## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----echo = FALSE-------------------------------------------------------------
pkgVersion <- packageDescription("EpiSignalDetection")$Version
pkgDate <- packageDescription("EpiSignalDetection")$Date
authorsString <- gsub("^ *|(?<= ) |\n| *$", "", 
                      packageDescription("EpiSignalDetection")$Authors, perl = TRUE)
authorList <- eval(parse(text = authorsString))
pkgAuthors <- paste(format(authorList, 
                           include = c("given", "family", "email", "comment"), 
                           braces = list(email = c("<", ">,<br />"), comment = c("", ""))), 
                    collapse = "<br /><br />")
pkgMaintainer <- packageDescription("EpiSignalDetection")$Maintainer
pkgLicense <- packageDescription("EpiSignalDetection")$License
pkgUrl <- packageDescription("EpiSignalDetection")$URL

## ----eval=FALSE, echo=TRUE----------------------------------------------------
# install.packages("EpiSignalDetection")
# library(EpiSignalDetection)
# EpiSignalDetection::runEpiSDApp()

## ----echo=FALSE, results='asis'-----------------------------------------------
my_dataset <- EpiSignalDetection::importAtlasExport("./data/ECDC_surveillance_data_Pertussis_20180717.csv")
knitr::kable(head(my_dataset), 
             format = "html", table.attr = 'class="myTable"',
             format.args = list(decimal.mark = ".", big.mark = ","),
             align = 'c',
             caption = "__Tab.1 Example of Pertussis data exported from the ECDC Atlas__")

## ----echo=FALSE, results='asis'-----------------------------------------------
my_dataset <- EpiSignalDetection::SignalData
my_dataset <- dplyr::filter(my_dataset, my_dataset$HealthTopic == "Salmonellosis")
my_dataset <- dplyr::group_by(my_dataset, dplyr::across(dplyr::all_of("Population")))
my_dataset <- dplyr::summarise(my_dataset, "NumValue" = sum(NumValue, na.rm = TRUE))
my_dataset <- dplyr::ungroup(my_dataset)
my_dataset <- dplyr::arrange(my_dataset, desc(my_dataset$NumValue))
knitr::kable(my_dataset,
             format = "html", table.attr = 'class="myTable"',
             format.args = list(decimal.mark = ".", big.mark = ","),
             align = 'c',
             caption = "__Tab.2 Number of cases in each stratum using Salmonellosis data exported from the ECDC Atlas__")

## -----------------------------------------------------------------------------
my_parameters <- EpiSignalDetection::AlgoParam
names(my_parameters)

## ----echo = FALSE-------------------------------------------------------------
knitr::kable(my_parameters$FarringtonFlexible, 
             format = "html", table.attr = 'class="myTable"',
             format.args = list(decimal.mark = ".", big.mark = ","),
             align = 'c',
             caption = "__Tab.3 Parameters for the Farrington Flexible algorithm__")
knitr::kable(my_parameters$GLRNB, 
             format = "html", table.attr = 'class="myTable"',
             format.args = list(decimal.mark = ".", big.mark = ","),
             align = 'c',
             caption = "__Tab.4 Parameters for the GLRNB algorithm__")

## ----echo = FALSE, results = 'hide'-------------------------------------------
my_input <- list(
  disease = "Salmonellosis",
  country = "EU-EEA - complete series",
  indicator = "Reported cases",
  stratification = "Confirmed cases",
  unit = "Month",
  daterange = c("2012-01-01", "2016-12-31"),
  algo = "FarringtonFlexible",
  testingperiod = 5
)

png(file = "plots/plot_time_series.png", width = 1450, height = 500, res=90)
EpiSignalDetection::plotSD(input = my_input)
dev.off()

## -----------------------------------------------------------------------------
my_dataset <- EpiSignalDetection::SignalData
knitr::kable(head(my_dataset))

## -----------------------------------------------------------------------------
my_input <- list(
  disease = "Salmonellosis",
  country = "EU-EEA - complete series",
  indicator = "Reported cases",
  stratification = "Confirmed cases",
  unit = "Month",
  daterange = c("2012-01-01", "2016-12-31"),
  algo = "FarringtonFlexible",
  testingperiod = 5
)

## ----eval = FALSE-------------------------------------------------------------
# EpiSignalDetection::plotSD(input = my_input)

## ----eval = FALSE-------------------------------------------------------------
# EpiSignalDetection::runEpiSDReport(
#   outputfile = "C:/R/test.html",
#   input = my_input)

## ----eval = FALSE-------------------------------------------------------------
# EpiSignalDetection::runEpiSDReport(
#   outputfile = "C:/R/test.html",
#   input = my_input,
#   stratified = TRUE)

## ----eval = FALSE-------------------------------------------------------------
# EpiSignalDetection::runEpiSDReport()
# [1] "Dataset (please enter the full path to the csv file, or just press 'Enter' to use the default dataset)"
# 1:
# Read 0 items
# [1] "Disease / Health topic (e.g. Salmonellosis):"
# 1:  Salmonellosis
# Read 1 item
# [1] "Region name (e.g. EU-EEA - complete series):"

## -----------------------------------------------------------------------------
my_dataset <- EpiSignalDetection::importAtlasExport("./data/ECDC_surveillance_data_Pertussis_20180717.csv")

## -----------------------------------------------------------------------------
my_dataset <- EpiSignalDetection::cleanAtlasExport(my_dataset)

## -----------------------------------------------------------------------------
my_input <- list(
  disease = "Pertussis",
  country = "EU-EEA - complete series",
  indicator = "Reported cases",
  stratification = "All cases",
  unit = "Month",
  daterange = c("2012-01-01", "2016-12-31"),
  algo = "FarringtonFlexible",
  testingperiod = 6
)

## -----------------------------------------------------------------------------
my_dataset <- EpiSignalDetection::filterAtlasExport(my_dataset, my_input)

## -----------------------------------------------------------------------------
my_dataset <- EpiSignalDetection::aggAtlasExport(my_dataset, my_input)

## ----eval = FALSE-------------------------------------------------------------
# EpiSignalDetection::plotSD(x = my_dataset, input = my_input)

## ----echo = FALSE, results = 'hide'-------------------------------------------
png(file = "plots/plot_time_series_external.png", width = 1450, height = 500, res=90)
EpiSignalDetection::plotSD(x = my_dataset, input = my_input)
dev.off()

## ----eval = FALSE-------------------------------------------------------------
# my_input <- list(
#   file = list(datapath = "C:/data/ECDC_surveillance_data_Pertussis_20180717.csv"),
#   disease = "Pertussis",
#   country = "Greece",
#   indicator = "Reported cases",
#   stratification = "All cases",
#   unit = "Month",
#   daterange = c("2011-12-01", "2016-12-01"),
#   algo = "FarringtonFlexible",
#   testingperiod = 3
# )
# 
# EpiSignalDetection::runEpiSDReport(input = my_input)

## ----eval = FALSE-------------------------------------------------------------
# my_input <- list(
#   file = list(datapath = "C:/data/ECDC_surveillance_data_Salmonella_20180717.csv"),
#   disease = "Salmonellosis",
#   country = "EU-EEA - complete series",
#   indicator = "Reported cases",
#   stratification = "Confirmed cases",
#   unit = "Month",
#   daterange = c("2011-12-01", "2016-12-01"),
#   algo = "FarringtonFlexible",
#   testingperiod = 6
# )
# 
# EpiSignalDetection::runEpiSDReport(input = my_input, stratified = TRUE)

