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https://github.com/epiverse-trace/scenarios

[SUSPENDED]: R package to compare epidemic scenario model outcomes.
https://github.com/epiverse-trace/scenarios

epidemic-modelling epidemiology epiverse r r-package

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[SUSPENDED]: R package to compare epidemic scenario model outcomes.

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README 

        
---

output: github_document

link-citations: true

---



```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```



# _{{ packagename }}_: Compare epidemic scenarios 



[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)

[![R-CMD-check](https://github.com/{{ gh_repo }}/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/{{ gh_repo }}/actions/workflows/R-CMD-check.yaml)

[![Codecov test coverage](https://codecov.io/gh/{{ gh_repo }}/branch/main/graph/badge.svg)](https://app.codecov.io/gh/{{ gh_repo }}?branch=main)

[![Project Status: Suspended – Initial development has started, but there has not yet been a stable, usable release; work has been stopped for the time being but the author(s) intend on resuming work.](https://www.repostatus.org/badges/latest/suspended.svg)](https://www.repostatus.org/#suspended)

[![CRAN status](https://www.r-pkg.org/badges/version/{{ packagename }})](https://CRAN.R-project.org/package={{ packagename }})



_{{ packagename }}_ was intended to provide functions to compare the outcomes of epidemic modelling simulations.



The development of _{{ packagename }}_ has been suspended in favour of increased scenario modelling and comparison functionality coming to the [_epidemics_](https://github.com/epiverse-trace/epidemics) package.

Development may resume once a use case for a separate comparison package is clearer.



## Installation



You can install the development version of _{{ packagename }}_ from [GitHub](https://github.com/) with:



```r

if (!require("remotes")) install.packages("remotes")

remotes::install_github("{{ gh_repo }}")

```



## Quick start



The examples below show the existing functionality; this is not currently planned to be developed further.



### An example with _finalsize_



Define an epidemic model scenario by creating a new `scenario` object. The standard workflow needs a model function, such as `finalsize::final_size()`, and appropriate arguments to the function.



```{r}

# load scenarios

library(scenarios)



# create a scenario for pandemic-potential influenza

# with finalsize::final_size() as the model function

scenario_pandemic_flu <- scenario(

  model_function = "finalsize::final_size",

  parameters = make_parameters_finalsize_UK(), # a helper function

  replicates = 3

)

```



View a summary of the `scenario`.



```{r}

scenario_pandemic_flu

```



The `scenario` object is created but the model function is not initially run. This can be checked using a helper function. Tip: Many helper functions have the prefix `sce_` to help them be found quickly when using autocomplete in various text editors and IDEs.



```{r}

# check whether the scenario data have been generated

sce_has_data(scenario_pandemic_flu)

```



Model outcome data can be generated by running the model function with the parameters specified in the `scenario`.



```{r}

scenario_pandemic_flu <- run_scenario(scenario_pandemic_flu)

```



Take a peek at the column names in the model outcome replicates.



```{r}

sce_peek_outcomes(scenario_pandemic_flu)

```



Get the outcomes from all replicates as a single dataset, or aggregate an outcome variable of interest across replicates by some grouping variable.



```{r}

# get all output

head(sce_get_outcomes(scenario_pandemic_flu))



# aggregate proportion infected by demographic group

# NOTE that all replicates have the same outcome in this deterministic model

sce_aggregate_outcomes(

  x = scenario_pandemic_flu,

  grouping_variables = c("demo_grp"),

  measure_variables = c("p_infected"),

  summary_functions = c("mean", "min", "max")

)

```



### An example with _epidemics_



This example shows the same workflow applied to a simple, deterministic epidemic model from the _epidemics_ package.



```{r}

# create a new scenario

scenario_sir <- scenario(

  model_function = "epidemics::sir_desolve",

  parameters = make_parameters_SIR_epidemic(), # a helper function

  replicates = 5L

)



# view the initial conditions and infection parameters

sce_get_information(scenario_sir, which = c("init", "parms"))



# generate scenario outcomes by running the model

scenario_sir <- run_scenario(scenario_sir)



# peek at the outcomes

sce_peek_outcomes(scenario_sir)



# view the aggregated outcomes

# this is the per-timestep, per-class (S, I, R) mean proportion

# and is the same across replicates in this deterministic model

tail(

  sce_aggregate_outcomes(

    scenario_sir,

    grouping_variables = c("time", "state"),

    measure_variables = "proportion",

    summary_functions = "mean"

  )

)

```



## Help 



To report a bug please open an [issue](https://github.com/{{ gh_repo }}/issues/new/choose); please note that development on _{{ packagename }}_ has been suspended.



## Contribute



Development on _{{ packagename }}_ has been suspended.



However, use cases or requirements for a package that helps compare outcomes of epidemic scenario models are very welcome as issues, or on the main [Epiverse Discussion board](https://github.com/orgs/epiverse-trace/discussions).



Please follow the [package contributing guide](https://github.com/{{ gh_repo }}/blob/main/.github/CONTRIBUTING.md).



## Code of conduct



Please note that the _{{ packagename }}_ project is released with a [Contributor Code of Conduct](https://github.com/epiverse-trace/.github/blob/main/CODE_OF_CONDUCT.md). By contributing to this project, you agree to abide by its terms.