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Older age groups (older than equilibrium age object) are not correctl… #301

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merged 4 commits into from
May 24, 2024
Merged

Older age groups (older than equilibrium age object) are not correctl… #301

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Older age groups (older than equilibrium age object) are not correctl…
RJSheppard May 9, 2024
40e4f87
Changed the initial age distribution to a truncated exponential to re…
RJSheppard May 21, 2024
4994b82
Merge branch 'dev' into older_age_state_immunity_init
RJSheppard May 24, 2024
5eb21fa
Merge branch 'dev' into older_age_state_immunity_init
RJSheppard May 24, 2024
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4 changes: 4 additions & 0 deletions R/variables.R
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Original file line number Diff line number Diff line change
Expand Up @@ -321,6 +321,8 @@ initial_immunity <- function(
) {
if (!is.null(eq)) {
age <- age / 365
# older ages must be assigned within the equilibrium age bounds
age[age>=max(eq[[1]][, 'age'])] <- max(eq[[1]][, 'age'])-0.01
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Would adding a max_age parameter to calculate_initial_ages() and overwriting any initial ages > max_age in that function be a cleaner and clearer application?

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That sounds reasonable - Michael's model uses a truncated exponential distribution to draw ages anyway, so it doesn't have the same issue. It probably wouldn't be unreasonable to switch over to that. @giovannic ?

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hmm, it seems right to sample from a truncated exponential here too. From a quick look at mrc-ide/malariasimulation, it would be consistent.

You could use the maximum age in EQUILIBRIUM_AGES as your upper bound. rtexp in utils.R could do the sampling for you fyi.

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Sure thing. So if we sample ages from the truncated exponential, there won't be an issue with individuals being outside the eq solution.

My only concern is the way that the initial age distribution would be different to the age distribution at model equilibrium, although maybe this wouldn't be a problem. MW also limits ages to the max equilibrium solution age, so maintains a truncated exp dist throughout, but this might not be consistent with our model...?

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It should have very minimal impact as we're changing a very small proportion of the population

return(vnapply(
seq_along(age),
function(i) {
Expand All @@ -338,6 +340,8 @@ initial_state <- function(parameters, age, groups, eq, states) {
if (!is.null(eq)) {
eq_states <- c('S', 'D', 'A', 'U', 'T')
age <- age / 365
# older ages must be assigned within the equilibrium age bounds
age[age>=max(eq[[1]][, 'age'])] <- max(eq[[1]][, 'age'])-0.01
return(vcapply(
seq_along(age),
function(i) {
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