Vivax competing hazards main drugs

NAMESPACE

@@ -1,8 +1,13 @@
 # Generated by roxygen2: do not edit by hand
 
 export(AL_params)
+export(AL_params_falciparum)
+export(CQ_PQ_params_vivax)
+export(CQ_params_vivax)
 export(DHA_PQP_params)
+export(DHA_PQP_params_falciparum)
 export(SP_AQ_params)
+export(SP_AQ_params_falciparum)
 export(arab_params)
 export(create_pev_profile)
 export(fun_params)

R/drug_parameters.R

@@ -1,44 +1,95 @@
+#' @title Preset parameters for the DHA-PQP drug
+#' @description From SI of Commun. 5:5606 doi: 10.1038/ncomms6606 (2014)
+#' @details Use a vector of preset parameters for the DHA-PQP drug (dihydroartemisinin-piperaquine)
+#' @details Default parameters, from L to R, are: drug_efficacy: 0.95, drug_rel_c: 0.09434, drug_prophylaxis_shape: 4.4, drug_prophylaxis_scale: 28.1
+#' @export
+DHA_PQP_params_falciparum <- c(.95, 0.09434, 4.4, 28.1)
+
 #' @title Preset parameters for the DHA-PQP drug
 #' @description From SI of Commun. 5:5606 doi: 10.1038/ncomms6606 (2014)
 #' @details Use a vector of preset parameters for the DHA-PQP drug (dihydroartemisinin-piperaquine)
 #' @details Default parameters, from L to R, are: drug_efficacy: 0.95, drug_rel_c: 0.09434, drug_prophylaxis_shape: 4.4, drug_prophylaxis_scale: 28.1
 #' @export
 DHA_PQP_params <- c(.95, 0.09434, 4.4, 28.1)
 
+#' @title Preset parameters for the AL drug
+#' @description From SI of Commun. 5:5606 doi: 10.1038/ncomms6606 (2014)
+#' @details Use a vector of preset parameters for the AL drug (artemether-lumefantrine)
+#' @details Default parameters, from L to R, are: drug_efficacy: 0.95, drug_rel_c: 0.05094, drug_prophylaxis_shape: 11.3, drug_prophylaxis_scale: 10.6
+#' @export
+AL_params_falciparum <- c(.95, 0.05094, 11.3, 10.6)
+
 #' @title Preset parameters for the AL drug
 #' @description From SI of Commun. 5:5606 doi: 10.1038/ncomms6606 (2014)
 #' @details Use a vector of preset parameters for the AL drug (artemether-lumefantrine)
 #' @details Default parameters, from L to R, are: drug_efficacy: 0.95, drug_rel_c: 0.05094, drug_prophylaxis_shape: 11.3, drug_prophylaxis_scale: 10.6
 #' @export
 AL_params <- c(.95, 0.05094, 11.3, 10.6)
 
+#' @title Preset parameters for the SP-AQ drug
+#' @details Use a vector of preset parameters for the SP-AQ drug (sulphadoxine-pyrimethamine and amodiaquine)
+#' @details Default parameters, from L to R, are: drug_efficacy: 0.9, drug_rel_c: 0.32, drug_prophylaxis_shape: 4.3, drug_prophylaxis_scale: 38.1
+#' @export
+SP_AQ_params_falciparum <- c(0.9, 0.32, 4.3, 38.1)
+
 #' @title Preset parameters for the SP-AQ drug
 #' @details Use a vector of preset parameters for the SP-AQ drug (sulphadoxine-pyrimethamine and amodiaquine)
 #' @details Default parameters, from L to R, are: drug_efficacy: 0.9, drug_rel_c: 0.32, drug_prophylaxis_shape: 4.3, drug_prophylaxis_scale: 38.1
 #' @export
 SP_AQ_params <- c(0.9, 0.32, 4.3, 38.1)
 
