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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 as well as 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}
epiparameters <- epiparameter_db()
epiparameters
```
This results in a list of database entries. Each entry of the library is an `<epiparameter>` 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_epiparameter = TRUE` as we only want a single database entry returned, and by default (`single_epiparameter = FALSE`) it will return all database entries that match the disease (`disease`) and epidemiological distribution (`epi_dist`).
```{r load-single-epiparameter}
influenza_incubation <- epiparameter_db(
disease = "influenza",
epi_dist = "incubation period",
single_epiparameter = TRUE
)
influenza_incubation
```
To quickly view the list of epidemiological distributions returned by `epiparameter_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(epiparameters)
parameter_tbl(
epiparameters,
epi_dist = "onset to hospitalisation"
)
```
The `<epiparameter>` object can be plotted.
```{r plot-epiparameter}
plot(influenza_incubation)
```
The CDF can also be plotted by setting `cumulative = TRUE`.
```{r, plot-epiparameter-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")
```