In ian-hastings/rotations: Simulating the Evolution of Insecticide Resistance under Rotations

library(knitr)
#https://stackoverflow.com/a/36234023/1718356 for fig.pos = 'h'

opts_chunk$set(fig.height=7, fig.width=9, fig.pos = 'h', echo=FALSE, warning=FALSE, message=FALSE)  

library(rotations)
library(ggplot2)

outFolder <- "C:\\Dropbox\\resistanceResults\\rotations\\"

Resistance frequencies can take longer to rise for rotations than sequences once cost (or refugia) are included. Particularly noticeable when the rotation interval is short, costs (0.1) and dominance (1) high.

Can this be a simple mathematical result of:

1. slower rate of resistance frequency change at lower resistance frequencies.
2. rotation initially keeps frequencies lower where this rate of change is less.

#for above
#\pagebreak

linputs <- list()

linputs$n_insecticides <- 2
linputs$coverage <- 1
#linputs$migration <- 0.1
linputs$cost <-     0.1 
linputs$max_gen <-  200
linputs$expo_hi <-  0.6
linputs$eff <-      0.6
linputs$dom_sel <-  1
linputs$dom_cos <-  1
linputs$plot <-     FALSE

linputs$rot_interval=0
dfseq <- do.call(run_rot, linputs)
linputs$rot_interval=6
dfrot <- do.call(run_rot, linputs)

ggrot <- rot_plot_resistance(dfrot, plot_refuge=FALSE, logy=FALSE, plot=FALSE)
ggseq <- rot_plot_resistance(dfseq, plot_refuge=FALSE, logy=FALSE, plot=FALSE)
library(gridExtra)
grid.arrange(ggrot, ggseq, ncol=1)
grot <- as.numeric(gens_under_thresh(dfrot))
gseq <- as.numeric(gens_under_thresh(dfseq))
cat('sum generations deployed insecticide under threshold rotation:', grot,' sequence:',gseq)

print(unlist(linputs))

\pagebreak

Cost reduced from 0.1 to 0.02. Radically cuts difference between rotation and sequence.

#for above
#\pagebreak

linputs <- list()

linputs$n_insecticides <- 2
linputs$coverage <- 1
#linputs$migration <- 0.1
linputs$cost <-     0.02 
linputs$max_gen <-  200
linputs$expo_hi <-  0.6
linputs$eff <-      0.6
linputs$dom_sel <-  1
linputs$dom_cos <-  1
linputs$plot <-     FALSE

linputs$rot_interval=0
dfseq <- do.call(run_rot, linputs)
linputs$rot_interval=6
dfrot <- do.call(run_rot, linputs)

ggrot <- rot_plot_resistance(dfrot, plot_refuge=FALSE, logy=FALSE, plot=FALSE)
ggseq <- rot_plot_resistance(dfseq, plot_refuge=FALSE, logy=FALSE, plot=FALSE)
library(gridExtra)
grid.arrange(ggrot, ggseq, ncol=1)
grot <- as.numeric(gens_under_thresh(dfrot))
gseq <- as.numeric(gens_under_thresh(dfseq))
cat('sum generations deployed insecticide under threshold rotation:', grot,' sequence:',gseq)

print(unlist(linputs))

\pagebreak

Decreasing dominance of resistance and cost from 1 to 0 (had to increase exposure, effectiveness and rr to get similar times-to-resistance). Then the difference between rotation and sequence is less.

linputs <- list()

linputs$n_insecticides <- 2
linputs$coverage <- 1
#linputs$migration <- 0.1
linputs$cost <-     0.02 
linputs$max_gen <-  200
linputs$expo_hi <-  0.8
linputs$eff <-      0.8
linputs$rr  <-      0.8
linputs$dom_sel <-  0
linputs$dom_cos <-  0
linputs$plot <-     FALSE

linputs$rot_interval=0
dfseq <- do.call(run_rot, linputs)
linputs$rot_interval=6
dfrot <- do.call(run_rot, linputs)

ggrot <- rot_plot_resistance(dfrot, plot_refuge=FALSE, logy=FALSE, plot=FALSE)
ggseq <- rot_plot_resistance(dfseq, plot_refuge=FALSE, logy=FALSE, plot=FALSE)
library(gridExtra)
grid.arrange(ggrot, ggseq, ncol=1)
grot <- as.numeric(gens_under_thresh(dfrot))
gseq <- as.numeric(gens_under_thresh(dfseq))
cat('sum generations deployed insecticide under threshold rotation:', grot,' sequence:',gseq)

print(unlist(linputs))

\pagebreak

Dominance of cost 0 and dom_sel 1.

Benefit of rotation is lost, sequence lasts a tiny bit longer. Suggests it is a high dominance of cost that favours sequence over rotation.

linputs <- list()

linputs$n_insecticides <- 2
linputs$coverage <- 1
#linputs$migration <- 0.1
linputs$cost <-     0.1 
linputs$max_gen <-  200
linputs$expo_hi <-  0.6
linputs$eff <-      0.6
linputs$dom_sel <-  1
linputs$dom_cos <-  0
linputs$plot <-     FALSE

linputs$rot_interval=0
dfseq <- do.call(run_rot, linputs)
linputs$rot_interval=6
dfrot <- do.call(run_rot, linputs)

ggrot <- rot_plot_resistance(dfrot, plot_refuge=FALSE, logy=FALSE, plot=FALSE)
ggseq <- rot_plot_resistance(dfseq, plot_refuge=FALSE, logy=FALSE, plot=FALSE)
library(gridExtra)
grid.arrange(ggrot, ggseq, ncol=1)
grot <- as.numeric(gens_under_thresh(dfrot))
gseq <- as.numeric(gens_under_thresh(dfseq))
cat('sum generations deployed insecticide under threshold rotation:', grot,' sequence:',gseq)

print(unlist(linputs))

\pagebreak dom_sel and dom_cost 0.1, small favour of rotation

linputs <- list()

linputs$n_insecticides <- 2
linputs$coverage <- 1
#linputs$migration <- 0.1
linputs$cost <-     0.1 
linputs$max_gen <-  200
linputs$expo_hi <-  0.8
linputs$eff <-      0.8
linputs$dom_sel <-  0.1
linputs$dom_cos <-  0.1
linputs$plot <-     FALSE

linputs$rot_interval=0
dfseq <- do.call(run_rot, linputs)
linputs$rot_interval=6
dfrot <- do.call(run_rot, linputs)

ggrot <- rot_plot_resistance(dfrot, plot_refuge=FALSE, logy=FALSE, plot=FALSE)
ggseq <- rot_plot_resistance(dfseq, plot_refuge=FALSE, logy=FALSE, plot=FALSE)
library(gridExtra)
grid.arrange(ggrot, ggseq, ncol=1)
grot <- as.numeric(gens_under_thresh(dfrot))
gseq <- as.numeric(gens_under_thresh(dfseq))
cat('sum generations deployed insecticide under threshold rotation:', grot,' sequence:',gseq)

print(unlist(linputs))

ian-hastings/rotations documentation built on Dec. 14, 2020, 11:42 p.m.