Replace contact interval with infectious period

R/checkers.R

@@ -115,7 +115,7 @@
 #' @keywords internal
 .check_sim_input <- function(sim_type = c("linelist", "contacts", "outbreak"),
                              contact_distribution,
-                             contact_interval,
+                             infect_period,
                              prob_infect,
                              outbreak_start_date,
                              outbreak_size,
@@ -133,7 +133,7 @@
 
   checkmate::assert_number(prob_infect, lower = 0, upper = 1)
   .check_func_req_args(contact_distribution)
-  .check_func_req_args(contact_interval)
+  .check_func_req_args(infect_period)
   checkmate::assert_date(outbreak_start_date)
   checkmate::assert_integerish(outbreak_size, lower = 1, len = 2)
 

R/sim_contacts.R

@@ -20,20 +20,20 @@
 #'   prob_distribution_params = c(mean = 2)
 #' )
 #'
-#' contact_interval <- epiparameter::epidist(
+#' infect_period <- epiparameter::epidist(
 #'   disease = "COVID-19",
-#'   epi_dist = "contact interval",
+#'   epi_dist = "infectious period",
 #'   prob_distribution = "gamma",
 #'   prob_distribution_params = c(shape = 1, scale = 1)
 #' )
 #'
 #' contacts <- sim_contacts(
 #'   contact_distribution = contact_distribution,
-#'   contact_interval = contact_interval,
+#'   infect_period = infect_period,
 #'   prob_infect = 0.5
 #' )
 sim_contacts <- function(contact_distribution,
-                         contact_interval,
+                         infect_period,
                          prob_infect,
                          outbreak_start_date = as.Date("2023-01-01"),
                          outbreak_size = c(10, 1e4),
@@ -47,17 +47,17 @@ sim_contacts <- function(contact_distribution,
   # check and convert distribution to func if needed before .check_sim_input()
   stopifnot(
     "Input delay distributions need to be either functions or <epidist>" =
-      inherits(contact_interval, c("function", "epidist"))
+      inherits(infect_period, c("function", "epidist"))
   )
   contact_distribution <- as.function(
     contact_distribution, func_type = "density"
   )
-  contact_interval <- as.function(contact_interval, func_type = "generate")
+  infect_period <- as.function(infect_period, func_type = "generate")
 
   .check_sim_input(
     sim_type = "contacts",
     contact_distribution = contact_distribution,
-    contact_interval = contact_interval,
+    infect_period = infect_period,
     prob_infect = prob_infect,
     outbreak_start_date = outbreak_start_date,
     outbreak_size = outbreak_size,
@@ -75,7 +75,7 @@ sim_contacts <- function(contact_distribution,
   contacts <- .sim_internal(
     sim_type = "contacts",
     contact_distribution = contact_distribution,
-    contact_interval = contact_interval,
+    infect_period = infect_period,
     prob_infect = prob_infect,
     outbreak_start_date = outbreak_start_date,
     outbreak_size = outbreak_size,

R/sim_internal.R

@@ -13,7 +13,7 @@
 #' @keywords internal
 .sim_internal <- function(sim_type = c("linelist", "contacts", "outbreak"),
                           contact_distribution,
-                          contact_interval,
+                          infect_period,
                           prob_infect,
                           onset_to_hosp = NULL,
                           onset_to_death = NULL,
@@ -36,7 +36,7 @@
   while (num_cases < min(outbreak_size)) {
     .data <- .sim_network_bp(
       contact_distribution = contact_distribution,
-      contact_interval = contact_interval,
+      infect_period = infect_period,
       prob_infect = prob_infect,
       max_outbreak_size = max(outbreak_size),
       config = config

