Dataset describing the parameters for the epidemiological report production

Description

A dataset describing the parameters to be used for each output of each disease report for all 53 health topics included in TESSy

Usage

AERparams

Format

A data frame with 53 rows (corresponding to the 53 health topics) and 24 variables:

HealthTopic

Disease code that should match with the health topic code from the disease-specific dataset e.g. ANTH, SALM, etc.

DG

(optional) Disease group e.g. FWD

DP

(optional) Disease programme e.g. FWD

Label

Disease label to be used in the report e.g. salmonellosis, anthrax

FrequencyCategory

(optional) Frequency of the disease e.g. VERY RARE, NON-RARE, etc.

MeasurePopulation

Type of population presented for this disease i.e. ALL or CONFIRMED cases

DatePublicAtlas

Date of latest availability in the public access of the Atlas

TableUse

Type of table to present in the report i.e. NO table, ASR table presenting age-standardised rates, RATE table presenting rates or COUNT table presenting the number of cases only.

TableRatesLabel

Label to use in the table for rates e.g. RATE PER 100000 POPULATION

TableRatesNoDecimals

Number of decimals to use when presenting rates

TableASRNoDecimals

Number of descimals to use when presenting ASR

AgeGenderUse

Type of age and gender bar graph to present i.e. NO graph, AG-COUNT Bar graph presenting the number of cases by age and gender, AG-RATE Bar graph presenting the rates of cases by age and gender, AG-PROP Bar graph presenting the proportion of cases by age and gender, A-RATE Bar graph presenting the rates of cases by age.

AgeGenderBarGraphLabel

Label to use in the age and gender bar graph

AgeGenderGraphNoDecimals

Number of decimals to use when presenting rates in the age and gender bar graph

TSTrendGraphUse

Logical Y/N specifying whether to include a line graph describing the trend of the disease over the time

TSSeasonalityGraphUse

Logical Y/N specifying whether to include a line graph describing the seasonality of the disease

TSSpecific

Logical Y/N for specific line graph inclusion

MapNumbersUse

Logical Y/N specifying whether to include the map presenting the number of cases by Member State

MapRatesUse

Logical Y/N specifying whether to include the map presenting the rates of cases by Member State

MapRatesNoDecimals

(optional) Number of decimals to use for presenting maps

MapASRUse

Logical Y/N specifying whether to include the map presenting the age-standardised rates of cases by Member State

MapASRNoDecimals

(optional) Number of decimals to use for presenting maps

Transmission

Not implemented yet

TransmissionNoDecimals

Not implemented yet

Dataset including Dengue data for 2015-2019

Description

A dataset containing the data and indicators required to build the epidemiological report for Dengue 2019 TESSy data (default dataset used throughout EpiReport)

Usage

DENGUE2019

Format

A data frame with 44,332 rows and 11 variables:

HealthTopicCode

Disease code e.g. ANTH, SALM, etc.

MeasureCode

Code of the measure indicator

TimeUnit

Unit of the time variable i.e. Y for yearly data or M for monthly data

TimeCode

Time variable including dates in any formats available (according to the unit defined in TimeUnit) yearly data (e.g. 2001) or monthly data (e.g. 2001-01)

GeoCode

Geographical level in coded format including country names (e.g. AT for Austria, BE for Belgium, BG for Bulgaria, see also the EpiReport::MSCode table, correspondence table for Member State labels and codes)

XValue

XValue

XLabel

The label associated with the x-axis in the epidemiological report (see getAgeGender() and plotAgeGender() bar graph for the age variable)

YValue

The value associated with the y-axis in the epidemiological report (see plotAge() bar graph for the variable age, or getTableByMS() for the number of cases, rate or age-standardised rate in the table by Member States by year)

YLabel

The label associated with the y-axis in the epidemiological report (see getAgeGender() and plotAgeGender() bar graph for the grouping variable gender)

ZValue

The value associated with the stratification of XLabel and YLabel in the age and gender bar graph (see getAgeGender() and plotAgeGender())

N

Number of cases (see getTrend() and getSeason() line graph)

See Also

The correspondence table for Member State labels and codes MSCode
and the functions mentioned above: getAgeGender, plotAgeGender, plotAge, getTableByMS, getTrend and getSeason.

