Dynamical Systems Approach to Infectious Disease Epidemiology
This R package consists of a set of simulations (refered to here as apps) that teach infectious disease epidemiology from a dynamical system perspective. By manipulating the models through the Shiny UI interface and working through the instructions provided within the Shiny UI, you can learn about some important concepts in infectious disease epidemiology. You will also learn how models can be used to study such concepts.
I assume you have R
installed. I also highly recommend RStudio
, though it's not required.
- Install the CRAN release in the usual way with
install.packages('DSAIDE')
. - The latest development version (potentially buggy) can be installed from github, using the devtools package. If you don't have it, install the devtools package. The following commands will get you up and running:
install.packages('devtools')
devtools::install_github('ahgroup/DSAIDE')
After install (which you need to do only once), load the package by runing library('DSAIDE')
. You should receive a short greeting. Now you can open the main menu by running dsaidemenu()
. From the main menu, choose the different apps corresponding to different modeling topics and scenarios. Each app contains information on the model and topic that are covered. Each app also contains a list of recommeded tasks to work through in order to learn about a specific topic. Once done exploring, close the main menu to exit back to the R
console.
You can call the underlying simulation functions directly from the R
console. You can also download the code for all functions from the main menu and modify them to your own needs. See the package vignette for more details on the different ways to use the package. Also see the DSAIDE publication in PLoS Comp Bio.
The package is on GitHub and you can use the usual GitHub process to contribute updated, bug fixes, etc. If you don't know how to do that or don't have the time, you can also file an issue on GitHub and let me know what should be changed.
The package is built in a way that makes it (hopefully) easy for others to contribute new simulations/apps. To that end, the package contains this Markdown file, documentation.md, which provides further information on the details of the package structure. If you plan to develop new apps, or add other substantial updates, it's best to get in touch with me first via email or GitHub.
- I published a paper describing the package and how to use it which you can find and read here. Also use this paper if you want to cite the package.
- The package vignette provides details about the different ways the package can be used. I highly recommend going through it.
- The documentation.md file described above contains more information about the package structure.
- For feedback, bug reports, feature requests, etc., file a GitHub issue.
- A 'companion' package to this one, called Dynamical Systems Approaches for Immune Respone Modeling (DSAIRM), focuses on models for analyzing with-host infection dynamics. It has the same structure as DSAIDE. See the DSAIRM site for more information.
- I have solutions (as R Markdown files) to most of the 'What to do' tasks for the different apps. If you are an instructor using this package as part of a class, email me if you are interested in having access to these solutions.
This R package is developed and maintained by Andreas Handel. The following individuals have made contributions to this package: Isaac Fung, Spencer Hall, Ben Listyg, Brian McKay, John Rossow, Sina Solaimanpour, Henok Woldu.