--- Application under development ---

mwss-App: an R-Shiny application to run stochastic simulation of infectious diseases spreading in healthcare systems structured as networked metapopulations

Hammami Pachka^1,2,3,, Oodally Ajmal^1,2,3,, Reilhac Astrid⁴, Guérineau de Lamérie Guillaume⁴, Widgren Stefan ⁵, Temime Laura^3,6,¤ and Opatowski Lulla^1,2,¤

¹ Anti-infective evasion and pharmacoepidemiology team, Université Paris-Saclay, UVSQ, Inserm, CESP, Montigny-Le-Bretonneux, France

² Epidemiology and Modelling of Antibiotic Evasion (EMAE), Institut Pasteur, Paris, France

³ Laboratoire de Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire national des arts et métiers, Paris, France

⁴ Département d'information médicale, Centre hospitalier Guillaume Régnier, Rennes, France

⁵ Department of Disease Control and Epidemiology, National Veterinary Institute, Uppsala, Sweden

⁶ PACRI unit, Institut Pasteur, Conservatoire national des arts et métiers, Paris, France ⁷MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, United Kingdom

^*These authors contributed equally

^¤These authors contributed equally

Corresponding author: Hammami Pachka (pachka@hotmail.fr)

Run mwss-App from your R console or RStudio with one command

Open your R console or RStudio and paste the commands provided below. mwss-App will automatically install all required dependencies (R packages).

library("shiny")
runGitHub("MESuRS-Lab/mwss-App")

The main package used is mwss available in our GitHub page: https://github.com/MESuRS-Lab/mwss

Required Shiny version >= 1.7.1

Dependencies

This version of mwss-App was developed on R version 4.1.3 (2022-03-10) with Windows 10 x64 (build 18363) using the following version of dependencies:

mwss-App
├── shiny_1.7.1
├── shinyalert_3.0.0
├── shinydashboard_0.7.2 
├── shinyhelper_0.3.2
├── shinyjs_2.1.0
├── shinyTime_1.0.1
├── shinyWidgets_0.7.0
├── DT_0.23
├── data.table_1.14.2
├── SimInf_9.0.0
├── statnet_2019.6
├── igraph_1.3.1
├── network_1.17.2
├── plotly_4.10.0
├── magrittr_2.0.3
├── dplyr_1.0.9
├── knitr_1.39
├── devtools_2.4.3
├── ggplot2_3.3.6

The package mwss developed simultaneously should always be up to date with the online version.

library(devtools)
install_github("MESuRS-Lab/mwss")

Main contents

This repository contains the source code for the "mwss-App" RShiny application developed using R-programming language. The RShiny application provides a comprehensive, user-friendly interface to run complex stochastic simulations for the nosocomial spread of Covid-19 in multi-service healthcare systems.

mwss-App
├── body
├── data
├── functions
├── header
├── helpfiles
├── www
├── report.Rmd
├── app.R
├── global.R
├── server.R
├── ui.R

• body
  This folder contains the main ui files shaping the different panels.

• data
  This folder contains the toydataset and parameters for different Covid-19 variants.

• functions
  This folder contains the modules.

• header
  This folder contains the ui file designing the header.

• helpfiles
  This folder contains the markdown content of help notes.

• www
  This folder contains the images displayed in the application.

• report.Rmd
  This RMarkdown file contains the structure of the report that can be downloaded after runing simulations.

• R files

  • app.R
  • global.R
  • server.R
  • ui.R Those files are baseline files for Rshiny application (read more on: https://shiny.rstudio.com/articles/scoping.html)

Further actions

• complete report content
• define parameters for two variants (e.g. alpha and omicron) & fill References tabs
• test by modelers (Lulla, Ajmal, Laura) -> test by clinicians (Hackathon)
• upgrade
• publication