Colour palettes following the March 2018 ECDC guidelines for presentation of surveillance data

Description

Full document: European Centre for Disease Prevention and Control. Guidelines for presentation of surveillance data. Stockholm: ECDC; 2018. Available from: Guidelines for presentation of surveillance data

Usage

EcdcColors(col_scale = "green", n = NULL, grey_shade = NULL, hot_cols = NULL)

Arguments

Author(s)

Tommi Karki

Examples

# Select three first green colours
EcdcColors("green", n=3)

# Select two first qualitative colours
EcdcColors("qual", n=2)

# Select seven red colours
EcdcColors("red", n=7)

EcdcColors("grey", grey_shade = c("mediumlight", "dark"))

# Use in a graph
# Dummy data
mydat <- data.frame(ID = c(seq(1,10,1)),
                    Gender = c(rep(c("F", "M"),5)))
barplot(table(mydat$Gender),
        col = EcdcColors(col_scale = "qual", n=2))

# Hot-cold colour scale
barplot(c(1:4),
        col = EcdcColors(col_scale = "hotcold", n = 4, hot_cols = 2))

Dataset correspondence table between country names and country code

Description

Dataframe providing the correspondence table of the geographical code GeoCode used in the disease dataset, and the geographical label Country to use throughout the report. Additional information on the EU/EEA affiliation is also available in column EUEEA.

Usage

MSCode

Format

A data frame with 32 rows and 3 variables:

Country

Full name of the country / Member State e.g. Austria, Belgium, etc.

TheCountry

Full name of the country / Member State including 'the' article for NL and UK e.g. Austria, Belgium, the Netherlands, the United Kingdom etc.

GeoCode

Associated code (see GeoCode variable on the SALM2016 internal dataset) e.g. AT, BE, BG, etc.

EUEEA

For each Member State, variable specifying in the country is part of the EU or EEA.

See Also

SALM2016

Dataset including Salmonellosis data for 2012-2016

Description

A dataset containing the data and indicators required to build the epidemiological report for Salmonellosis 2016 TESSy data (default dataset used throughout EpiReport)

Usage

SALM2016

Format

A data frame with 60,775 rows and 18 variables:

HealthTopicCode

Disease code e.g. ANTH, SALM, etc.

MeasureLabel

optional) Label of the measure indicator

MeasurePopulation

Population targeted by the measure indicator

MeasureCode

Code of the measure indicator

MeasureId

(optional) Measure indicator ID

MeasureType

(optional) Type of measure indicator

TimeUnit

Unit of the time variable i.e. Y for yearly data or M for monthly data

GeoLevel

(optional) Geographical level e.g. 1, 2, etc

TimeCode

Time variable including dates in any formats available (according to the unit defined in TimeUnit) yearly data (e.g. 2001) or monthly data (e.g. 2001-01)

GeoCode

Geographical level in coded format including country names (e.g. AT for Austria, BE for Belgium, BG for Bulgaria, see also the EpiReport::MSCode table, correspondence table for Member State labels and codes)

XValue

(optional) XValue

XLabel

The label associated with the x-axis in the epidemiological report (see getAgeGender() and plotAgeGender() bar graph for the age variable)

YValue

The value associated with the y-axis in the epidemiological report (see plotAge() bar graph for the variable age, or getTableByMS() for the number of cases, rate or age-standardised rate in the table by Member States by year)

YLabel

The label associated with the y-axis in the epidemiological report (see getAgeGender() and plotAgeGender() bar graph for the grouping variable gender)

ZValue

The value associated with the stratification of XLabel and YLabel in the age and gender bar graph (see getAgeGender() and plotAgeGender())

N

Number of cases (see getTrend() and getSeason() line graph)

NMissing

(optional)

NLowerResolution

(optional)

See Also

The correspondence table for Member State labels and codes MSCode
and the functions mentioned above: getAgeGender, plotAgeGender, plotAge, getTableByMS, getTrend and getSeason.

Replace a plot at a bookmark location

Description

Replace a plot at a bookmark location saving it as a PNG file in a temporary folder.
A bookmark will be considered as valid if enclosing words within a paragraph; i.e., a bookmark along two or more paragraphs is invalid, a bookmark set on a whole paragraph is also invalid, but bookmarking few words inside a paragraph is valid.

Usage

body_replace_gg_at_bkm(doc, gg, bookmark, width = 6, height = 3)

Arguments

Value

doc

Examples

doc <- officer::read_docx(path = file.path(system.file(package = "EpiReport"),
                                           "template/AER_template.docx" ))
p <- EpiReport::getTrend()
doc <- EpiReport::body_replace_gg_at_bkm(doc = doc,
                                         gg = p,
                                         bookmark = "TS_TREND",
                                         width = 6,
                                         height = 3)

Cleaning the final table

Description

Cleaning the final table: identifying missing reports with '-', replacing the Member State codes with Member State names (see correspondence table MSCode), identifying not reporting Member States with '.'

