Interactive COVID-19 Dashboard: Case Trends, Vaccination Progress & Forecasting Using R

Abstract

The COVID-19 pandemic has highlighted the importance of data monitoring, visualization, and forecasting in supporting public health awareness and decision-making. This study presents an interactive COVID-19 dashboard developed using R to analyses confirmed cases, deaths, and vaccination progress across different countries and regions. Publicly available datasets from Our World in Data (OWID) were used for data preprocessing, exploratory analysis, and visualization. R packages, including tidyverse, ggplot2, plotly, and shiny, were used to develop interactive charts and a user-friendly dashboard. Time-series forecasting was performed using the Autoregressive Integrated Moving Average (ARIMA) model to generate short-term predictions of COVID-19 case trends. The dashboard enables users to explore historical patterns, compare vaccination progress, and examine forecasting results through interactive visualizations. The proposed system demonstrates the application of R-based data analytics and predictive modelling to improve the accessibility and interpretation of public health information.Keywords: peacekeeping education; higher education strategy; DEMATEL; analytic network process; mixed methods; defence diplomacy; Indonesia