Using the Absolute Advantage Coefficient(AAC) to Measure the Strength of Damage Hit by COVID-19 in India on a Growth-Share Matrix

Abstract

Background: The COVID-19 pandemic occurred and rapidly spread around the world. Some online dashboards have included essential features on a world map. However, only transforming data into visualizations for countries/regions is insufficient for the public need. This study aims to (1) develop an algorithm for classifying countries/regions into four quadrants inn GSM and (2) design an app for a better understanding of the COVID-19 situation.Methods: We downloaded COVID-19 outbreak numbers daily from the Github website, including 189 countries/regions. A four-quadrant diagram was applied to present the classification of each country/region using Google Maps run on dashboards. A novel presentation scheme was used to identify the most struck entities by observing (1) the multiply infection rate(MIR) and (2) the growth trend in the recent seven days. Four clusters of the COVID-19 outbreak were dynamically classified. An app based on a dashboard aimed at public understanding of the outbreak types and visualizing of the COVID-19 pandemic with Google Maps run on dashboards. The absolute advantage coefficient(AAC) was used to measure the damage hit by COVID-19 referred to the next two countries severely hit by COVID-19.Results: We found that the two hypotheses were supported: India (i) is in the increasing status as of April 28, 2021, (ii) has a substantially higher ACC(=0.81>0.70), and (iii) has a substantially higher ACC(=0.66<0.70) as of May 17,2021. Conclusion: Four clusters of the COVID-19 outbreak were dynamically classified online on an app making the public understand the outbreak types of COVID-19 pandemic shown on dashboards. The app with GSM and AAC is recommended for researchers in other disease outbreaks, not just limited to COVID-19.