Usage

cleanECDCTable(
  x,
  Country = EpiReport::MSCode$Country,
  GeoCode = EpiReport::MSCode$GeoCode
)

Arguments

Value

cleaned ECDC dataframe

See Also

Global function: getTableByMS
Default dataset MSCode

Clean the MeasureCode variable

Description

Clean the MeasureCode variable and replace the specific codes with the generic ones
(e.g. ACCUTE.AGE_GENDER.RATE will be replaced by CONFIRMED.AGE_GENDER.RATE)

Usage

cleanMeasureCode(var)

Arguments

Details

• ALL.COUNT will replace the following codes:

  • ALL.DOMESTIC.COUNT

  • AGELT1.COUNT

• ALL.RATE will replace the following codes:

  • ALL.DOMESTIC.AGE.RATE

• ALL.AGE.RATE will replace the following codes:

  • ALL.DOMESTIC.AGE.RATE

• ALL.AGESTANDARDISED.RATE will replace the following codes:

  • ALL.DOMESTIC.AGESTANDARDISED.RATE

• CONFIRMED.COUNT will replace the following codes:

  • ALL.LABCONFIRMED.COUNT

  • CONFIRMED.LABCONFIRMED.COUNT

  • CONFIRMED.AGELT1.COUNT

  • TYPHOID.COUNT

• CONFIRMED.RATE will replace the following codes:

  • CONFIRMED.LABCONFIRMED.RATE

  • CONFIRMED.AGELT1.RATE

  • TYPHOID.RATE

• CONFIRMED.AGESTANDARDISED.RATE will replace the following codes:

  • CONFIRMED.LABCONFIRMED.AGESTANDARDISED.RATE

• CONFIRMED.AGE_GENDER.RATE will replace the following codes:

  • CONFIRMED.LABCONFIRMED.AGE_GENDER.RATE

  • TYPHOID.AGE_GENDER.RATE

  • ACCUTE.AGE_GENDER.RATE

Value

cleaned vector variable

See Also

SALM2016

Examples

x <- EpiReport::SALM2016
x$MeasureCode <- cleanMeasureCode(x$MeasureCode)

Filter disease parameters

Description

Filter the table of parameters for the report on the given disease

Usage

filterDisease(dis, reportParameters)

Arguments

Value

dataframe with one row (from the AERparams dataframe) corresponding to the parameters of the selected disease

See Also

AERparams

Examples

disease <- "SALM"
reportParameters <- EpiReport::AERparams
reportParameters <- filterDisease(disease, reportParameters)

Get full disease-specific epidemiological report

Description

Function to generate the 'Microsoft Word' epidemiological report (similar to the ECDC Annual Epidemiological Report (AER)) including all disease-specific outputs at each output-specific bookmarks exact location.
(for further information on the outputs and the corresponding bookmarks, please see the package vignette "The Epidemiological Report Package" with browseVignettes("EpiReport"))
(see ECDC AER https://www.ecdc.europa.eu/en/publications-data/monitoring/all-annual-epidemiological-reports)

Usage

getAER(
  template = file.path(system.file(package = "EpiReport"), "template/AER_template.docx"),
  outputPath = getwd(),
  x = EpiReport::DENGUE2019,
  disease = "DENGUE",
  year = 2019,
  reportParameters = EpiReport::AERparams,
  MSCode = EpiReport::MSCode,
  pathPNG = system.file("maps", package = "EpiReport")
)

Arguments

Value

A 'Word' document

See Also

Default template: getTemplate
Default datasets: MSCode AERparams SALM2016 DENGUE2019
Disease-specific outputs: getTableByMS getSeason getTrend getMap getAgeGender

Examples

## Not run: 
# --- Generating the AER report using the default Dengue dataset
getAER()

## End(Not run)

## Not run: 
# --- Or using external data (example below)
ZIKV2016 <- read.table("data/ZIKV2016.csv", sep = ",", header = TRUE, stringsAsFactors = FALSE)
output <- "C:/EpiReport/doc/"
pathMap <- "C:/EpiReport/maps/"
getAER(disease = "ZIKV", year = 2016, x = ZIKV2016, outputPath = output, pathPNG = pathMap)

## End(Not run)

Get disease-specific age and gender bar graph

Description

Function returning the age and gender bar graph that will be included in the epidemiological report at the bookmark location 'BARGPH_AGEGENDER' of the template report.
The bar graph presents the distribution of cases at EU/EEA level using either:

