c(
person( given = "Lore", family = "Merdrignac",
role = c("aut", "ctr"), email = "l.merdrignac@epiconcept.fr", comment = "Author of the package and original code"),
person( given = "Joana", family = "Gomes Dias",
role = c("aut", "fnd", "cre"), email = "joana.gomes.dias@ecdc.europa.eu", comment = "Project manager and package maintainer"),
person( given = "Esther", family = "Kissling",
role = c("aut", "ctr"), email = "e.kissling@epiconcept.fr"),
person( given = "Tommi", family = "Karki",
role = c("aut", "fnd"), email = "tommi.karki@ecdc.europa.eu"),
person( given = "Margot", family = "Einoder-Moreno",
role = c("ctb", "fnd"), email = "margot.einoder-moreno@ecdc.europa.eu"))
Exploring time series for signal detection. It is specifically designed
to detect possible outbreaks using infectious disease surveillance data
at the European Union / European Economic Area or country level.
Automatic detection tools used are presented in the paper
"Monitoring count time series in R: aberration detection in public health surveillance",
by Salmon et al. (2016) <doi:10.18637/jss.v070.i10>.
The package includes:
- Signal Detection tool, an interactive 'shiny' application
in which the user can import external data and perform basic signal detection analyses;
- An automated report in HTML format, presenting the results of the time series analysis in tables and graphs.
This report can also be stratified by population characteristics (see 'Population' variable).
This project was funded by the European Centre for Disease Prevention and Control.
shiny, dplyr, pander, DT, surveillance, ISOweek, ggplot2,
graphics, utils, knitr (>= 1.20), rmarkdown
Lore Merdrignac [aut, ctr] (Author of the package and original code),
Joana Gomes Dias [aut, fnd, cre] (Project manager and package
maintainer),
Esther Kissling [aut, ctr],
Tommi Karki [aut, fnd],
Margot Einoder-Moreno [ctb, fnd]

c(
person( given = "Lore", family = "Merdrignac",
role = c("aut", "ctr", "cre"), email = "l.merdrignac@epiconcept.fr", comment = "Author of the package and original code"),
person( given = "Joana", family = "Gomes Dias",
role = c("aut", "fnd"), email = "joana.gomes.dias@ecdc.europa.eu", comment = "Project manager"),
person( given = "Esther", family = "Kissling",
role = c("aut", "ctr"), email = "e.kissling@epiconcept.fr"),
person( given = "Tommi", family = "Karki",
role = c("aut", "fnd"), email = "tommi.karki@ecdc.europa.eu"),
person( given = "Margot", family = "Einoder-Moreno",
role = c("ctb", "fnd"), email = "margot.einoder-moreno@ecdc.europa.eu"))
Exploring time series for signal detection. It is specifically designed
to detect possible outbreaks using infectious disease surveillance data
at the European Union / European Economic Area or country level.
Automatic detection tools used are presented in the paper
"Monitoring count time series in R: aberration detection in public health surveillance",
by Salmon (2016) <doi:10.18637/jss.v070.i10>.
The package includes:
- Signal Detection tool, an interactive 'shiny' application
in which the user can import external data and perform basic signal detection analyses;
- An automated report in HTML format, presenting the results of the time series analysis in tables and graphs.
This report can also be stratified by population characteristics (see 'Population' variable).
This project was funded by the European Centre for Disease Prevention and Control.
dplyr, graphics, ISOweek, rmarkdown, shiny, surveillance,
utils
Lore Merdrignac [aut, ctr, cre] (Author of the package and original
code),
Joana Gomes Dias [aut, fnd] (Project manager),
Esther Kissling [aut, ctr],
Tommi Karki [aut, fnd],
Margot Einoder-Moreno [ctb, fnd]