updated WORDLIST and spelling

inst/WORDLIST

@@ -36,6 +36,7 @@ Getz
 ggplot
 Hanne
 Heleze
+hline
 infectees
 infector
 infectors
@@ -55,6 +56,8 @@ Magassouba
 md
 MERS
 Meuwissen
+mpox
+Natsal
 N’Faly
 Niel
 num
@@ -67,20 +70,26 @@ pkgdown
 pointrange
 poisson
 prob
+res
 rightarrow
 rmarkdown
+SAR
 SARS
 Schreiber
 Selina
 Sien
 Soropogui
 testthat
 Torneri
+var
+vars
 Verdonschot
 viridis
 vline
 Wellcome
 wellcomeopenres
 xintercept
+yintercept
 ymax
 ymin
+zika

vignettes/heterogeneous_network_outbreaks.Rmd

@@ -41,7 +41,7 @@ $$
 
 where $V$ is the variance of the number of contacts per year. This formulation can be used if a disease is sexually transmitted and suspected to cause a substantial outbreak ($R > 1$). 
 
-The {superspreading} package provides teh `calc_network_R()` function to calculate the reproduction number using the unadjusted formula (first equation) and the adjusted formula (second equation).
+The {superspreading} package provides the `calc_network_R()` function to calculate the reproduction number using the unadjusted formula (first equation) and the adjusted formula (second equation).
 
 The possibility of a sexually transmitted outbreak Zika virus arose around 2015. @yakobLowRiskSexuallytransmitted2016 used the above simple heterogeneous network model to determine the risk of an outbreak if sexual transmission was a viable and common mode of transmission for Zika virus.
 
@@ -113,11 +113,11 @@ Another study that showed the network effects on transmission of an STI was @end
 beta <- seq(0.001, 1, length.out = 1000)
 duration_years <- 21 / 365
 res <- lapply(
-  beta, 
-  calc_network_R,  
-  mean_num_contact = 10, 
-  sd_num_contact = 50, 
-  infect_duration = duration_years, 
+  beta,
+  calc_network_R,
+  mean_num_contact = 10,
+  sd_num_contact = 50,
+  infect_duration = duration_years,
   age_range = c(18, 44)
 )
 res <- do.call(rbind, res)
@@ -137,15 +137,15 @@ ggplot(data = res) +
   geom_line(mapping = aes(x = beta, y = R, colour = group)) +
   geom_hline(mapping = aes(yintercept = 1)) +
   scale_y_continuous(
-    name = "Reproduction Number (R)", 
-    trans = "log", 
-    breaks = breaks_log(), 
+    name = "Reproduction Number (R)",
+    trans = "log",
+    breaks = breaks_log(),
     labels = label_comma()
   ) +
   scale_x_continuous(name = "Secondary Attack Rate (SAR)") +
   scale_colour_brewer(
-    name = "Repoduction Number", 
-    labels = c("R", "Adjusted R"), 
+    name = "Reproduction Number",
+    labels = c("R", "Adjusted R"),
     palette = "Set1"
   ) +
   theme_bw() +