CM scaling that helps speed up some runs

jameel-institute · Oct 31, 2024 · 213fab3 · 213fab3
1 parent ad93975
commit 213fab3
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Showing 3 changed files with 6 additions and 4 deletions.
diff --git a/R/class_country.R b/R/class_country.R
@@ -429,15 +429,17 @@ prepare_parameters.daedalus_country <- function(x, ...) {
 
   demography <- get_data(x, "demography")
 
-  # scale contacts by largest real eigenvalue
-  cm <- get_data(x, "contact_matrix")
+  # scale M[i, ] by demography[j]
+  cm_unscaled <- get_data(x, "contact_matrix")
+  cm <- cm_unscaled / demography
   cmw <- get_data(x, "contacts_workplace")
   cmcw <- get_data(x, "contacts_consumer_worker")
   workers <- get_data(x, "workers")
 
   list(
     demography = demography,
     contact_matrix = cm,
+    cm_unscaled = cm_unscaled, # for use in Rt calculations
     contacts_workplace = cmw / workers, # scaled by workers
     contacts_consumer_worker = cmcw
   )

diff --git a/R/ode.R b/R/ode.R
@@ -118,7 +118,7 @@ daedalus_rhs <- function(t, state, parameters) {
 
   community_infectious <- community_infectious[i_AGE_GROUPS]
 
-  cm_inf <- beta * cm %*% (community_infectious / demography)
+  cm_inf <- beta * cm %*% (community_infectious)
 
   # NOTE: `state` and `cm_inf` mult. assumes length(cm_inf) == nrows(state)
   new_community_infections <- state_[, i_S, ]

diff --git a/R/reff_calculation.R b/R/reff_calculation.R
@@ -28,7 +28,7 @@ r_eff <- function(state, parameters) {
   demography <- parameters$demography
 
   beta <- parameters$beta
-  cm <- parameters$contact_matrix
+  cm <- parameters$cm_unscaled
   sigma <- parameters$sigma
   p_sigma <- parameters$p_sigma
   epsilon <- parameters$epsilon