diff --git a/R/create.R b/R/create.R
index bf54f3612..c8c299503 100644
--- a/R/create.R
+++ b/R/create.R
@@ -685,10 +685,12 @@ create_stan_args <- function(stan = stan_opts(),
 ##' Create delay variables for stan
 ##'
 ##' @param ... Named delay distributions. The names are assigned to IDs
-##' @param weight Numeric, weight associated with delay priors; default: 1
+##' @param time_points Integer, the number of time points in the data;
+##'   determines weight associated with weighted delay priors; default: 1
 ##' @return A list of variables as expected by the stan model
 ##' @importFrom purrr transpose map flatten
-create_stan_delays <- function(..., weight = 1) {
+create_stan_delays <- function(..., time_points = 1L) {
+  delays <- list(...)
   ## discretise
   delays <- map(list(...), discretise)
   ## convolve where appropriate
@@ -706,23 +708,23 @@ create_stan_delays <- function(..., weight = 1) {
   ids[type_n > 0] <- seq_len(sum(type_n > 0))
   names(ids) <- paste(names(type_n), "id", sep = "_")
 
-  delays <- flatten(delays)
-  parametric <- unname(
-    vapply(delays, function(x) x$distribution != "nonparametric", logical(1))
-  )
-  param_length <- unname(vapply(delays[parametric], function(x) {
+  flat_delays <- flatten(delays)
+  parametric <- unname(vapply(
+    flat_delays, function(x) x$distribution != "nonparametric", logical(1)
+  ))
+  param_length <- unname(vapply(flat_delays[parametric], function(x) {
     length(x$parameters)
   }, numeric(1)))
-  nonparam_length <- unname(vapply(delays[!parametric], function(x) {
+  nonparam_length <- unname(vapply(flat_delays[!parametric], function(x) {
     length(x$pmf)
   }, numeric(1)))
   distributions <- unname(as.character(
-    map(delays[parametric], ~ .x$distribution)
+    map(flat_delays[parametric], ~ .x$distribution)
   ))
 
   ## create stan object
   ret <- list(
-    n = length(delays),
+    n = length(flat_delays),
     n_p = sum(parametric),
     n_np = sum(!parametric),
     types = sum(type_n > 0),
@@ -738,15 +740,15 @@ create_stan_delays <- function(..., weight = 1) {
   ret$types_groups <- array(c(0, cumsum(unname(type_n[type_n > 0]))) + 1)
 
   ret$params_mean <- array(unname(as.numeric(
-    map(flatten(map(delays[parametric], ~ .x$parameters)), mean)
+    map(flatten(map(flat_delays[parametric], ~ .x$parameters)), mean)
   )))
   ret$params_sd <- array(unname(as.numeric(
-    map(flatten(map(delays[parametric], ~ .x$parameters)), sd_dist)
+    map(flatten(map(flat_delays[parametric], ~ .x$parameters)), sd_dist)
   )))
   ret$max <- array(max_delay[parametric])
 
   ret$np_pmf <- array(unname(as.numeric(
-    flatten(map(delays[!parametric], ~ .x$pmf))
+    flatten(map(flat_delays[!parametric], ~ .x$pmf))
   )))
   ## get non zero length delay pmf lengths
   ret$np_pmf_groups <- array(c(0, cumsum(nonparam_length)) + 1)
@@ -758,12 +760,16 @@ create_stan_delays <- function(..., weight = 1) {
   ret$params_length <- sum(param_length)
   ## set lower bounds
   ret$params_lower <- array(unname(as.numeric(flatten(
-    map(delays[parametric], function(x) {
+    map(flat_delays[parametric], function(x) {
       lower_bounds(x$distribution)[names(x$parameters)]
     })
   ))))
   ## assign prior weights
-  ret$weight <- array(rep(weight, ret$n_p))
+  weigh_priors <- vapply(
+    delays[parametric], attr, "weigh_prior", FUN.VALUE = logical(1)
+  )
+  ret$weight <- array(rep(1, ret$n_p))
+  ret$weight[weigh_priors] <- time_points
   ## assign distribution
   ret$dist <- array(match(distributions, c("lognormal", "gamma")) - 1L)
 
diff --git a/R/dist_spec.R b/R/dist_spec.R
index a1d1645b8..45526e0b5 100644
--- a/R/dist_spec.R
+++ b/R/dist_spec.R
@@ -472,7 +472,8 @@ discretise <- function(x, silent = TRUE) {
       }
     }
   })
-  attr(ret, "class") <- c("dist_spec", "list")
+  ## preserve attributes
+  attributes(ret) <- attributes(x)
   return(ret)
 }
 #' @rdname discretise
@@ -543,7 +544,7 @@ apply_tolerance <- function(x, tolerance) {
   if (!is(x, "dist_spec")) {
     stop("Can only apply tolerance to distributions in a <dist_spec>.")
   }
-  x <- lapply(x, function(x) {
+  y <- lapply(x, function(x) {
     if (x$distribution == "nonparametric") {
       cmf <- cumsum(x$pmf)
       new_pmf <- x$pmf[c(TRUE, (1 - cmf[-length(cmf)]) >= tolerance)]
@@ -554,8 +555,9 @@ apply_tolerance <- function(x, tolerance) {
     }
   })
 