R/sim_linelist.R

@@ -24,11 +24,13 @@
 #' the contact distribution. This is any discrete density function that
 #' produces non-negative integers (including zero, \eqn{\mathbb{N}_0}) for the
 #' number of contacts per infection.
-#' @param contact_interval An `<epidist>` object or anonymous function for
-#' the contact interval. This is analogous to the serial interval or generation
-#' time, but defines the time interval between an individual being
-#' infected/infectious (in the simulation the latency period is assumed to be
-#' zero) and having contact with another susceptible individual.
+#' @param infect_period An `<epidist>` object or anonymous function for
+#' the infectious period. This defines the duration from becoming infectious
+#' to no longer infectious. In the simulation, individuals are assumed to
+#' become infectious immediately after being infected (the latency period is
+#' assumed to be zero). The time intervals between an infected individual and
+#' their contacts are assumed to be uniformly distributed within the
+#' infectious period.
 #' @param prob_infect A single `numeric` for the probability of a secondary
 #' contact being infected by an infected primary contact.
 #' @param onset_to_hosp An `<epidist>` object or anonymous function for
@@ -93,9 +95,9 @@
 #'   prob_distribution_params = c(mean = 2)
 #' )
 #'
-#' contact_interval <- epiparameter::epidist(
+#' infect_period <- epiparameter::epidist(
 #'   disease = "COVID-19",
-#'   epi_dist = "contact interval",
+#'   epi_dist = "infectious period",
 #'   prob_distribution = "gamma",
 #'   prob_distribution_params = c(shape = 1, scale = 1)
 #' )
@@ -116,7 +118,7 @@
 #' # example with single hospitalisation risk for entire population
 #' linelist <- sim_linelist(
 #'   contact_distribution = contact_distribution,
-#'   contact_interval = contact_interval,
+#'   infect_period = infect_period,
 #'   prob_infect = 0.5,
 #'   onset_to_hosp = onset_to_hosp,
 #'   onset_to_death = onset_to_death,
@@ -134,15 +136,15 @@
 #' )
 #' linelist <- sim_linelist(
 #'   contact_distribution = contact_distribution,
-#'   contact_interval = contact_interval,
+#'   infect_period = infect_period,
 #'   prob_infect = 0.5,
 #'   onset_to_hosp = onset_to_hosp,
 #'   onset_to_death = onset_to_death,
 #'   hosp_risk = age_dep_hosp_risk
 #' )
 #' head(linelist)
 sim_linelist <- function(contact_distribution,
-                         contact_interval,
+                         infect_period,
                          prob_infect,
                          onset_to_hosp,
                          onset_to_death,
@@ -164,21 +166,21 @@ sim_linelist <- function(contact_distribution,
   stopifnot(
     "Input delay distributions need to be either functions or <epidist>" =
       inherits(contact_distribution, c("function", "epidist")) &&
-      inherits(contact_interval, c("function", "epidist")) &&
+      inherits(infect_period, c("function", "epidist")) &&
       inherits(onset_to_hosp, c("function", "epidist")) &&
       inherits(onset_to_death, c("function", "epidist"))
   )
   contact_distribution <- as.function(
     contact_distribution, func_type = "density"
   )
-  contact_interval <- as.function(contact_interval, func_type = "generate")
+  infect_period <- as.function(infect_period, func_type = "generate")
   onset_to_hosp <- as.function(onset_to_hosp, func_type = "generate")
   onset_to_death <- as.function(onset_to_death, func_type = "generate")
 
   .check_sim_input(
     sim_type = "linelist",
     contact_distribution = contact_distribution,
-    contact_interval = contact_interval,
+    infect_period = infect_period,
     prob_infect = prob_infect,
     outbreak_start_date = outbreak_start_date,
     outbreak_size = outbreak_size,
@@ -226,7 +228,7 @@ sim_linelist <- function(contact_distribution,
   linelist <- .sim_internal(
     sim_type = "linelist",
     contact_distribution = contact_distribution,
-    contact_interval = contact_interval,
+    infect_period = infect_period,
     prob_infect = prob_infect,
     onset_to_hosp = onset_to_hosp,
     onset_to_death = onset_to_death,

R/sim_network_bp.R

@@ -5,8 +5,9 @@
 #' Simulate a branching process on a infinite network where the contact
 #' distribution provides a function to sample the number of contacts of each
 #' individual in the simulation. Each contact is then infected with the
-#' probability of infection. The time between each infection is determined
-#' by the contact interval function.
+#' probability of infection. The time between each contact is assumed to be
+#' evenly distributed across the infectious period of the infected individual,
+#' and is independent of whether the contact becomes infected.
 #'
 #' @details
 #' The contact distribution sampled takes the network effect
@@ -22,7 +23,7 @@
 #' @return A `<data.frame>` with the contact and transmission chain data.
 #' @keywords internal
 .sim_network_bp <- function(contact_distribution,
-                            contact_interval,
+                            infect_period,
                             prob_infect,
                             max_outbreak_size,
                             config) {
@@ -92,9 +93,16 @@
           infect <- stats::rbinom(n = contacts[i], size = 1, prob = prob_infect)
           infected[vec_idx] <- as.numeric(infect)
 
-          # add delay time
-          time[vec_idx] <- contact_interval(length(vec_idx)) +
-            time[ancestor_idx[i]]
+          # compute infectious period for ancestor
+          contact_infect_period <- infect_period(1)
+
+          # assume contacts are evenly distributed across the infectious period
+          contact_times <- stats::runif(
+            n = length(vec_idx),
+            min = 0,
+            max = contact_infect_period
+          )
+          time[vec_idx] <- contact_times + time[ancestor_idx[i]]
         }
       }
       ancestor_idx <- setdiff(which(infected == 1), prev_ancestors)

