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) develo...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-06-01
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| Series: | European Journal of Medical Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40001-021-00528-4 |
| _version_ | 1819001344824967168 |
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| author | Daw-Hsin Yang Tsair-Wei Chien Yu-Tsen Yeh Ting-Ya Yang Willy Chou Ju-Kuo Lin |
| author_facet | Daw-Hsin Yang Tsair-Wei Chien Yu-Tsen Yeh Ting-Ya Yang Willy Chou Ju-Kuo Lin |
| author_sort | Daw-Hsin Yang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T22:47:44Z |
| format | Article |
| id | doaj.art-bacc7f44b1a34b8e8cd208f94584d6cc |
| institution | Directory Open Access Journal |
| issn | 2047-783X |
| language | English |
| last_indexed | 2024-12-20T22:47:44Z |
| publishDate | 2021-06-01 |
| publisher | BMC |
| record_format | Article |
| series | European Journal of Medical Research |
| spelling | doaj.art-bacc7f44b1a34b8e8cd208f94584d6cc2022-12-21T19:24:19ZengBMCEuropean Journal of Medical Research2047-783X2021-06-0126111110.1186/s40001-021-00528-4Using the absolute advantage coefficient (AAC) to measure the strength of damage hit by COVID-19 in India on a growth-share matrixDaw-Hsin Yang0Tsair-Wei Chien1Yu-Tsen Yeh2Ting-Ya Yang3Willy Chou4Ju-Kuo Lin5Department of Gastrointestinal Hepatobiliary, Chiali Chi-Mei HospitalDepartment of Medical Research, Chi-Mei Medical CenterMedical School, St. George’s University of LondonMedical Education Center, Chi-Mei Medical CenterDepartment of Physical Medicine and RehabilitationDepartment of Medical Research, Chi-Mei Medical CenterAbstract 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.https://doi.org/10.1186/s40001-021-00528-4Four-quadrant diagramCOVID-19Multiply infection rateDashboardGoogle maps |
| spellingShingle | Daw-Hsin Yang Tsair-Wei Chien Yu-Tsen Yeh Ting-Ya Yang Willy Chou Ju-Kuo Lin Using the absolute advantage coefficient (AAC) to measure the strength of damage hit by COVID-19 in India on a growth-share matrix European Journal of Medical Research Four-quadrant diagram COVID-19 Multiply infection rate Dashboard Google maps |
| title | Using the absolute advantage coefficient (AAC) to measure the strength of damage hit by COVID-19 in India on a growth-share matrix |
| title_full | Using the absolute advantage coefficient (AAC) to measure the strength of damage hit by COVID-19 in India on a growth-share matrix |
| title_fullStr | Using the absolute advantage coefficient (AAC) to measure the strength of damage hit by COVID-19 in India on a growth-share matrix |
| title_full_unstemmed | Using the absolute advantage coefficient (AAC) to measure the strength of damage hit by COVID-19 in India on a growth-share matrix |
| title_short | Using the absolute advantage coefficient (AAC) to measure the strength of damage hit by COVID-19 in India on a growth-share matrix |
| title_sort | using the absolute advantage coefficient aac to measure the strength of damage hit by covid 19 in india on a growth share matrix |
| topic | Four-quadrant diagram COVID-19 Multiply infection rate Dashboard Google maps |
| url | https://doi.org/10.1186/s40001-021-00528-4 |
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