The Automated and Early Detection of Seasonal Epidemic Onset (aedseo)
Package provides a powerful tool for automating the early detection of
seasonal epidemic onsets in time series data. It offers the ability to
estimate growth rates for consecutive time intervals and calculate the
Sum of Cases (SoC) within those intervals. This package is particularly
useful for epidemiologists, public health professionals, and researchers
seeking to identify and respond to seasonal epidemics in a timely
fashion.
# Install aedseo from CRAN
install.packages("aedseo")You can install the development version of aedseo from
GitHub with:
# install.packages("devtools")
devtools::install_github("ssi-dk/aedseo")To quickly get started with aedseo, follow these steps:
- Install the package using the code provided above.
- Load the package with
library(aedseo). - Create a time series data object (
aedseo_tsd) from your data using thetsd()function. - Apply the
aedseo()function to estimate growth rates and detect seasonal epidemic onsets.
# Load the package
library(aedseo)
# Create a aedseo_tsd object from your data
tsd_data <- tsd(
observed = c(100, 120, 150, 180, 220, 270),
time = as.Date(c(
"2023-01-01",
"2023-01-02",
"2023-01-03",
"2023-01-04",
"2023-01-05",
"2023-01-06")
),
time_interval = "day"
)
# Detect seasonal epidemic onsets
aedseo_results <- aedseo(tsd = tsd_data, k = 3, level = 0.95, family = "poisson")For a more detailed introduction to the workflow of this package, see the introductory vignette.
# After installing the package
vignette("aedseo_introduction", package = "aedseo")We welcome contributions to the aedseo package. Feel free to open
issues, submit pull requests, or provide feedback to help us improve.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent