Using the absolute advantage coefficient (AAC) to measure the strength of damage hit by COVID-19 in India on a growth-share matrix.
Eur J Med Res
; 26(1): 61, 2021 Jun 24.
Article
in English
| MEDLINE | ID: covidwho-1282268
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 7 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.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Algorithms
/
Global Health
/
Models, Statistical
/
SARS-CoV-2
/
COVID-19
Type of study:
Observational study
Limits:
Humans
Country/Region as subject:
Asia
Language:
English
Journal:
Eur J Med Res
Journal subject:
Medicine
Year:
2021
Document Type:
Article
Affiliation country:
S40001-021-00528-4
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