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Contains all the scripts needed to recreate the analyses and figures in the bed bug disclosure paper.

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Dynamics of bed bug infestations and control under disclosure policies

This repository contains scripts that can be used to recreate the analyses and figures presented in the manuscript titled Dynamics of bed bug infestations and control under disclosure policies: Short-term costs lead to long-term savings. A description of the repository's contents are provided below.

Script files

All scripts can be found in the code folder. For scripts to run correctly, it is important to: (1) install all necessary packages (listed within the library function in the first few lines of code) and (2) set the working directory to the location of the downloaded repository.

Calculate cost and prevalence while varying p and s

  • costmatrix.R - Runs multiple simulations to calculate disclosure cost and year-end prevalence over a range of values for p and s. The output of costmatrix.R can be found in output_costmatrix.
  • costmatrix_renters.R - Same as costmatrix but calculates disclosure cost from the perspective of renters. The output of costmatrix.R can be found in output_costmatrix_renters.

Figures

  • figure_barplot.R - plots Figure 2
  • figure_cost.R - plots Figure 3 from the output of costmatrix.R
  • figure_prevalence.R - plots Figure 4 from the output of costmatrix.R

Supplemental tables and figures

  • stable_twopopmodel.R - outputs values used to populate Table S1
  • sfigure_components.R - plots Figure S1
  • sfigure_relativeprevalencereduction.R - plots Figure S2
  • sfigure_discountedcosts.R - plots Figure S3
  • sfigure_renters_barplot.R - plots Figure S4
  • sfigure_costtorenters.R - plots Figure S5 from the output of costmatrix_renters.R
  • sfigure_sensitivitytoparameters.R - plots Figures S6-S9
  • sfigure_intermarketmigration.R - plots Figure S10
  • sfigure_googletrends.R - plots Figure S11
  • sfigure_breakevenpoint.R - plots Figure S12
  • sfigure_ddm_barplot.R - plots Figure S13
  • sfigure_ddm_props.R - plots Figure S14

Shiny figures

  • shinyapp_fig_costplots.R - makes the plots used in the app's landlord cost animation
  • shinyapp_fig_rentercostplots.R - makes the plots used in the app's renter cost animation
  • shinyapp_fig_prevalenceplots.R - makes the plots used in the app's prevalence animation

User-defined functions

Contains the user-defined functions sourced by the other scripts.

  • functions.R - contains user-defined functions used in the primary analysis that is presented in the main text of the manuscript
  • functions_extra.R - contains additional user-defined functions for sub- and sensitivity analyses that are presented in the Supporting Information

Plot time-course of bed bug spread

The output of these scripts are not used in the manuscript, but are a good place to start to get an understanding of the models.

  • plotodes.R - plots the number of units in each class (Sr, Ir, etc.) for a single simulation, with user controls to change parameter values. Note: time unit for parameter values is in days.
  • plotodes_years.R - same as plotodes.R except time unit for parameters is in years.
  • plotodes_imm.R - same as plotodes.R with the addition of intermarket migration parameters (i.e. i and e). Note: time unit for parameter values is in days.
  • plotodes_ddm.R - same as plotodes.R but modified to approximate a discrete disclosure period. Note: time unit for parameter values is in days.

Other files

Shiny app

R scripts and image files used to create the R Shiny web application associated with this manuscript can be found in the shinyApp folder. The app can also be run locally with code/shinyapp_local.R

Figures

Figures in the main text of the manuscript can be found in the figures folder, and those in the Supplemental Information can be found in the figures_supplement folder. All figures were either directly output from R or were output from R and then imported into keynote for formatting.

Data

Data from Google Trends presented in Figure S7 can be found in the data folder.

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Contains all the scripts needed to recreate the analyses and figures in the bed bug disclosure paper.

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