• AG-COUNT: The number of cases by age and gender

• AG-RATE: The rate per 100 000 cases by age and gender

• AG-PROP: The proportion of cases by age and gender

• A-RATE: The rate per 100 000 cases by age only

The choice of the type of bar graph is set in the report parameters table AERparams.
(see ECDC reports https://www.ecdc.europa.eu/en/publications-data/monitoring/all-annual-epidemiological-reports)

Usage

getAgeGender(
  x = EpiReport::DENGUE2019,
  disease = "DENGUE",
  year = 2019,
  reportParameters = EpiReport::AERparams,
  geoCode = "EU_EEA31",
  index = 1,
  doc
)

Arguments

Value

'Word' doc or a ggplot2 object

See Also

Global function for the full epidemilogical report: getAER
Required Packages: ggplot body_replace_text_at_bkm
Internal functions: plotBarGrouped (use of plotAgeGender discouraged) plotBar (use of plotAge discouraged) EcdcColors
Default datasets: AERparams

Examples

# --- Plot using the default dataset
getAgeGender()

# --- Plot using external dataset
# --- Please see examples in the vignette
browseVignettes(package = "EpiReport")

Get disease-specific map: distribution of cases by Member State

Description

Function returning the disease-specific PNG map previously created and stored in a specific folder (see pathPNG argument) and that will be included in the epidemiological report at the bookmark location of the template report, depending of the type of map. Three type of maps can be included in the report:

• Bookmark 'MAP_NB': Distribution of cases by country. An additional caption will be included at the location of the bookmark 'MAP_NB_CAPTION'.

• Bookmark 'MAP_RATE': Distribution of cases per 100 000 population by country. An additional caption will be included at the location of the bookmark 'MAP_RATE_CAPTION'.

• Bookmark 'MAP_ASR': Distribution of cases using age-strandardised rates per 100 000 population by country. An additional caption will be included at the location of the bookmark 'MAP_ASR_CAPTION'.

(see ECDC reports https://www.ecdc.europa.eu/en/publications-data/monitoring/all-annual-epidemiological-reports)

Usage

getMap(
  disease = "DENGUE",
  year = 2019,
  reportParameters = EpiReport::AERparams,
  index = 1,
  pathPNG = system.file("maps", package = "EpiReport"),
  doc
)

Arguments

Value

'Word' doc an image preview

See Also

Global function for the full epidemilogical report: getAER
Required Packages: body_replace_img_at_bkm
Internal functions: includeMap previewMap
Default datasets: AERparams

Examples

# --- Preview of the PNG map using the default Dengue dataset
getMap()

# --- Plot using external PNG image
# --- Please see examples in the vignette
browseVignettes(package = "EpiReport")

Get disease-specific seasonality graph: distribution of cases by month

Description

Function returning the plot describing the seasonality of the disease that will be included in the epidemiological report at the bookmark location 'TS_SEASON' of the template report.

The graph includes the distribution of cases at EU/EEA level, by month, over the past five years, with:

• The number of cases by month in the reference year (green solid line)

• The mean number of cases by month in the four previous years (grey dashed line)

• The minimum number of cases by month in the four previous years (grey area)

• The maximum number of cases by month in the four previous years (grey area)

(see ECDC reports https://www.ecdc.europa.eu/en/publications-data/monitoring/all-annual-epidemiological-reports)

Usage

getSeason(
  x = EpiReport::DENGUE2019,
  disease = "DENGUE",
  year = 2019,
  reportParameters = EpiReport::AERparams,
  MSCode = EpiReport::MSCode,
  index = 1,
  doc
)

Arguments

Value

'Word' doc or a ggplot2 object

See Also

Global function for the full epidemilogical report: getAER
Required Packages: ggplot body_replace_text_at_bkm
Internal functions: plotSeasonality
Default datasets: AERparams MSCode

Examples

# --- Plot using the default dataset
getSeason()

# --- Plot using external dataset
# --- Please see examples in the vignette
browseVignettes(package = "EpiReport")

Get disease-specific table: distribution of cases by Member State (GeoCode)

Description

Function returning the table ('flextable') that will be included in the epidemiological report at the bookmark location 'TABLE1' of the template report. An additional caption will be included at the location of the bookmark 'TABLE1_CAPTION'.
(see Table 1 of the ECDC annual reports https://www.ecdc.europa.eu/en/publications-data/monitoring/all-annual-epidemiological-reports)

Usage

getTableByMS(
  x = EpiReport::DENGUE2019,
  disease = "DENGUE",
  year = 2019,
  reportParameters = EpiReport::AERparams,
  MSCode = EpiReport::MSCode,
  index = 1,
  doc
)

Arguments

Details

The current version of the 'EpiReport' package includes three types of table (see detailed specification of the tables in the package vignette with browseVignettes(package = "EpiReport")):

• COUNT - Table presenting the number of cases by Member State (GeoCode) over a 5-year period;

• RATE - Table presenting the number of cases and rates by Member State (GeoCode) over a 5-year period;

• ASR - Table presenting the number of cases and rates by Member State (GeoCode) over a 5-year period, including age-standardised rates for the most recent year.