-  attr(x, "class") <- c("dist_spec", "list")
-  return(x)
+  ## preserve attributes
+  attributes(y) <- attributes(x)
+  return(y)
 }
 
 #' Prints the parameters of one or more delay distributions
diff --git a/R/estimate_infections.R b/R/estimate_infections.R
index b69390ed9..44345c9ca 100644
--- a/R/estimate_infections.R
+++ b/R/estimate_infections.R
@@ -203,9 +203,7 @@ estimate_infections <- function(reported_cases,
     gt = generation_time,
     delay = delays,
     trunc = truncation,
-    weight = ifelse(
-      weigh_delay_priors, data$t - data$seeding_time - data$horizon, 1
-    )
+    time_points = data$t - data$seeding_time - data$horizon
   ))
 
   # Set up default settings
diff --git a/R/estimate_secondary.R b/R/estimate_secondary.R
index 7c02611d9..6eb9658cc 100644
--- a/R/estimate_secondary.R
+++ b/R/estimate_secondary.R
@@ -140,7 +140,7 @@ estimate_secondary <- function(reports,
                                    meanlog = Normal(2.5, 0.5),
                                    sdlog = Normal(0.47, 0.25),
                                    max = 30
-                                 )
+                                 ), weigh_prior = FALSE
                                ),
                                truncation = trunc_opts(),
                                obs = obs_opts(),
@@ -198,7 +198,7 @@ estimate_secondary <- function(reports,
   data <- c(data, create_stan_delays(
     delay = delays,
     trunc = truncation,
-    weight = ifelse(weigh_delay_priors, data$t, 1)
+    time_points = data$t
   ))
 
   # observation model data
diff --git a/R/estimate_truncation.R b/R/estimate_truncation.R
index f42422620..7aedb5d58 100644
--- a/R/estimate_truncation.R
+++ b/R/estimate_truncation.R
@@ -47,12 +47,8 @@
 #' @param model A compiled stan model to override the default model. May be
 #' useful for package developers or those developing extensions.
 #'
-#' @param weigh_delay_priors Logical. If TRUE, all delay distribution priors
-#' will be weighted by the number of observation data points, in doing so
-#' approximately placing an independent prior at each time step and usually
-#' preventing the posteriors from shifting. If FALSE (default), no weight will
-#' be applied, i.e. delay distributions will be treated as a single
-#' parameters.
+#' @param weigh_delay_priors Deprecated; use the `weigh_priors` option in
+#'   [trunc_opts()] instead.
 #'
 #' @param verbose Logical, should model fitting progress be returned.
 #'
@@ -121,7 +117,15 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10,
       "estimate_truncation(stan)"
     )
   }
-  # Validate inputs
+  if (!missing(weigh_delay_priors)) {
+    lifecycle::deprecate_warn(
+      "1.5.0",
+      "estimate_truncation(weigh_delay_priors)",
+      "trunc_opts(weigh_prior)",
+      detail = "This argument will be removed completely in version 2.0.0"
+    )
+  }
+   # Validate inputs
   walk(obs, check_reports_valid, model = "estimate_truncation")
   assert_class(truncation, "dist_spec")
   assert_class(model, "stanfit", null.ok = TRUE)
@@ -216,7 +220,7 @@ estimate_truncation <- function(obs, max_truncation, trunc_max = 10,
 
   data <- c(data, create_stan_delays(
     trunc = truncation,
-    weight = ifelse(weigh_delay_priors, data$t, 1)
+    time_points = data$t
   ))
 
   # initial conditions
diff --git a/R/opts.R b/R/opts.R
index 4d0aaae1b..f340e70ae 100644
--- a/R/opts.R
+++ b/R/opts.R
@@ -12,8 +12,13 @@
 #' @param max deprecated; use `dist` instead
 #' @param fixed deprecated; use `dist` instead
 #' @param prior_weight deprecated; prior weights are now specified as a
-#' model option. Use the `weigh_delay_priors` argument of
-#' [estimate_infections()] instead.
+#' model option. Use the `weigh_prior` argument instead
+#' @param weigh_prior Logical; if TRUE (default), the generation time prior
+#'   will be weighted by the number of observation data points, in doing so
+#'   approximately placing an independent prior at each time step and usually
+#'   preventing the posteriors from shifting. If FALSE , no weight will be
+#'   applied, i.e. the generation time distribution will be treated as a single
+#'   parameter.
 #' @inheritParams apply_tolerance
 #' @return A `<generation_time_opts>` object summarising the input delay
 #' distributions.
@@ -40,7 +45,8 @@
 #' generation_time_opts(example_generation_time)
 generation_time_opts <- function(dist = Fixed(1), ...,
                                  disease, source, max = 14, fixed = FALSE,
-                                 prior_weight, tolerance = 0.001) {
+                                 prior_weight, tolerance = 0.001,
+                                 weigh_prior = TRUE) {
   deprecated_options_given <- FALSE
   dot_options <- list(...)
 