+#' @title Preset parameters for the CQ drug acting on P. vivax
+#' @description Efficacy from SI of Nekkab et al., DOI: 10.1371/journal.pmed.1003535 (2021),
+#' shape and scale consistent with a longer prophylaxis time: 28 days, decreasing gradually
+#' @details Use a vector of preset parameters for the CQ drug (chloroquine) acting on P. vivax
+#' @details Default parameters, from L to R, are: drug_efficacy: 0.899, drug_rel_c: 0.5, drug_prophylaxis_shape: 20, drug_prophylaxis_scale: 5
+#' @export
+CQ_params_vivax <- c(0.899, 0.5, 5, 20)
+
+#' @title Preset parameters for the CQ-PQ drug acting on P. vivax
+#' @description Efficacy from SI of Nekkab et al., DOI: 10.1371/journal.pmed.1003535 (2021),
+#' BS shape and scale consistent with a longer prophylaxis time: 28 days, decreasing gradually,
+#' LS shape are scale consistent with a 7 day PQ treatment, with rapid decay.
+#' @details Use a vector of preset parameters for the CQ-PQ drug (chloroquine and primaquine) acting on P. vivax
+#' @details Default parameters, from L to R, are: drug_efficacy: 0.948, drug_rel_c: 0.5, drug_prophylaxis_shape: 5, drug_prophylaxis_scale: 20,
+#' drug_hypnozoite_efficacy: 0.713, drug_hypnozoite_prophylaxis_shape: 10, drug_hypnozoite_prophylaxis_scale: 5.5
+#' @export
+CQ_PQ_params_vivax <- c(0.948, 0.5, 5, 20, 0.713, 10, 5.5)
+
+#' @title Preset parameters for the CQ-TQ drug acting on P. vivax
+#' @description Efficacy from SI of Nekkab et al., DOI: 10.1371/journal.pmed.1003535 (2021),
+#' BS shape and scale consistent with a longer prophylaxis time: 28 days, decreasing gradually,
+#' LS shape are scale consistent with a single TQ treatment, with longer prophylaxis: 45 days.
+#' @details Use a vector of preset parameters for the CQ-TQ drug (chloroquine and tafenoquine) acting on P. vivax
+#' @details Default parameters, from L to R, are: drug_efficacy: 1, drug_rel_c: 0.5, drug_prophylaxis_shape: 5, drug_prophylaxis_scale: 20,
+#' drug_hypnozoite_efficacy: 0.713, drug_hypnozoite_prophylaxis_shape: 5.5, drug_hypnozoite_prophylaxis_scale: 30
+CQ_TQ_params_vivax <- c(1, 0.5, 5, 20, 0.713, 5, 30)
+
 #' @title Parameterise drugs to use in the model
 #'
 #' @param parameters the model parameters
 #' @param drugs a list of drug parameters, can be set using presets
 #' @export
 set_drugs <- function(parameters, drugs) {
-  stopifnot(is.list(drugs))
+  stopifnot("is.list(drugs) is not TRUE" = is.list(drugs))
   keys <- c(
     'drug_efficacy',
     'drug_rel_c',
     'drug_prophylaxis_shape',
-    'drug_prophylaxis_scale'
+    'drug_prophylaxis_scale',
+    # hypnozoite parameters
+    'drug_hypnozoite_efficacy',
+    'drug_hypnozoite_prophylaxis_shape',
+    'drug_hypnozoite_prophylaxis_scale'
   )
+
   for (drug in seq_along(drugs)) {
     for (i in seq_along(drugs[[drug]])) {
-      parameters[[keys[[i]]]] <- c(parameters[[keys[[i]]]], drugs[[drug]][[i]])
+      parameters[[keys[[i]]]][drug] <- drugs[[drug]][[i]]
     }
   }
   parameters
 }
-
 #' @title Parameterise clinical treatment
 #'
 #' @param parameters the model parameters

R/human_infection.R

@@ -519,13 +519,33 @@ relapse_bite_infection_hazard_resolution <- function(
   ## all bitten humans with an infectious bite (incorporating prophylaxis) get a new batch of hypnozoites
   if(bite_infections$size()>0){
 
+    ## drug prophylaxis may limit formation of new hypnozoite batches
+    ls_prophylaxis <- rep(0, bite_infections$size())
+    if(length(parameters$drug_hypnozoite_efficacy) > 0){
+
+      ls_drug <- variables$ls_drug$get_values(bite_infections)
+      ls_medicated <- (ls_drug > 0)
+      ls_medicated[ls_drug > 0] <- !is.na(parameters$drug_hypnozoite_efficacy[ls_drug])
+
+      if (any(ls_medicated)) {
+        ls_drug <- ls_drug[ls_medicated]
+        ls_drug_time <- variables$ls_drug_time$get_values(bite_infections)[ls_medicated]
+        ls_prophylaxis[ls_medicated] <- weibull_survival(
+          timestep - ls_drug_time,
+          parameters$drug_hypnozoite_prophylaxis_shape[ls_drug],
+          parameters$drug_hypnozoite_prophylaxis_scale[ls_drug]
+        )
+      }
+    }
+
     # make sure batches are capped
-    current_batches <- variables$hypnozoites$get_values(bite_infections)
+    new_hypnozoite_batch_formed <- bitset_at(bite_infections, bernoulli_multi_p(1 - ls_prophylaxis))
+    current_batches <- variables$hypnozoites$get_values(new_hypnozoite_batch_formed)
     new_batch_number <- pmin(current_batches + 1, parameters$kmax)
 
     variables$hypnozoites$queue_update(
       new_batch_number,
-      bite_infections
+      new_hypnozoite_batch_formed
     )
   }
 }
@@ -729,6 +749,15 @@ calculate_treated <- function(
     )
   }
 
