 +74,8 @@ outbreak_model <- function(num.initial.cases = NULL, prop.ascertain = NULL,
                            r0isolated = NULL, r0community = NULL,
                            r0subclin = NULL, disp.iso = NULL,
                            disp.com = NULL, disp.subclin = NULL,
-                           k, onset_to_isolation, incfn, prop.asym = NULL,
-                           quarantine = NULL) {
+                           k, onset_to_isolation, incubation_period,
+                           prop.asym = NULL, quarantine = NULL) {
 
   # Set initial values for loop indices
   total.cases <- num.initial.cases
@@ -83,7 +84,7 @@ outbreak_model <- function(num.initial.cases = NULL, prop.ascertain = NULL,
 
   # Initial setup
   case_data <- outbreak_setup(num.initial.cases = num.initial.cases,
-                            incfn = incfn,
+                            incubation_period = incubation_period,
                             prop.asym = prop.asym,
                             onset_to_isolation = onset_to_isolation,
                             k = k)
@@ -103,7 +104,7 @@ outbreak_model <- function(num.initial.cases = NULL, prop.ascertain = NULL,
                              r0isolated = r0isolated,
                              r0community = r0community,
                              r0subclin = r0subclin,
-                             incfn = incfn,
+                             incubation_period = incubation_period,
                              onset_to_isolation = onset_to_isolation,
                              prop.ascertain = prop.ascertain,
                              k = k,

R/outbreak_setup.R

@@ -21,20 +21,20 @@
 #'
 #' @examples
 #' # incubation period sampling function
-#' incfn <- \(x) stats::rweibull(n = x, shape = 2.32, scale = 6.49)
+#' incubation_period <- \(x) stats::rweibull(n = x, shape = 2.32, scale = 6.49)
 #' # delay distribution sampling function
 #' onset_to_isolation <- \(x) stats::rweibull(n = x, shape = 1.65, scale = 4.28)
 #' out <- outbreak_setup(
 #'   num.initial.cases = 1,
-#'   incfn = incfn,
+#'   incubation_period = incubation_period,
 #'   onset_to_isolation = onset_to_isolation,
 #'   k = 1.95,
 #'   prop.asym = 0
 #' )
 #' out
-outbreak_setup <- function(num.initial.cases, incfn, onset_to_isolation, k, prop.asym) {
+outbreak_setup <- function(num.initial.cases, incubation_period, onset_to_isolation, k, prop.asym) {
   # Set up table of initial cases
-  inc_samples <- incfn(num.initial.cases)
+  inc_samples <- incubation_period(num.initial.cases)
 
   case_data <- data.table(exposure = rep(0, num.initial.cases), # Exposure time of 0 for all initial cases
                           asym = as.logical(rbinom(num.initial.cases, 1, prop.asym)),

R/outbreak_step.R

@@ -22,13 +22,13 @@
 #'
 #' @examples
 #' # incubation period sampling function
-#' incfn <- \(x) stats::rweibull(n = x, shape = 2.32, scale = 6.49)
+#' incubation_period <- \(x) stats::rweibull(n = x, shape = 2.32, scale = 6.49)
 #' # delay distribution sampling function
 #' onset_to_isolation <- \(x) stats::rweibull(n = x, shape = 1.65, scale = 4.28)
 #' # generate initial cases
 #' case_data <- outbreak_setup(
 #'   num.initial.cases = 5,
-#'   incfn = incfn,
+#'   incubation_period = incubation_period,
 #'   onset_to_isolation = onset_to_isolation,
 #'   k = 1.95,
 #'   prop.asym = 0
@@ -44,7 +44,7 @@
 #'   r0subclin = 1.25,
 #'   r0community = 2.5,
 #'   prop.asym = 0,
-#'   incfn = incfn,
+#'   incubation_period = incubation_period,
 #'   onset_to_isolation = onset_to_isolation,
 #'   prop.ascertain = 0,
 #'   k = 1.95,
@@ -54,7 +54,7 @@
 #' case_data
 outbreak_step <- function(case_data = NULL, disp.iso = NULL, disp.com = NULL,
                           r0isolated = NULL, r0community = NULL,
-                          prop.asym = NULL, incfn = NULL,
+                          prop.asym = NULL, incubation_period = NULL,
                           onset_to_isolation = NULL, prop.ascertain = NULL,
                           k = NULL, quarantine = NULL, r0subclin = NULL,
                           disp.subclin = NULL) {
@@ -90,7 +90,7 @@ outbreak_step <- function(case_data = NULL, disp.iso = NULL, disp.com = NULL,
   }
 
   # Compile a data.table for all new cases, new_cases is the amount of people that each infector has infected
-  inc_samples <- incfn(total_new_cases)
+  inc_samples <- incubation_period(total_new_cases)
 
   prob_samples <- data.table(
     # time when new cases were exposed, a draw from serial interval based on infector's onset

R/scenario_sim.R

@@ -36,15 +36,16 @@
 #'   disp.com = 0.16,
 #'   k = 0.7,
 #'   onset_to_isolation = \(x) stats::rweibull(n = x, shape = 2.5, scale = 5),
-#'   incfn = \(x) stats::rweibull(n = x, shape = 2.32, scale = 6.49),
+#'   incubation_period = \(x) stats::rweibull(n = x, shape = 2.32, scale = 6.49),
 #'   prop.asym = 0,
 #'   prop.ascertain = 0
 #' )
 #' res
 scenario_sim <- function(n.sim, prop.ascertain, cap_max_days, cap_cases,
                          r0isolated, r0community, disp.iso, disp.com, k,
-                         onset_to_isolation, incfn, num.initial.cases, prop.asym,
-                         quarantine, r0subclin = NULL, disp.subclin = NULL) {
+                         onset_to_isolation, incubation_period,
+                         num.initial.cases, prop.asym, quarantine,
+                         r0subclin = NULL, disp.subclin = NULL) {
 
   # Set infectiousness of subclinical cases to be equal to clinical cases unless specified otherwise
   if(is.null(r0subclin)) {
@@ -66,7 +67,7 @@ scenario_sim <- function(n.sim, prop.ascertain, cap_max_days, cap_cases,
                                              disp.iso = disp.iso,
                                              disp.com = disp.com,
                                              onset_to_isolation = onset_to_isolation,
-                                             incfn = incfn,
+                                             incubation_period = incubation_period,
                                              k = k,
                                              prop.asym = prop.asym,
                                              quarantine = quarantine))

README.Rmd

@@ -56,7 +56,7 @@ res <- scenario_sim(
   disp.com = 0.16, ## dispersion parameter in the community
   disp.iso = 1, ## dispersion  parameter of those isolated
   onset_to_isolation = \(x) stats::rweibull(n = x, shape = 1.651524, scale = 4.287786), ## time from onset to isolation
-  incfn = \(x) stats::rweibull(n = x, shape = 2.322737, scale = 6.492272),
+  incubation_period = \(x) stats::rweibull(n = x, shape = 2.322737, scale = 6.492272), ## incubation period
   k = 0, ## skew of generation interval to be beyond onset of symptoms
   quarantine = FALSE ## whether quarantine is in effect
 )