Value

'Word' doc or flextable object (see 'flextable' package)

See Also

Global function for the full epidemiological report: getAER
Required Packages: flextable cursor_bookmark
Internal functions: shapeECDCFlexTable cleanECDCTable
Default datasets: AERparams MSCode

Examples

# --- Draft the table using the default Dengue dataset
getTableByMS()

Get epidemiological report (empty) template

Description

Function to export the generic 'Microsoft Word' empty template (included in the 'EpiReport' package) used to produce the epidemiological report similar to the ECDC Annual Epidemiological Report (AER). The modified version of the template can then be used to produce the final epidemiological report using getAER(template = 'NewTemplate.docx', ...)
(see the package vignette "The Epidemiological Report Package" with browseVignettes("EpiReport"))
(see ECDC annual epidemilogical reports https://www.ecdc.europa.eu/en/publications-data/monitoring/all-annual-epidemiological-reports)

Usage

getTemplate(output_path)

Arguments

Value

A 'Word' document

See Also

getAER

Examples

## Not run: 
# --- Export the template in the default folder: working directory
getTemplate()

# --- Or specify the full path
getTemplate(output_path = getwd())

## End(Not run)

Get disease-specific trend plot: trend and number of cases by month

Description

Function returning the plot describing the trend of the disease over time that will be included in the epidemiological report at the bookmark location 'TS_TREND' on the template report.

The graph includes the number of cases at EU/EEA level, by month, over the past five years, with:

• The number of cases by month over the 5-year period (grey solid line)

• The 12-month moving average of the number of cases by month (green solid line)

(see ECDC reports https://www.ecdc.europa.eu/en/publications-data/monitoring/all-annual-epidemiological-reports)

Usage

getTrend(
  x = EpiReport::DENGUE2019,
  disease = "DENGUE",
  year = 2019,
  reportParameters = EpiReport::AERparams,
  MSCode = EpiReport::MSCode,
  index = 1,
  doc
)

Arguments

Value

'Word' doc or a ggplot2 preview

See Also

Global function for the full epidemilogical report: getAER
Required Packages: ggplot body_replace_text_at_bkm
Internal functions: plotTS12MAvg
Default datasets: AERparams MSCode

Examples

# --- Plot using the default dataset
getTrend()

# --- Plot using external dataset
# --- Please see examples in the vignette
browseVignettes(package = "EpiReport")

Including PNG map in the 'Microsoft Word' template

Description

Function including the disease-specific PNG map in the 'Word' document at the specific bookmark location.

Usage

includeMap(
  disease,
  year,
  reportParameters,
  index,
  pathPNG,
  doc,
  pop,
  namePNGsuffix,
  unit,
  mapBookmark,
  captionBookmark
)

Arguments

Value

'Word' doc

See Also

Global function: getMap

Order 'quasinumerical' categorical vectors (increasing order)

Description

A function to order 'quasinumerical' (i.e. categorical with values such as "15-30" or "<18") integer vectors into increasing order. Currently handles away the following non-numerical characters "-", ">", "<", ">=", "<=", "+".

Usage

orderQuasinum(x)

Arguments

Author(s)

Tommi Karki

See Also

Used in getAgeGender and plotAgeGender / plotAge

Examples

age1 <- c("<1", "1-15", "16-25", ">65", "26-65")
age2 <- c("0-4", "5-10", ">65", "25-64", "11-25")
age3 <- c("5-10", ">65", "25-64", "11-25", "<=4")
age4 <- c(">=65", "<18", "18-64")
age5 <- c("5-10", "+65", "25-64", "11-25", "0-4")

age1
orderQuasinum(age1)
age2
orderQuasinum(age2)
age3
orderQuasinum(age3)
age4
orderQuasinum(age4)
age5
orderQuasinum(age5)

Age bar graph

Description

(Discouraged function. Please use plotBarGrouped() instead.)

Usage

plotAge(
  .data,
  xvar = "XLabel",
  yvar = "YValue",
  fill_color1 = "#65B32E",
  ytitle = "Rate"
)

Arguments

Details

This function draws a bar graph by age group (or possibly other grouping).
The bar graph presents the distribution of cases at EU/EEA level using the rate per 100 000 cases by age.
Expects aggregated data.

