Soft reset the combine all constant asymptomatic branch changes. I wi…

…ll rebase in the next commit/push. This commit only really adds more vignette details, in addition to changes previously made in dev.

R/disease_progression.R

@@ -51,7 +51,7 @@ progression_outcome_process <- function(
       "A",
       variables$infectivity,
       parameters$ca,
-      variables$recovery_rates,
+      variables$progression_rates,
       1/parameters$da,
       variables$state$get_index_of("D")$and(target)
     )

R/human_infection.R

@@ -521,7 +521,7 @@ schedule_infections <- function(
         parameters$ca,
         variables$recovery_rates,
         1/parameters$da,
-        to_infect
+        to_infect_asym
       )
     }
   }

R/parameters.R

@@ -278,8 +278,6 @@
 #' * incidence_rendering_min_ages - the minimum ages for incidence
 #' outputs (includes asymptomatic microscopy +); default = turned off
 #' * incidence_rendering_max_ages - the corresponding max ages; default = turned off
-#' * patent_incidence_rendering_min_ages - the minimum ages for patent incidence outputs (LM detectable), (p.v only); default = turned off
-#' * patent_incidence_rendering_max_ages - the corresponding max ages (p.v only); default = turned off
 #' * clinical_incidence_rendering_min_ages - the minimum ages for clinical incidence outputs (symptomatic); default = 0
 #' * clinical_incidence_rendering_max_ages - the corresponding max ages; default = 1825
 #' * severe_incidence_rendering_min_ages - the minimum ages for severe incidence
@@ -318,6 +316,8 @@
 #' and PCR prevalence; default = -0.968
 #' * rdt_coeff - the coefficient for the log logit relationship betweeen rdt
 #' and PCR prevalence; default = 1.186
+#' 
+#' miscellaneous:
 #'
 #' * mosquito_limit - the maximum number of mosquitoes to allow for in the
 #' simulation; default = 1.00E+05
@@ -631,4 +631,3 @@ set_parameter_draw <- function(parameters, draw){
   }
   return(parameters)
 }
-

tests/testthat/test-vivax.R

@@ -24,7 +24,7 @@ test_that('Test difference between falciparum and vivax parameter lists', {
 
   expect_identical(
     in_falciparum_not_vivax,
-    character(0)
+    c("gamma1") # asymptomatic infected infectivity towards mosquitos parameter
   )
 
   expect_identical(
@@ -38,41 +38,3 @@ test_that('Test difference between falciparum and vivax parameter lists', {
     )
   )
 })
-
-test_that('Test age structure should not change vivax infectivity', {
-  falc_parameters <- get_parameters(
-    overrides = list(
-      human_population = 1,
-      init_id  = 0.5))
-
-  vivax_parameters <- get_parameters(
-    parasite = "vivax",
-    overrides = list(
-      human_population = 1,
-      init_id  = 0.5))
-
-  state_mock <- mockery::mock('A', cycle = T)
-  mockery::stub(create_variables, 'initial_state', state_mock)
-  state_vivax_mock <- mockery::mock(list(human_states = 'A',
-                                         hypnozoites_v = 0), cycle = T)
-  mockery::stub(create_variables, 'initial_state_vivax', state_vivax_mock)
-
-  ages_mock <- mockery::mock(365, cycle = T)
-  mockery::stub(create_variables, 'calculate_initial_ages', ages_mock)
-
-  falc_variables <- create_variables(falc_parameters)
-  vivax_variables <- create_variables(vivax_parameters)
-
-  expect_equal(falc_variables$infectivity$get_values(), 0.06761596)
-  expect_equal(vivax_variables$infectivity$get_values(), 0.1)
-
-  ages_mock <- mockery::mock(365*70, cycle = T)
-  mockery::stub(create_variables, 'calculate_initial_ages', ages_mock)
-
-  falc_variables <- create_variables(falc_parameters)
-  vivax_variables <- create_variables(vivax_parameters)
-
-  expect_equal(falc_variables$infectivity$get_values(), 0.03785879)
-  expect_equal(vivax_variables$infectivity$get_values(), 0.1)
-
-})

vignettes/Plasmodium_vivax.Rmd

@@ -39,13 +39,23 @@ Then we can run the simulation as normal:
 simulation <- run_simulation(timesteps = 100, parameters = p)
 ```
 
-## Parameters
+## Model details
+
+### Parameters
 
 Our default *P. vivax* parameters are sourced from a version of the analysis in White et al. 2018 (doi: 10.1038/s41467-018-05860-8), where model parameters were fitted to data from Papua New Guinea. The chosen parameter set fixes `b = 0.25` and `sigma_squared = 1.67` (for consistency with the *P. falciparum* model). The default parameters for both parasite species can be found in `data/raw/parasite_parameters.csv`, while parameters common to both models are given in `R/parameters.R` under `get_parameters()`.
 
 Values for the model fitting posterior distribution can be selected using the `set_parameter_draw()` function as found in the [Parameter Variation](https://mrc-ide.github.io/malariasimulation/articles/ParameterVariation.html) vignette.
 
-## Model structure
+### Structure
+
+The *P. falciparum* model has five human disease compartments: susceptible (S), clinical disease (D), asymptomatic infection (A), sub-patent infection (U), and treated (Tr). Asymptomatic infections may or may not be detectable by light-microscopy.
+
+The *P. vivax* model follows a similar structure to the *P. falciparum* model, and also has five human disease compartments. However, the human disease states modeled explicitly focus on parasite density and detectability, such that we have: susceptible (S), clinical disease (D), **light-microscopy detectable infection (A)**, **PCR detectable infection (U)**, and treated (Tr).
+
+### Infectivity of LM-detectable infections
+
+While the *P. falciparum* model calculates the onward infectivity of asymptomatic infections (`ca`) using the age and detectability immunity of each individual, the *P. vivax* model uses a constant infectivity for LM-detectable infections (`ca = 0.1`).
 
 ### Key Model References