EpiSignalDetection (version 0.1.2)

algoSD: Build algo object

Description

Build algo object from an sts object class using either FarringtonFlexible or GLRNB surveillance algorithm

Usage

algoSD(x.sts, algo = "FarringtonFlexible", timeUnit = "Month", testingPeriod = 5)

Arguments

x.sts

sts class object (see stsSD output)

algo

character string containing the name of the algorithm to use. Options are "FarringtonFlexible" (default) or "GLRNB".

timeUnit

character string for the time unit of the time series. Options are "Week" or "Month".

testingPeriod

numeric: number of time units (months, weeks) back in time to test the algorithm on (to detect outbreaks in)

Value

sts

See Also

stsSD plotSD

Examples

# NOT RUN {
#-- Setting the parameters to run the report for
input <- list(
disease = "Salmonellosis",
country = "EU-EEA - complete series",
indicator = "Reported cases",
stratification = "Confirmed cases",
unit = "Month",
daterange = c("2010-01-01", "2016-12-31"),
algo = "FarringtonFlexible",
testingperiod = 5
)

#-- Example dataset
dataset <- EpiSignalDetection::SignalData

#-- Filtering on declared input parameters
dataset <- filterAtlasExport(dataset, input)

#-- Aggregating the data by geographical level and time point
dataset <- aggAtlasExport(dataset, input)

#-- Bulding the corresponding sts object
dataset.sts <- stsSD(observedCases = dataset$NumValue,
                     studyPeriod = dataset$StudyPeriod,
                     timeUnit = input$unit,
                     startYM = c(as.numeric(format(as.Date(input$daterange[1], "%Y-%m-%d"), "%Y")),
                                 as.numeric(format(as.Date(input$daterange[1], "%Y-%m-%d"), "%m"))))

#-- Building the corresponding algo object
dataset.algo <- algoSD(dataset.sts,
                       algo = input$algo,
                       timeUnit = input$unit,
                       testingPeriod =
                       input$testingperiod)

# }