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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "75%",
fig.align = "center"
)
```
# epiparameter <img src="man/figures/logo.png" align="right" width="120" />
<!-- badges: start -->
[](https://opensource.org/licenses/MIT)
[](https://github.com/epiverse-trace/epiparameter/actions/workflows/R-CMD-check.yaml)
[](https://app.codecov.io/gh/epiverse-trace/epiparameter?branch=main)
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[](https://doi.org/10.5281/zenodo.11110881)
<!-- badges: end -->
`{epiparameter}` is an `R` package that contains a library of epidemiological parameters for infectious diseases and a set of classes and helper functions to work with the data. It also includes functions to extract and convert parameters from reported summary statistics.
`{epiparameter}` is developed at the [Centre for the Mathematical Modelling of Infectious Diseases](https://www.lshtm.ac.uk/research/centres/centre-mathematical-modelling-infectious-diseases) at the [London School of Hygiene and Tropical Medicine](https://www.lshtm.ac.uk/) as part of [Epiverse-TRACE](https://data.org/initiatives/epiverse/).
## Installation
The easiest way to install the development version of `{epiparameter}` is to use the `{pak}` package:
``` r
# check whether {pak} is installed
if(!require("pak")) install.packages("pak")
pak::pak("epiverse-trace/epiparameter")
```
Alternatively, install pre-compiled binaries from [the Epiverse TRACE R-universe](https://epiverse-trace.r-universe.dev/epiparameter)
```r
install.packages("epiparameter", repos = c("https://epiverse-trace.r-universe.dev", "https://cloud.r-project.org"))
```
## Quick start
```{r load-epiparameter}
library(epiparameter)
```
To load the library of epidemiological parameters into `R`:
```{r load-data}
epidists <- epidist_db()
epidists
```
This results a list of database entries. Each entry of the library is an `<epidist>` object.
Alternatively, the library of epiparameters can be viewed as a vignette locally (`vignette("database", package = "epiparameter")`) or on the [{epiparameter} website](https://epiverse-trace.github.io/epiparameter/articles/database.html).
The results can be filtered by disease and epidemiological distribution. Here we set `single_epidist = TRUE` as we only want a single database entry returned, and by default (`single_epidist = FALSE`) it will return all database entries that match the disease (`disease`) and epidemiological distribution (`epi_dist`).
```{r load-single-epidist}
influenza_incubation <- epidist_db(
disease = "influenza",
epi_dist = "incubation period",
single_epidist = TRUE
)
influenza_incubation
```
To quickly view the list of epidemiological distributions returned by `epidist_db()` in a table, the `parameter_tbl()` gives a summary of the data, and offers the ability to subset you data by `disease`, `pathogen` and epidemiological distribution (`epi_dist`).
```{r parameter-tbl}
parameter_tbl(epidists)
parameter_tbl(
epidists,
epi_dist = "onset to hospitalisation"
)
```
The `<epidist>` object can be plotted.
```{r plot-epidist}
plot(influenza_incubation)
```
The CDF can also be plotted by setting `cumulative = TRUE`.
```{r, plot-epidist-cdf}
plot(influenza_incubation, cumulative = TRUE)
```
### Parameter conversion and extraction
The parameters of a distribution can be converted to and from mean and standard deviation. In `{epiparameter}` we implement this for a variety of distributions:
- gamma
- lognormal
- Weibull
- negative binomial
- geometric
The parameters of a probability distribution can also be extracted from other summary statistics, for example, percentiles of the distribution, or the median and range of the data. This can be done for:
- gamma
- lognormal
- Weibull
- normal
## Contributing to library of epidemiological parameters
If you would like to contribute to the different epidemiological parameters stored in the `{epiparameter}` package, you can add data to a public [google sheet](https://docs.google.com/spreadsheets/d/1eCL3n_woseg5Npu7XD7TcuNoLUIhMBu8ZoLCkVdATUE/edit?usp=sharing). This spreadsheet contains two example entries as a guide to what fields can accept. We are monitoring this sheet for new entries that will subsequently be included in the package.
Alternatively, parameters can be added to the [JSON file holding the data](https://github.com/epiverse-trace/epiparameter/blob/main/inst/extdata/parameters.json) base directly via a Pull Request.
You can find explanation of accepted entries for each column in the [data dictionary](https://github.com/epiverse-trace/epiparameter/blob/main/inst/extdata/data_dictionary.json).
## Help
To report a bug please open an [issue](https://github.com/epiverse-trace/epiparameter/issues/new/choose)
## Contribute
Contributions to `{epiparameter}` are welcomed. [package contributing guide](https://github.com/epiverse-trace/.github/blob/main/CONTRIBUTING.md).
## Code of Conduct
Please note that the `{epiparameter}` 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.
## Citing this package
```{r message=FALSE, warning=FALSE}
citation("epiparameter")
```