@@ -82,7 +88,7 @@ generation_time_opts <- function(dist = Fixed(1), ...,
   if (!missing(prior_weight)) {
     deprecate_warn(
       "1.4.0", "generation_time_opts(prior_weight)",
-      "estimate_infections(weigh_delay_prior)",
+      "generation_time_opts(weigh_prior)",
       "This argument will be removed in version 2.0.0."
     )
   }
@@ -107,6 +113,7 @@ generation_time_opts <- function(dist = Fixed(1), ...,
   }
   check_stan_delay(dist)
   attr(dist, "tolerance") <- tolerance
+  attr(dist, "weigh_prior") <- weigh_prior
   attr(dist, "class") <- c("generation_time_opts", class(dist))
   return(dist)
 }
@@ -189,6 +196,7 @@ secondary_opts <- function(type = c("incidence", "prevalence"), ...) {
 #' @param ... deprecated; use `dist` instead
 #' @param fixed deprecated; use `dist` instead
 #' @inheritParams apply_tolerance
+#' @inheritParams generation_time_opts
 #' @return A `<delay_opts>` object summarising the input delay distributions.
 #' @seealso [convert_to_logmean()] [convert_to_logsd()]
 #' [bootstrapped_dist_fit()] [dist_spec()]
@@ -207,7 +215,8 @@ secondary_opts <- function(type = c("incidence", "prevalence"), ...) {
 #'
 #' # Multiple delays (in this case twice the same)
 #' delay_opts(delay + delay)
-delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE, tolerance = 0.001) {
+delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE, tolerance = 0.001,
+                       weigh_prior = TRUE) {
   dot_options <- list(...)
   if (!is(dist, "dist_spec")) { ## could be old syntax
     if (is.list(dist)) {
@@ -240,6 +249,7 @@ delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE, tolerance = 0.001) {
   }
   check_stan_delay(dist)
   attr(dist, "tolerance") <- tolerance
+  attr(dist, "weigh_prior") <- weigh_prior
   attr(dist, "class") <- c("delay_opts", class(dist))
   return(dist)
 }
@@ -254,6 +264,12 @@ delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE, tolerance = 0.001) {
 #' @param dist A delay distribution or series of delay distributions reflecting
 #' the truncation generated using [dist_spec()] or [estimate_truncation()].
 #' Default is fixed distribution with maximum 0, i.e. no truncation
+#' @param weigh_prior Logical; if TRUE, the truncation prior will be weighted
+#'   by the number of observation data points, in doing so approximately placing
+#'   an independent prior at each time step and usually preventing the
+#'   posteriors from shifting. If FALSE (default), no weight will be applied,
+#'   i.e. the truncation distribution will be treated as a single parameter.
+#'
 #' @inheritParams apply_tolerance
 #' @return A `<trunc_opts>` object summarising the input truncation
 #' distribution.
@@ -267,7 +283,8 @@ delay_opts <- function(dist = Fixed(0), ..., fixed = FALSE, tolerance = 0.001) {
 #'
 #' # truncation dist
 #' trunc_opts(dist = LogNormal(mean = 3, sd = 2, max = 10))
-trunc_opts <- function(dist = Fixed(0), tolerance = 0.001) {
+trunc_opts <- function(dist = Fixed(0), tolerance = 0.001,
+                       weigh_prior = FALSE) {
   if (!is(dist, "dist_spec")) {
     if (is.list(dist)) {
       dist <- do.call(dist_spec, dist)
@@ -285,6 +302,7 @@ trunc_opts <- function(dist = Fixed(0), tolerance = 0.001) {
   }
   check_stan_delay(dist)
   attr(dist, "tolerance") <- tolerance
+  attr(dist, "weigh_prior") <- weigh_prior
   attr(dist, "class") <- c("trunc_opts", class(dist))
   return(dist)
 }
diff --git a/tests/testthat/test-delays.R b/tests/testthat/test-delays.R
index 6cb415724..639d584ff 100644
--- a/tests/testthat/test-delays.R
+++ b/tests/testthat/test-delays.R
@@ -6,7 +6,7 @@ test_stan_delays <- function(generation_time = generation_time_opts(Fixed(1)),
     generation_time = generation_time,
     delays = delays,
     truncation = truncation,
-    weight = 10
+    time_points = 10
   )
   return(unlist(unname(data[params])))
 }
diff --git a/tests/testthat/test-epinow.R b/tests/testthat/test-epinow.R
index 83dd87c69..f9b146259 100644
--- a/tests/testthat/test-epinow.R
+++ b/tests/testthat/test-epinow.R
@@ -84,7 +84,9 @@ test_that("epinow runs without error when saving to disk", {
 test_that("epinow can produce partial output as specified", {
   out <- suppressWarnings(epinow(
     reported_cases = reported_cases,
-    generation_time = generation_time_opts(example_generation_time),
+    generation_time = generation_time_opts(
+      example_generation_time, weigh_prior = FALSE
+    ),
     delays = delay_opts(example_incubation_period + reporting_delay),
     stan = stan_opts(
       samples = 25, warmup = 25,