+  # Update liver stage drug effects
+  if(length(parameters$drug_hynozoite_efficacy) > 0){
+    if(successfully_treated$successfully_treated_hypnozoites$size() > 0){
+      variables$hypnozoites$queue_update(0, successfully_treated$successfully_treated_hypnozoites)
+      variables$ls_drug$queue_update(drug, successfully_treated$successfully_treated_hypnozoites)
+      variables$ls_drug_time$queue_update(timestep, successfully_treated$successfully_treated_hypnozoites)
+    }
+  }
+
   successfully_treated$successfully_treated
 
 }
@@ -808,6 +837,16 @@ calculate_successful_treatments <- function(
       successfully_treated = successfully_treated)
 
   }
+
+  if(length(parameters$drug_hypnozoite_efficacy) > 0){
+    effectively_treated_hypnozoites_index <- bernoulli_multi_p(parameters$drug_hypnozoite_efficacy[drugs])
+    successfully_treated_hypnozoites <- bitset_at(target, effectively_treated_hypnozoites_index)
+    successfully_treated_list <- c(
+      successfully_treated_list,
+      successfully_treated_hypnozoites = successfully_treated_hypnozoites
+    )
+  }
+
   successfully_treated_list
 }
 

R/mda_processes.R

@@ -137,6 +137,15 @@ update_mass_drug_admin <- function(
     variables$drug_time$queue_update(timestep, target$successfully_treated)
 
   }
+
+  # Update liver stage drug effects
+  if(length(parameters$drug_hypnozoite_efficacy) > 0){
+    if(target$successfully_treated_hypnozoites$size() > 0){
+      variables$hypnozoites$queue_update(0, target$successfully_treated_hypnozoites)
+      variables$ls_drug$queue_update(drug, target$successfully_treated_hypnozoites)
+      variables$ls_drug_time$queue_update(timestep, target$successfully_treated_hypnozoites)
+    }
+  }
 }
 
 #' @title Calculate asymptomatic detectable individuals

R/parameters.R

@@ -403,6 +403,9 @@ get_parameters <- function(overrides = list(), parasite = "falciparum") {
       drug_rel_c             = numeric(0),
       drug_prophylaxis_shape = numeric(0),
       drug_prophylaxis_scale = numeric(0),
+      drug_hypnozoite_efficacy = numeric(0),
+      drug_hypnozoite_prophylaxis_shape = numeric(0),
+      drug_hypnozoite_prophylaxis_scale = numeric(0),
       clinical_treatment_drugs     = list(),
       clinical_treatment_timesteps = list(),
       clinical_treatment_coverages = list(),

R/pmc.R

@@ -63,6 +63,5 @@ create_pmc_process <- function(
       timestep,
       drug
     )
-
   }
 }

R/processes.R

@@ -47,7 +47,7 @@ create_processes <- function(
     immunity_process = create_exponential_decay_process(variables$ica,
                                                         parameters$rc)
   )
-  
+
   if(parameters$parasite == "falciparum"){
     processes <- c(
       processes,

R/variables.R

@@ -35,6 +35,8 @@
 #' * infectivity - The onward infectiousness to mosquitos
 #' * drug - The last prescribed drug
 #' * drug_time - The timestep of the last drug
+#' * ls_drug - The last prescribed drug
+#' * ls_drug_time - The timestep of the last drug
 #'
 #' Antimalarial resistance variables are:
 #' * dt - the delay for humans to move from state Tr to state S
@@ -286,6 +288,11 @@ create_variables <- function(parameters) {
   drug <- individual::IntegerVariable$new(rep(0, size))
   drug_time <- individual::IntegerVariable$new(rep(-1, size))
 
+  if(length(parameters$drug_hypnozoite_efficacy) > 0){
+    ls_drug <- individual::IntegerVariable$new(rep(0, size))
+    ls_drug_time <- individual::IntegerVariable$new(rep(-1, size))
+  }
+
   last_pev_timestep <- individual::IntegerVariable$new(rep(-1, size))
   last_eff_pev_timestep <- individual::IntegerVariable$new(rep(-1, size))
   pev_profile <- individual::IntegerVariable$new(rep(-1, size))