--- Package under development ---

mwss: an R package for 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)

Installation

The package can be install using 'devtools' library:

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

The companion RShiny application providing user-friendly interface to run simulations can be loaded directly from the GitHub repository (https://github.com/MESuRS-Lab/mwss-App) using 'shiny' library:

library(shiny) # use version >= 1.7.1
runGitHub("MESuRS-Lab/mwss-App")

Main contents

This repository contains the source code for the "mwss" package developed using R-programming language. This package allows the user to run multi-ward stochastic simulations to simulate virus transmission in the hospital setting.

mwss
├── R
├── data
├── man
├── DESCRIPTION
├── NAMESPACE
├── mwss.Rproj

• R
  This folder contains all the package functions

• Data
  This folder contains the toydataset to run the examples documented for each exported function.

Further actions

• sensitivity analysis
• publications