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.
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:
You can install the development version of aeddo from GitHub with:
Start leveraging aeddo today to gain a unique perspective on disease outbreak detection in your time series data.
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 to aeddo are welcomed. If you have suggestions, feature requests, or encounter issues, please don’t hesitate to open an issue or submit a pull request.