See Also

Global function: getAgeGender
Internal function: EcdcColors
Required Packages: ggplot

Examples

# --- Create dummy data
mydat <- data.frame(AgeGroup = c("0-25", "26-65", "65+"),
                    NumberOfCases = c(54,32,41))

# --- Plot the dummy data
plotAge(mydat,
        xvar = "AgeGroup",
        yvar = "NumberOfCases",
        ytitle = "Number of cases")

Age and Gender bar graph

Description

(Discouraged function. Please use plotBarGrouped() instead.)

Usage

plotAgeGender(
  .data,
  xvar = "XLabel",
  yvar = "ZValue",
  group = "YLabel",
  fill_color1 = "#65B32E",
  fill_color2 = "#7CBDC4",
  ytitle = "Rate"
)

Arguments

Details

This function draws a bar graph of the distribution of cases by age group and gender (or possibly other grouping).
The bar graph presents the distribution of cases at EU/EEA level using either:

• AG-COUNT: The number of cases by age and gender

• AG-RATE: The rate per 100 000 cases by age and gender

• AG-PROP: The proportion of cases by age and gender

Expects aggregated data.

See Also

Global function: getAgeGender
Internal function: EcdcColors
Required Packages: ggplot

Examples

# --- Create dummy data
mydat <- data.frame(Gender=c("F", "F", "M", "M"),
                    AgeGroup = c("0-65", "65+", "0-65", "65+"),
                    NumberOfCases = c(54,43,32,41))

# --- Plot the dummy data
plotAgeGender(mydat,
              xvar = "AgeGroup",
              yvar = "NumberOfCases",
              group = "Gender",
              ytitle = "Number of cases")

Bar graph

Description

This function draws a bar graph of the values of variable 'Yvar' with the categorical variable 'Xvar' on the x-axis.
Expects aggregated data.

Usage

plotBar(
  .data,
  xvar = "XLabel",
  xlabel = "",
  yvar = "YValue",
  ylabel = "",
  fill_color = EcdcColors(col_scale = "qual", n = 1)
)

Arguments

See Also

Global function: getAgeGender
Internal function: EcdcColors
Required Packages: ggplot

Examples

# --- Create dummy data
mydat <- data.frame(AgeGroup = c("0-25", "26-65", "65+"),
                    NumberOfCases = c(54,32,41))

# --- Plot the dummy data
plotBar(mydat,
        xvar = "AgeGroup",
        xlabel = "Age",
        yvar = "NumberOfCases",
        ylabel = "Number of cases")

Grouped bar graph

Description

This function draws a vertical grouped bar graph of the values of variable 'Yvar' with the categorical variable 'Xvar' on the x-axis and grouped by 'Group' categorical variable.
Expects aggregated data.

Usage

plotBarGrouped(
  .data,
  xvar = "XLabel",
  xlabel = "",
  yvar = "ZValue",
  ylabel = "",
  group = "YLabel",
  fill_color = EcdcColors(col_scale = "qual", n = length(unique(.data[[group]]))),
  position = "dodge"
)

Arguments

See Also

Global function: getAgeGender
Internal function: EcdcColors
Required Packages: ggplot

Examples

# --- Create dummy data
mydat <- data.frame(Gender=c("F", "F", "M", "M"),
                    AgeGroup = c("0-65", "65+", "0-65", "65+"),
                    NumberOfCases = c(30, 35, 70, 65))

# --- Plot the dummy data
plotBarGrouped(mydat,
              xvar = "AgeGroup",
              xlabel = "Age",
              yvar = "NumberOfCases",
              ylabel = "Number of cases",
              group = "Gender")

# -- Create dummy data
mydat <- data.frame(VaccStatus = rep(c("Unvaccinated", "1 dose", "2 doses", "3 doses"), 3),
                    AgeGroup = rep(c("<1", "1-4", "5-9") , each = 4),
                    Proportion = c(90, 10, 0, 0,
                                   30, 50, 20, 0,
                                   10, 25, 35, 30))
mydat$VaccStatus <- factor(mydat$VaccStatus,
                           levels = c("Unvaccinated", "1 dose", "2 doses", "3 doses"))
plotBarGrouped(mydat,
               xvar = "AgeGroup",
               xlabel = "Age (years)",
               yvar = "Proportion",
               ylabel = "Proportion of cases %",
               group = "VaccStatus",
               position = "stack")

Horizontal grouped bar graph

Description

This function draws an horizontal bar graph of the values of variable 'Yvar' with the categorical variable 'Xvar' on the x-axis.
Expects aggregated data.

