https://github.com/ssi-dk/aeddo

Automated and Early Detection of Disease Outbreaks
https://github.com/ssi-dk/aeddo

Last synced: 3 days ago
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Automated and Early Detection of Disease Outbreaks

• Host: GitHub
• URL: https://github.com/ssi-dk/aeddo
• Owner: ssi-dk
• License: other
• Created: 2023-11-07T14:40:05.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-09-03T22:32:48.000Z (2 months ago)
• Last Synced: 2024-11-07T07:53:07.808Z (8 days ago)
• Language: R
• Homepage: https://ssi-dk.github.io/aeddo/
• Size: 4.29 MB
• Stars: 1
• Watchers: 3
• Forks: 0
• Open Issues: 4
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE

Awesome Lists containing this project

README

        
---

output: github_document

---

```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

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

  out.width = "100%"

)

```

# aeddo 

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

[![R-CMD-check](https://github.com/ssi-dk/aeddo/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/ssi-dk/aeddo/actions/workflows/R-CMD-check.yaml)

[![Codecov test coverage](https://codecov.io/gh/ssi-dk/aeddo/branch/main/graph/badge.svg)](https://app.codecov.io/gh/ssi-dk/aeddo?branch=main)

[![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)

## aeddo: Automated and Early Detection of Disease Outbreaks

aeddo is an R package that provides a cutting-edge solution for the automated and early detection of disease outbreaks in time series data. This innovative tool leverages hierarchical models in a novel way to infer one-step ahead random effects, which are subsequently used to identify and characterize disease outbreaks.

## Why aeddo?

Epidemiologists, public health professionals, and researchers are often challenged by the need to detect disease outbreaks promptly. Timely identification is critical for implementing appropriate control measures and mitigating the impact of outbreaks. aeddo is designed to address this challenge and offer a range of benefits:

* **Innovative Approach**: aeddo employs hierarchical models to estimate one-step ahead random effects, enabling early detection of outbreaks in disease data. This approach is a game-changer in epidemiological analysis.

* **Effectively Controls False Alarms**: aeddo's applications are broad and relevant across the field of epidemiology. It supports professionals and researchers in various domains, including public health, epidemiological research, and data analysis, while effectively controlling the number of false alarms.

* **Real-time Insights**: By providing prospective detection capabilities, aeddo offers real-time insights into disease outbreak patterns. This is invaluable for making data-driven decisions and implementing timely interventions.

## Installation

``` r

# Install aeddo from CRAN

install.packages("aeddo")

```

### Development version

You can install the development version of `aeddo` from

[GitHub](https://github.com/) with:

``` r

# install.packages("devtools")

devtools::install_github("ssi-dk/aeddo")

```

Start leveraging aeddo today to gain a unique perspective on disease

outbreak detection in your time series data.

## Get Started

Explore the package's functions and features by referring to the documentation. Detailed examples and use cases are provided to help you make the most of aeddo in your epidemiological work.

## Contributions

Contributions to aeddo are welcomed. If you have suggestions, feature requests, or encounter issues, please don't hesitate to open an [issue](https://github.com/ssi-dk/aeddo/issues) or submit a [pull request](https://github.com/ssi-dk/aeddo/pulls).