Fix example dataset polymod_uk (#112)

* Transpose contact data before demography scaling

* Use pre-transposed contact matrix

* Fix polymod_uk use in examples

* Correct R0 in text

* Automatic readme update

Co-authored-by: GitHub Action <[email protected]>

R/final_size.R

@@ -56,7 +56,7 @@
 #' # load example POLYMOD data included in the package
 #' data(polymod_uk)
 #' r0 <- 2.0
-#' contact_matrix <- t(polymod_uk$contact_matrix)
+#' contact_matrix <- polymod_uk$contact_matrix
 #' demography_vector <- polymod_uk$demography_vector
 #'
 #' # define the number of age and susceptibility groups

README.Rmd

@@ -48,8 +48,8 @@ devtools::install_github("epiverse-trace/finalsize")
 
 _finalsize_ provides the single function `final_size()`, to calculate the final size of an epidemic.
 
-Here, an example using social contact data from the _socialmixr_ package investigates the final size of an epidemic when the disease has an R<sub>0</sub> of 2.0, and given three age groups of interest --- 0-19, 20-39 and 40+.
-The under-20 age group is assumed to be fully susceptible to the disease, whereas individuals aged over 20 are only half as susceptible.
+Here, an example using social contact data from the _socialmixr_ package investigates the final size of an epidemic when the disease has an R<sub>0</sub> of 1.5, and given three age groups of interest --- 0-19, 20-39 and 40+.
+The under-20 age group is assumed to be fully susceptible to the disease, whereas individuals aged over 20 are only half as susceptible as those under 20.
 
 ```{r}
 # load finalsize
@@ -59,7 +59,7 @@ library(finalsize)
 data(polymod_uk)
 
 # Define contact matrix (entry {ij} is contacts in group i reported by group j)
-contact_matrix <- t(polymod_uk$contact_matrix)
+contact_matrix <- polymod_uk$contact_matrix
 
 # Define population in each age group
 demography_vector <- polymod_uk$demography_vector

README.md

@@ -56,10 +56,10 @@ the final size of an epidemic.
 
 Here, an example using social contact data from the *socialmixr* package
 investigates the final size of an epidemic when the disease has an
-R<sub>0</sub> of 2.0, and given three age groups of interest — 0-19,
+R<sub>0</sub> of 1.5, and given three age groups of interest — 0-19,
 20-39 and 40+. The under-20 age group is assumed to be fully susceptible
 to the disease, whereas individuals aged over 20 are only half as
-susceptible.
+susceptible as those under 20.
 
 ``` r
 # load finalsize
@@ -69,7 +69,7 @@ library(finalsize)
 data(polymod_uk)
 
 # Define contact matrix (entry {ij} is contacts in group i reported by group j)
-contact_matrix <- t(polymod_uk$contact_matrix)
+contact_matrix <- polymod_uk$contact_matrix
 
 # Define population in each age group
 demography_vector <- polymod_uk$demography_vector
@@ -100,9 +100,9 @@ final_size(
   susceptibility
 )
 #>   demo_grp   susc_grp susceptibility p_infected
-#> 1   [0,20) susc_grp_1            1.0  0.3207405
-#> 2  [20,40) susc_grp_1            0.5  0.1127051
-#> 3      40+ susc_grp_1            0.5  0.1270013
+#> 1   [0,20) susc_grp_1            1.0 0.32849966
+#> 2  [20,40) susc_grp_1            0.5 0.10532481
+#> 3      40+ susc_grp_1            0.5 0.06995193
 ```
 
 ## Package vignettes

data-raw/polymod_uk.R

@@ -10,7 +10,7 @@ polymod_uk <- socialmixr::contact_matrix(
 )
 
 # get contact matrix and demography vector
-contact_matrix <- polymod_uk$matrix
+contact_matrix <- t(polymod_uk$matrix)
 demography_vector <- polymod_uk$demography$population
 
 # scale contacts by maximum real eigenvalue and divide by demography