Cleaning up vignettes for initial release

.gitignore

@@ -8,3 +8,4 @@ inst/doc
 /doc/
 /Meta/
 scratch.R
+pkgdown/favicon/

DESCRIPTION

@@ -54,7 +54,7 @@ Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.2.3
 Imports:
     checkmate,
-    stats,
+    stats
 Suggests: 
     dplyr,
     tidyr,
@@ -63,8 +63,8 @@ Suggests:
     forcats,
     ggplot2,
     pak,
+    owidR,
     testthat (>= 3.0.0),
-    covidregionaldata,
     usethis,
     knitr,
     bookdown,
@@ -74,8 +74,7 @@ Suggests:
     incidence2,
     outbreaks
 Remotes:
-    epiverse-trace/epiparameter,
-    epiforecasts/covidregionaldata
+    epiverse-trace/epiparameter
 Config/testthat/edition: 3
 Config/Needs/website:
     epiverse-trace/epiversetheme

_pkgdown.yml

@@ -1,3 +1,14 @@
 url: https://epiverse-trace.github.io/cfr/
 template:
   package: epiversetheme
+articles:
+- title: Package vignettes
+  navbar: Package vignettes
+  contents:
+  - estimate_static_severity
+  - estimate_time_varying_severity
+  - estimate_ascertainment
+- title: Handling data from other packages
+  navbar: Handling data from other packages
+  contents:
+  - data_from_incidence2

inst/WORDLIST

@@ -18,7 +18,6 @@ Poisson
 Tidyverse
 WIP
 binom
-codeblock
 codecov
 com
 covidregionaldata
@@ -42,6 +41,7 @@ linelists
 lockdown
 md
 org
+owidR
 packagename
 parameterised
 pkg

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}
@@ -50,7 +52,7 @@ library(cfr)
 
 ## Case and death data
 
-Data on cases and deaths may be obtained from a number of publicly accessible sources, such as the [_covidregionaldata_ package for data on the Covid-19 outbreak](https://epiforecasts.io/covidregionaldata/).
+Data on cases and deaths may be obtained from a number of publicly accessible sources, such as the [global Covid-19 dataset collected by Our World in Data](https://ourworldindata.org/coronavirus), and provided through the [_owidR_ package](https://cran.r-project.org/package=owidR).
 
 In an outbreak response scenario, such data may also be compiled and shared locally.
 
@@ -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.
 

vignettes/data_from_incidence2.Rmd

@@ -113,7 +113,7 @@ estimate_static(
 
 ## `<incidence2>` objects from aggregated case data
 
-Aggregated case data such as that provided by the package [_covidregionaldata_](https://epiforecasts.io/covidregionaldata/) can be used with _cfr_ directly.
+Aggregated case data such as the Covid-19 dataset provided by _incidence2_ can be used with _cfr_ directly.
 
 Such usage is shown in other vignettes such as the [vignette on estimating time-varying severity](estimate_time_varying_severity.html).