Usage

plotBarGroupedH(
  .data,
  xvar = "",
  xlabel = "",
  yvar = "",
  ylabel = "",
  group = "",
  fill_color = EcdcColors(col_scale = "qual", n = length(unique(.data[[group]]))),
  log10_scale = FALSE
)

Arguments

See Also

Internal function: EcdcColors
Required Packages: ggplot

Examples

# --- Create dummy data
mydat <- data.frame(Gender=c("F", "F", "M", "M"),
                    AgeGroup = c("0-65", "65+", "0-65", "65+"),
                    NumberOfCases = c(54,43,32,41))

# --- Plot the dummy data
plotBarGroupedH(mydat,
              xvar = "AgeGroup",
              xlabel = "Age",
              yvar = "NumberOfCases",
              ylabel = "Number of cases",
              group = "Gender")

Horizontal bar graph

Description

This function draws an horizontal bar graph of the values of variable 'Yvar' with the categorical variable 'Xvar' on the x-axis.
Expects aggregated data.

Usage

plotBarH(
  .data,
  xvar = "",
  xlabel = "",
  yvar = "",
  ylabel = "",
  fill_color = EcdcColors(col_scale = "qual", n = 1),
  log10_scale = FALSE,
  xlabel_black = ""
)

Arguments

See Also

Internal function: EcdcColors
Required Packages: ggplot

Examples

# --- Create dummy data
mfratio <- data.frame( Country = sample(EpiReport::MSCode$Country, 28),
                       Ratio = runif(28, min = 0, max = 28))

# --- Plot the dummy data
plotBarH(mfratio,
         xvar = "Country",
         xlabel = "",
         yvar = "Ratio",
         ylabel = "Male-to-Female ratio",
         log10_scale = FALSE)
plotBarH(mfratio,
         xvar = "Country",
         xlabel = "",
         yvar = "Ratio",
         ylabel = "Male-to-Female ratio",
         log10_scale = TRUE,
         xlabel_black = "EU-EEA")

Pie chart

Description

This function draws a pie chart of the values of variable 'Xvar' with the labels from the categorical variable 'Labels'.
Expects aggregated data.

Usage

plotPie(
  .data,
  xvar = "",
  labels = "",
  fill_colors = EcdcColors(col_scale = "qual", n = nrow(.data))
)

Arguments

See Also

Internal function: EcdcColors
Required Packages: ggplot

Examples

# --- Create dummy data
piechart <- data.frame(Labels = c("Heterosexual females",
                                  "Heterosexual males",
                                  "MSM",
                                  "Unknow"),
                       Values = c(1633,2937,15342,2854))

# --- Plot the dummy data
plotPie(piechart,
         xvar = "Values",
         labels = "Labels")

Seasonality line graph

Description

This function draws a line graph describing the seasonality of the selected disease over the past 5 years.
The graph includes the distribution of cases, by month, over the past five years, with:

• yvar: The number of cases by month in the reference year (green solid line)

• mean4years: The mean number of cases by month in the four previous years (grey dashed line)

• min4years: The minimum number of cases by month in the four previous years (grey area)

• max4years: The maximum number of cases by month in the four previous years (grey area)

Expects aggregated data and pre-calculated min, max and mean figures.

Usage

plotSeasonality(
  .data,
  xvar = "TimeCode",
  yvar = "N",
  min4years = "Min4Years",
  max4years = "Max4Years",
  mean4years = "Mean4Years",
  year = 2016
)

Arguments

See Also

Global function: getSeason
Required Packages: ggplot

Examples

# --- Plot using external dataset

# Create a dummy dataset
test <- data.frame(Time = as.Date(paste0("2019-",c(1:12), "-01")),
                   N = sample(c(5000:7000), 12),
                   mean = sample(c(4000:5000), 12),
                   low = sample(c(3000:4000), 12),
                   high = sample(c(5000:6000), 12))

# Plot the dummy data
plotSeasonality(test,
                xvar = "Time",
                yvar = "N",
                min4years = "low",
                max4years = "high",
                mean4years = "mean",
                year = 2019)

# --- Please see examples in the vignette
browseVignettes(package = "EpiReport")

# --- Plot using the default dataset
getSeason()

Time series plot

Description

This function draws a time series of the values of variable 'Yvar' with the time variable 'Xvar' on the x-axis.
Expects aggregated data.

