This presentation introduces an interactive Shiny application designed to explore global COVID-19 trends.

Data were taken from WHO Statistical Release, which can be accessed here: https://data.who.int/dashboards/covid19/data

Features

• Cumulative cases and deaths visualization
• Country and WHO region filtering
• Time-based analysis
• Interactive Plotly graphs

• Select time range using date filter
• Switch between Country and WHO Region view
• View cumulative cases and deaths
• Interactive tooltips using Plotly
• Customize plot appearance (titles, axes)

RPubs Shiny App

The Shiny App can be accessed here: https://ryd8803.shinyapps.io/COVID19_Dashboard_DataReport/

GitHub can be accessed here: https://github.com/RYD8803/coviddatadashboard

We want to plot the number of cumulative cases for Indonesia, Malaysia, and Singapore in 2020 - 2022

Start date = 2020-01-04

End date = 2022-12-31

library(plotly)
country_select <- c("Indonesia", "Malaysia", "Singapore")
date_range <- c("2020-01-04", "2022-12-31")

#Filter the date and country
datacountry <- coviddata[coviddata$Country %in% country_select, ]
data <- datacountry[datacountry$Date_reported >= date_range[1] & datacountry$Date_reported <= date_range[2], ]

#Plot with plot_ly            
p <- plot_ly(data, x = ~Date_reported, y = ~Cumulative_cases, mode = "lines+markers", type = "scatter", color = ~Country, 
        text = ~paste("Country:", Country, "(", Country_code, ")", "<br>WHO Region:", WHO_region, 
        "<br>New cases:", New_cases, "<br>Cumulative cases:", Cumulative_cases), hoverinfo = "text")

p