Fix Get started vignette

vignettes/cfr.Rmd

@@ -16,7 +16,9 @@ vignette: >
 
 It is important to understand the severity of a disease in terms of the case fatality rate in order to respond appropriately to an outbreak.
 During an outbreak there is often a delay between cases being reported, and the outcomes of those cases being known.
+
 Knowing the distribution of these delays from previous outbreaks of the same (or similar) diseases, and accounting for them, can be useful in getting better estimates of disease severity.
+
 The severity of a disease can be estimated while correcting for delays in reporting using methods outlines in @nishiura2009, and which are implemented in the _cfr_ package.
 
 ::: {.alert .alert-primary}
@@ -66,6 +68,9 @@ Here, we use some data from the first Ebola outbreak, in the Democratic Republic
 
 ```{r}
 data("ebola1976")
+
+# view ebola dataset
+head(ebola1976)
 ```
 
 ## Obtaining data on reporting delays
@@ -105,9 +110,12 @@ estimate_static(
 
 The `estimate_static()` function is well suited to small outbreaks. For larger outbreaks where it may be useful to know how severity has changed over time, the function `estimate_time_varying()` is available. This function is however not well suited to small outbreaks. More on this can be found on the [vignette on estimating how disease severity varies over the course of an outbreak](estimate_time_varying_severity.html).
 
-## Estimate reporting rate
+## Estimate ascertainment rate
+
+It is important to know what proportion of cases in an outbreak are being ascertained to muster the appropriate response, and to estimate the overall burden of the outbreak.
 
-It is important to know what proportion of cases in an outbreak are being reported to muster the appropriate response, and to estimate the overall burden of the outbreak.
+**Note** that the ascertainment rate may be affected by a number of factors.
+When the main factor in low ascertainment is the lack of (access to) testing capacity, we refer to this as reporting or under-reporting.
 
 The `estimate_reporting()` function can help estimate this using the daily case and death data, the known severity of the disease from previous outbreaks, as well as a delay distribution of onset-to-death.