Usage

plotTS(
  .data,
  xvar = "",
  xlabel = "",
  yvar = "",
  ylabel = "",
  fill_color = EcdcColors(col_scale = "qual", n = 1),
  log10_scale = FALSE,
  xvar_format = "%Y",
  xvar_breaks = "1 year"
)

Arguments

See Also

Internal function: EcdcColors
Required Packages: ggplot

Examples

# --- Create dummy data
mydat <- data.frame(TimeCode = seq(as.Date("2008/1/1"), as.Date("2017/1/1"), "years"),
                    YValue = sample(1:500/10, 10))

# --- Plot the dummy data
plotTS(mydat,
       xvar = "TimeCode",
       xlabel = "Year",
       yvar = "YValue",
       ylabel = "Rate per 100 000 population",
       log10_scale = FALSE,
       xvar_format = "%Y",
       xvar_breaks = "1 year")

Time series with 12-month moving average

Description

This function draws a line graph describing the trend of the selected disease over the past 5 years.
The graph includes the trend and number of cases at EU/EEA level, by month, over the past five years, with:

• yvar: The number of cases by month over the 5-year period (grey solid line)

• movAverage: The 12-month moving average of the number of cases by month (green solid line)

Expects aggregated data and pre-calculated 12-month moving average.

Usage

plotTS12MAvg(.data, xvar = "TimeCode", yvar = "N", movAverage = "MAV")

Arguments

See Also

Global function: getTrend
Required Packages: ggplot

Examples

# --- Plot using external dataset

# Create a dummy dataset
test <- data.frame(Time = as.Date(paste0("2019-",c(1:12), "-01")),
                   N = sample(c(4000:6000), 12),
                   mean = sample(c(4000:5000), 12))

# Plot the dummy data
plotTS12MAvg(test,
             xvar = "Time",
             yvar = "N",
             movAverage = "mean")

Multiple time series plot

Description

This function draws a time series of the values of variable 'Yvar' with the time variable 'Xvar' on the x-axis. The categorical variable that specify the group of the observations for which there will be one time series each.
Expects aggregated data.

Usage

plotTSGrouped(
  .data,
  xvar = "",
  xlabel = "",
  yvar = "",
  ylabel = "",
  group = "",
  fill_color = EcdcColors(col_scale = "qual", n = length(unique(.data[[group]]))),
  log10_scale = FALSE,
  xvar_format = "%Y",
  xvar_breaks = "1 year"
)

Arguments

See Also

Internal function: EcdcColors
Required Packages: ggplot

Examples

# --- Create dummy data
mydat <- data.frame(TimeCode = seq(as.Date("2008/1/1"), as.Date("2017/1/1"), "years"),
                    YValue = sample(1:79/10, 20),
                    YLabel = rep(c("Acute", "Chronic"), each = 10))

# --- Plot the dummy data
plotTSGrouped(mydat,
              xvar = "TimeCode",
              xlabel = "Year",
              yvar = "YValue",
              ylabel = "Rate per 100 000 population",
              group = "YLabel",
              log10_scale = TRUE,
              xvar_format = "%Y",
              xvar_breaks = "1 year")

# --- Create dummy data
mydat <- data.frame(TimeCode = rep(seq(as.Date("2008/1/1"), as.Date("2017/1/1"), "years"), 5),
                    YValue = c(sample(1:50/10, 10),
                               sample(1:100/10, 10),
                               sample(1:300/10, 10),
                               sample(1:400/10, 10),
                               sample(1:500/10, 10)),
                    YLabel = rep(c("United Kingdom",
                                   "France",
                                   "Spain",
                                   "Netherlands",
                                   "Belgium"), each = 10))

# --- Plot the dummy data
plotTSGrouped(mydat,
              xvar = "TimeCode",
              xlabel = "Year",
              yvar = "YValue",
              ylabel = "Rate per 100 000 population",
              group = "YLabel",
              log10_scale = FALSE,
              xvar_format = "%Y",
              xvar_breaks = "1 year")

Previewing the PNG map

Description

Function previewing the disease-specific PNG map

Usage

previewMap(disease, year, reportParameters, pathPNG, namePNGsuffix)

Arguments

Value

Preview

See Also

Global function: getMap

Shaping the final table (layout, title, color, font)

Description

Shaping the final table including titles, adding background color, specifying font name and size.

Usage

shapeECDCFlexTable(ft, headers, fsize, fname, maincolor, lastbold)

Arguments

Value

flextable object (see flextable package)

See Also

Global function: getTableByMS
Required package: flextable

Capitalise first letter

Description

Capitalise the first letter of a character string in order to use it as title

Usage

toCapTitle(str)

Arguments

Value

character string

Examples

my_title <- "number of salmonellosis cases by age group"
toCapTitle(my_title)