Compartmental epidemic models for forecasting and analysis of infectious disease pandemics: contributions from Ben Bolker, Jonathan Dushoff, David Earn, Morgan Kain, Michael Li, Irena Papst (in alphabetical order). Feedback is welcome at the issues list, or e-mail us.

Documentation

  • See the accompanying pkgdown site.
  • Functions are under the Reference tab.
  • Vignettes (under construction!) are under Articles.
  • Issues list.
  • Shiny app written by Zach Levine

Installation

The repository contains an R package and various workflows/analyses. You can fork/clone the repository (from here) and install locally or use remotes::install_github("mac-theobio/McMasterPandemic") to install the package. You will need to first install the developer version of bbmle (remotes::install_github("bbolker/bbmle")) before installing McMasterPandemic.

For developers

  • the main system dependencies are R, git, and pandoc (latest versions are recommended, but not strictly required) – there are other dependencies (e.g. curl, openssl), but the specific requirements will vary among platforms (see dockerfile for details on Debian Linux)
  • as a convenience you can install all of the R and tex package dependencies using make dependencies or running /misc/dependencies.R
  • to re-install the package, including re-building and incorporating vignettes, use make build-package
  • If you modify function arguments, you should change the roxygen documentation accordingly. If you change the roxygen documentation, please use make doc-update to update the .Rd files.
  • please test/check the package periodically as you go (use make pkgcheck and make pkgtest from the shell or devtools::check() and devtools::test() from within R). (Tests are also run on GitHub Actions; if you want to skip CI testing, e.g. for a trivial commit, put [skip ci] somewhere in your commit message.) Please don’t make a habit of pushing without testing.
  • To avoid whitespace diffs between versions/branches, automatically style the package with make style or run misc/macpan_style.R. make style (or running misc/macpan_lint.R) also creates a new file, misc/lints.csv, which contains stylistic and other lints that styler cannot automatically fix.
  • rebuild the pkgdown site using GitHub Actions: click “run workflow” on the link to rebuild.
  • Code that is used in the refactoring process should go in the top-level refactor folder.
  • Slow tests are skipped by default; this process is controlled by the presence of a MACPAN_TEST_LEVEL environment (shell) variable. Many of the test files contain this code:
testLevel <- if (nzchar(s <- Sys.getenv("MACPAN_TEST_LEVEL"))) as.numeric(s) else 1

which sets testLevel to a default value of 1 unless the environment variable is found. You can set this environment variable outside of your R session (e.g. via export MACPAN_TEST_LEVEL=2 in a bash shell), or via Sys.setenv(MACPAN_TEST_LEVEL=2) from within R. In principle this mechanism allows for a hierarchy of slowness; at present only 1 and >1 are distinguished.

Documentation

The documentation is a little bit scattered right now, working on cleaning it up. In addition to the standard short descriptions of the functions (help(package="McMasterPandemic")), stuff can be found:

  • in the vignettes (look at the source code in the [vignettes] directory or vignette(<title>, package="McMasterPandemic"))
    • getting_started
    • model: design decisions and information for developers
    • calibration (very out of date)
    • farr: stuff on Farr’s law and phenomenological curve-fitting (very incomplete and likely to remain so for now)
    • testing_flow: incorporating testing dynamics (ditto)
  • McMasterReport.Rnw: this is a more or less up-to-date description of calibration to Ontario data
  • ontario_calibration_report.html: more technical and less up-to-date than the preceding document
  • TODO.md: active to-do list

More bits and pieces: notes/refactor.Rmd, testing.md, reimplementation.md

DISCLAIMER

All use of this package is at your own risk. Quantitative forecasts are only as good as their parameter estimates.