From 819b5dd3c3716a8c45192b02e4a99a1cefaacd28 Mon Sep 17 00:00:00 2001 From: Andree Valle Campos Date: Thu, 28 Mar 2024 19:31:32 +0000 Subject: [PATCH] add detail to challenges --- episodes/delays-reuse.Rmd | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/episodes/delays-reuse.Rmd b/episodes/delays-reuse.Rmd index 56833b1e..6e88a630 100644 --- a/episodes/delays-reuse.Rmd +++ b/episodes/delays-reuse.Rmd @@ -289,7 +289,7 @@ distribution[[4]]$metadata$inference_method Take 2 minutes to explore the `{epiparameter}` library. -Search for delay distributions of your disease of interest (e.g., Influenza) and a specific delay distribution (e.g., the incubation period). +**Choose** a disease of interest (e.g., Influenza, Measles, etc.) and a delay distribution (e.g., the incubation period, onset to death, etc.). Find: @@ -408,7 +408,7 @@ Now, we have an epidemiological parameter we can reuse! We can replace the **sum Let's assign this `` class object to the `covid_serialint` object. -```{r} +```{r,message=FALSE} covid_serialint <- epiparameter::epidist_db( disease = "covid", @@ -592,7 +592,7 @@ For Ebola: An informative delay should measure the time from symptom onset to recovery or death. -Find a way to access the whole `{epiparameter}` database and find how that delay may be stored. +Find a way to access the whole `{epiparameter}` database and find how that delay may be stored. The `list_distributions()` output is a dataframe. ::::::::::::::::::::::