It has been two years since I started to develop various interactive web applications by using R-Shiny packages. Due to Coronavirus disease (COVID-19) at this moment, I spent some time at home on preparing a simple COVID-19 related Dashboard. To share my experiences and consideration, especially those about how to create interactive maps, the following details has been discussed.

Data Source 

Dataset (data/key-countries-pivoted.csv) from Github (https://github.com/datasets/covid-19), which contains the data of daily confirmed cases of COVID-19 since 22th Jan 2020 from the eight most rapidly-spread countries (China, USA, United Kingdom, Italy, France, Germany, Spain and Iran), has been used. An example of overview of the dataset is given as follows:
In addition, the geographic coordinates (Latitude and Longitude) of the centroids of these countries have been collected for placing charts in the leaflet map.

R Shiny: Introduction 

 library(shiny)
 library(leaflet.minicharts)
 library(leaflet)

In the lower block, we are able to visualize the time dependent development of confirmed cases for a selected country and time history.  The classical layout sideBarLayout, which consists of a sidebar (sidebarPanel()) and the main area (mainPanel()), is used. Moreover, a checkbox is provided to select whether plotting the daily new confirmed cases is desired.


The R code for UI is given as follows:

 ui<- fluidPage(
   #Assign Dasbhoard title 
   titlePanel("COVID19 Analytics"),
  
  # Start:  the First Block
  # Sliderinput: select from the date between 01.20.2020 
  # and 01.04.2020
  sliderInput(inputId = "date", "Date:", min = 
  as.Date("2020-01-20"), max = as.Date("2020-04-01"), 
  value = as.Date("2020-03-01"), width = "600px"),
    
  # plot leaflet object (map) 
  leafletOutput(outputId = "distPlot", width = "700px", 
  height = "300px"),
  #End:  the First Block
  
  #Start: the second Block
  sidebarLayout(
    
    #Sidebar Panel: the selected country, history and 
    #whether to plot daily new confirmed cases.
    sidebarPanel(
      selectInput("selectedcountry", h4("Country"), choices 
      =list("China","US","United_Kingdom","Italy","France",
      "Germany", "Spain"), selected = "US"),
      selectInput("selectedhistoricwindow", h4("History"), 
      choices = list("the past 10 days", "the past 20 
      days"), selected = "the past 10 days"),
      checkboxInput("dailynew", "Daily new infected", 
      value = TRUE),
      width = 3  
    ),
    
    #Main Panel: plot the selected values
    mainPanel (
      plotOutput(outputId = "Plotcountry", width = "500px", 
      height = "300px")
    )
  ),
  #End: the second Block 
)

server <- function(input, output){
  
  #Assign output$distPlot with renderLeaflet object
  output$distPlot <- renderLeaflet({
  
    # row index of the selected date (from input$date)
    rowindex = which(as.Date(as.character(daten$Date), 
    "%d.%m.%Y") ==input$date)
    
    # initialise the leaflet object
    basemap= leaflet()  %>%
      addProviderTiles(providers$Stamen.TonerLite,
      options = providerTileOptions(noWrap = TRUE)) 
    
    # assign the chart colors for each country, where those 
    # countries with more than 500,000 cases are marked 
    # as red, otherwise black
    chartcolors = rep("black",7)
    stresscountries 
    = which(as.numeric(daten[rowindex,c(2:8)])>50000)
    chartcolors[stresscountries] 
    = rep("red", length(stresscountries))
    
    # add chart for each country according to the number of 
    # confirmed cases to selected date 
    # and the above assigned colors
    basemap %>%
      addMinicharts(
        citydaten$long, citydaten$Lat,
        chartdata = as.numeric(daten[rowindex,c(2:8)]),
        showLabels = TRUE,
        fillColor = chartcolors,
        labelMinSize = 5,
        width = 45,
        transitionTime = 1
      ) 
  })
  
  #Assign output$Plotcountry with renderPlot object
  output$Plotcountry <- renderPlot({
    
    #the selected country 
    chosencountry = input$selectedcountry
    
    #assign actual date
    today = as.Date("2020/04/02")
    
    #size of the selected historic window
    chosenwindow = input$selectedhistoricwindow
    if (chosenwindow == "the past 10 days")
       {pastdays = 10}
    if (chosenwindow  == "the past 20 days")
       {pastdays = 20}
    
    #assign the dates of the selected historic window
    startday = today-pastdays-1
    daten$Date=as.Date(as.character(daten$Date),"%d.%m.%Y")
    selecteddata 
    = daten[(daten$Date>startday)&(daten$Date<(today+1)), 
    c("Date",chosencountry)]
    
    #assign the upperbound of the y-aches (maximum+100)
    upperboundylim = max(selecteddata[,2])+100
    
    #the case if the daily new confirmed cases are also
    #plotted
    if (input$dailynew == TRUE){
    
      plot(selecteddata$Date, selecteddata[,2], type = "b", 
      col = "blue", xlab = "Date", 
      ylab = "number of infected people", lwd = 3, 
      ylim = c(0, upperboundylim))
      par(new = TRUE)
      plot(selecteddata$Date, c(0, diff(selecteddata[,2])), 
      type = "b", col = "red", xlab = "", ylab = 
      "", lwd = 3,ylim = c(0,upperboundylim))
      
      #add legend
      legend(selecteddata$Date[1], upperboundylim*0.95, 
      legend=c("Daily new", "Total number"), 
      col=c("red", "blue"), lty = c(1,1), cex=1)
    }
    
    #the case if the daily new confirmed cases are 
    #not plotted
    if (input$dailynew == FALSE){
      
      plot(selecteddata$Date, selecteddata[,2], type = "b", 
      col = "blue", xlab = "Date", 
      ylab = "number of infected people", lwd = 3,
      ylim = c(0, upperboundylim))
      par(new = TRUE)
      
      #add legend
      legend(selecteddata$Date[1], upperboundylim*0.95, 
      legend=c("Total number"), col=c("blue"), 
      lty = c(1), cex=1)
    }
    
  })
    
} 

 shinyApp(ui = ui, server = server)