Compare the normoblast population to data

vignettes/evidence-for-parameter-values.Rmd

@@ -33,6 +33,9 @@ suppressPackageStartupMessages(library(here))
 
 output_dir <- here("outputs")
 
+pf <- baseline_parameters("Pf")
+pv <- baseline_parameters("Pv")
+
 # Remove non-scalar derived parameters, such as the initial red blood cell
 # populations.
 remove_nonscalar_derived_parameters <- function(x) {
@@ -40,9 +43,18 @@ remove_nonscalar_derived_parameters <- function(x) {
 }
 
 # Define how to format parameter values of different magnitudes.
-format_value <- function(x, nsmall=4, min=1e-3, max=1e3) {
+format_value <- function(x, nsmall = 4, digits = 5, min = 1e-3, max = 1e3,
+                         delim = TRUE) {
   scientific <- x < min || x > max
-  result <- format(x, digits = 5, nsmall=3, scientific = scientific)
+  result <- format(x, digits = digits, nsmall = nsmall,
+                   scientific = scientific)
+  if (delim) {
+    start <- "\\("
+    end <- "\\)"
+  } else {
+    start <- ""
+    end <- ""
+  }
   if (scientific) {
     # Convert from scientific notation to "X x 10^Y".
     parts <- strsplit(result, "e")[[1]]
@@ -51,14 +63,19 @@ format_value <- function(x, nsmall=4, min=1e-3, max=1e3) {
     power <- sub("^\\+", "", parts[2])
     # Strip leading zeros from positive and negative exponents.
     power <- sub("^(-?)0*", "\\1", power)
-    paste0("\\(", digits, "\\times 10^{", power, "}\\)")
+    paste0(start, digits, "\\times 10^{", power, "}", end)
   } else {
     # Strip fractional digits for integer values.
     result <- sub("\\.0+$", "", result)
-    paste0("\\(", result, "\\)")
+    paste0(start, result, end)
   }
 }
 
+# Convenience function for inline R expressions.
+pretty <- function(x, digits = 3, nsmall = 0, delim = FALSE) {
+  format_value(x, digits = digits, nsmall = nsmall, delim = delim)
+}
+
 # Return the baseline parameters for a species as a long data frame.
 get_baseline_parameters <- function(species) {
   baseline_parameters(species = species) |>
@@ -100,6 +117,8 @@ baseline <- dplyr::inner_join(
 # available evidence (if any).
 baseline <- baseline |>
   dplyr::mutate(Evidence = dplyr::case_when(
+    Parameter == "gamma" ~ "[Normoblast population in the bone marrow]",
+    Parameter == "M_t_1" ~ "[Macrophage population in the spleen]",
     Parameter == "MaxFold" ~ "[Maximum fold increase in RBC production]",
     Parameter == "PMF" ~ "[Parasite multiplication]",
     Parameter == "rho0" ~ "[Reticulocyte release from bone marrow]",
@@ -139,12 +158,12 @@ Figure 3 of Appendix 1 shows the haematocrit response and reticulocyte count res
 
 Steven Kho:
 
-> I have done a literature search and couldn't find a reference that states the exact number above or in that range.
 > The reference we have previously used for bone marrow cellularity and content is [@Harris62] which states a mean of \(11.1 \times 10^9\) nucleated cells/kg body weight, of which 28.4% are normoblasts.
 > Therefore, in an average 60kg Papuan male, this data suggests the bone marrow contains \(6.7 \times 10^{11}\) normoblasts, which is about 2 log-folds higher than the current value in the model.
 > If I look at other studies cited in this paper (Table 5), values do fall in this range when you adjust to total bodyweight.
-> Could it be possible that the current model value is still corrected per kg bodyweight?
-> Were there any clues in the script to where this value was obtained
+
+At steady-state we obtain \(\gamma = `r pretty(pf$gamma)`\), which results in a normoblast population of \(`r pretty(pf$gamma * pf$T_n)`\).
+This is \(`r pretty(100 * pf$gamma * pf$T_n / 6.7e11 - 100)`\%\) higher than \(6.7 \times 10^{11}\).
 
 ## Parasite multiplication