R/sim_outbreak.R

@@ -25,9 +25,9 @@
 #'   prob_distribution_params = c(mean = 2)
 #' )
 #'
-#' contact_interval <- epiparameter::epidist(
+#' infect_period <- epiparameter::epidist(
 #'   disease = "COVID-19",
-#'   epi_dist = "serial interval",
+#'   epi_dist = "infectious period",
 #'   prob_distribution = "gamma",
 #'   prob_distribution_params = c(shape = 1, scale = 1)
 #' )
@@ -48,13 +48,13 @@
 #'
 #' outbreak <- sim_outbreak(
 #'   contact_distribution = contact_distribution,
-#'   contact_interval = contact_interval,
+#'   infect_period = infect_period,
 #'   prob_infect = 0.5,
 #'   onset_to_hosp = onset_to_hosp,
 #'   onset_to_death = onset_to_death
 #' )
 sim_outbreak <- function(contact_distribution,
-                         contact_interval,
+                         infect_period,
                          prob_infect,
                          onset_to_hosp,
                          onset_to_death,
@@ -81,21 +81,21 @@ sim_outbreak <- function(contact_distribution,
   stopifnot(
     "Input delay distributions need to be either functions or <epidist>" =
       inherits(contact_distribution, c("function", "epidist")) &&
-      inherits(contact_interval, c("function", "epidist")) &&
+      inherits(infect_period, c("function", "epidist")) &&
       inherits(onset_to_hosp, c("function", "epidist")) &&
       inherits(onset_to_death, c("function", "epidist"))
   )
   contact_distribution <- as.function(
     contact_distribution, func_type = "density"
   )
-  contact_interval <- as.function(contact_interval, func_type = "generate")
+  infect_period <- as.function(infect_period, func_type = "generate")
   onset_to_hosp <- as.function(onset_to_hosp, func_type = "generate")
   onset_to_death <- as.function(onset_to_death, func_type = "generate")
 
   .check_sim_input(
     sim_type = "outbreak",
     contact_distribution = contact_distribution,
-    contact_interval = contact_interval,
+    infect_period = infect_period,
     prob_infect = prob_infect,
     outbreak_start_date = outbreak_start_date,
     outbreak_size = outbreak_size,
@@ -144,7 +144,7 @@ sim_outbreak <- function(contact_distribution,
   outbreak <- .sim_internal(
     sim_type = "outbreak",
     contact_distribution = contact_distribution,
-    contact_interval = contact_interval,
+    infect_period = infect_period,
     prob_infect = prob_infect,
     onset_to_hosp = onset_to_hosp,
     onset_to_death = onset_to_death,

README.Rmd

@@ -50,7 +50,7 @@ library(simulist)
 library(epiparameter)
 ```
 
-The line list simulation requires that we define a contact distribution, contact interval, onset-to-hospitalisation delay, and onset-to-death delay. We can load these from the library of epidemiological parameters in the `{epiparameter}` R package if available, or if these are not in the database yet (such as the contact interval for COVID-19) we can define them ourselves.
+The line list simulation requires that we define a contact distribution, period of infectiousness, onset-to-hospitalisation delay, and onset-to-death delay. We can load these from the library of epidemiological parameters in the `{epiparameter}` R package if available, or if these are not in the database yet (such as the contact distribution for COVID-19) we can define them ourselves.
 
 ```{r create-epidists}
 # create COVID-19 contact distribution
@@ -61,10 +61,10 @@ contact_distribution <- epiparameter::epidist(
   prob_distribution_params = c(mean = 2)
 )
 
-# create COVID-19 contact interval
-contact_interval <- epiparameter::epidist(
+# create COVID-19 infectious period
+infect_period <- epiparameter::epidist(
   disease = "COVID-19",
-  epi_dist = "contact interval",
+  epi_dist = "infectious period",
   prob_distribution = "gamma",
   prob_distribution_params = c(shape = 1, scale = 1)
 )
@@ -92,7 +92,7 @@ To simulate a line list for COVID-19 with an Poisson contact distribution with a
 set.seed(1)
 linelist <- sim_linelist(
   contact_distribution = contact_distribution,
-  contact_interval = contact_interval,
+  infect_period = infect_period,
   prob_infect = 0.5,
   onset_to_hosp = onset_to_hosp,
   onset_to_death = onset_to_death
@@ -105,7 +105,7 @@ In this example, the line list is simulated using the default values (see `?sim_
 ```{r sim-linelist-diff-args}
 linelist <- sim_linelist(
   contact_distribution = contact_distribution,
-  contact_interval = contact_interval,
+  infect_period = infect_period,
   prob_infect = 0.5,
   onset_to_hosp = onset_to_hosp,
   onset_to_death = onset_to_death,
@@ -120,7 +120,7 @@ To simulate a table of contacts of cases (i.e. to reflect a contact tracing data
 ```{r, sim-contacts}
 contacts <- sim_contacts(
   contact_distribution = contact_distribution,
-  contact_interval = contact_interval, 
+  infect_period = infect_period, 
   prob_infect = 0.5
 )
 head(contacts)
@@ -131,7 +131,7 @@ If both the line list and contacts table are required, they can be jointly simul
 ```{r, sim-outbreak}
 outbreak <- sim_outbreak(
   contact_distribution = contact_distribution,
-  contact_interval = contact_interval,
+  infect_period = infect_period,
   prob_infect = 0.5,
   onset_to_hosp = onset_to_hosp,
   onset_to_death = onset_to_death