diff --git a/DESCRIPTION b/DESCRIPTION
index 06e83453..8e817594 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -42,7 +42,6 @@ Suggests:
     knitr,
     markdown,
     testthat (>= 3.0.0),
-    MASS,
     ciTools
 VignetteBuilder: knitr
 Config/testthat/edition: 3
diff --git a/vignettes/incidence2.Rmd b/vignettes/incidence2.Rmd
index 2e96e234..1c5b8ed7 100644
--- a/vignettes/incidence2.Rmd
+++ b/vignettes/incidence2.Rmd
@@ -9,7 +9,7 @@ vignette: >
   %\VignetteIndexEntry{An introduction to incidence2}
   %\VignetteEngine{knitr::knitr}
   %\VignetteEncoding{UTF-8}
-  %\VignetteDepends{outbreaks, ggplot2, MASS, ciTools, tidyr}
+  %\VignetteDepends{outbreaks, ggplot2, ciTools, tidyr}
 ---
 
 ```{r, include = FALSE}
@@ -545,18 +545,23 @@ When called on incidence2 objects, these methods will utilise the
 underlying grouping structure without the user needing to explicitly state
 what it is. This makes it very easy to utilise in analysis pipelines.
 
-#### Example fitting a negative binomial model
+#### Example fitting a poisson model
 
 ```{r}
 # first twenty weeks of the ebola data set across hospitals
 dat <- incidence_(ebola, date_of_onset, groups = hospital, interval = "isoweek")
 dat <- keep_first(dat, 20L)
 
-# fit a negative binomial to the grouped data
+# fit a poisson model to the grouped data
 (fitted <-
     dat |>
     nest(.key = "data") |>
-    mutate(model  = lapply(data, \(x) MASS::glm.nb(count ~ date_index, x))))
+    mutate(
+        model  = lapply(
+            data,
+            function(x) glm(count ~ date_index, data = x, family = poisson)
+        )
+    ))
 # Add confidence intervals to the result
 (intervals <-
     fitted |>