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Analysis of COVID-19 Tracking Tool in India: Case Study of Aarogya Setu Mobile Application

Authors:

Srishti Wadhera,

Vaishnavi VermaAuthors Info & Claims

Digital Government: Research and Practice, Volume 1, Issue 4

Article No.: 28, Pages 1 - 8

https://doi.org/10.1145/3416088

Published: 21 August 2020 Publication History

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Abstract

COVID-19 tracking tools or contact-tracing apps are getting developed at a rapid pace by different governments in their respective countries. This study explores one such tool called Aarogya Setu, developed by the Government of India. It is a mobile application developed under the Health Ministry, as a part of the E-Governance initiative, to track and sensitize the citizens of India in a joint battle against COVID-19 spread. The study aims to understand various useful features of this tool and to present different concepts of data science applied within the application along with its importance in managing the ongoing pandemic. The App uses Bluetooth and GPS technologies to alert a user when they are nearby a COVID-19 infected person. The application uses various Data Science concepts such as Classification, Association Rule Mining, and Clustering to analyze COVID-19 spread in India. The study also shows potential upgradations in the application, which includes usage of Artificial Intelligence and Computer Vision to detect COVID-19 patients. The study would be useful for mobile technology professionals, data science professionals, medical practitioners, health-related frontline workers, public administrators, and government officials.

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Cited By

Da Silva MSantos BRettore PMota V(2024)Privacy-Preserving Contact Tracing System based on a Publish-Subscribe ModelJournal of Internet Services and Applications10.5753/jisa.2024.378115:1Online publication date: 11-Aug-2024
https://doi.org/10.5753/jisa.2024.3781
Comer LDonelle LHiebert BSmith MKothari AStranges SGilliland JLong JBurkell JShelley JHall JShelley JCooke TNgole Dione MFacca D(2024)Short- and Long-Term Predicted and Witnessed Consequences of Digital Surveillance During the COVID-19 Pandemic: Scoping ReviewJMIR Public Health and Surveillance10.2196/4715410(e47154)Online publication date: 24-May-2024
https://doi.org/10.2196/47154
Senarath YMukhopadhyay APurohit HDubey A(2024)Designing a Human-centered AI Tool for Proactive Incident Detection Using Crowdsourced Data Sources to Support Emergency ResponseDigital Government: Research and Practice10.1145/36337845:1(1-19)Online publication date: 12-Mar-2024
https://dl.acm.org/doi/10.1145/3633784
Show More Cited By

Index Terms

Analysis of COVID-19 Tracking Tool in India: Case Study of Aarogya Setu Mobile Application
1. Applied computing
  1. Computers in other domains
    1. Computing in government
      1. E-government
2. Social and professional topics
  1. Computing / technology policy
    1. Surveillance
      1. Governmental surveillance

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Published In

cover image Digital Government: Research and Practice

Digital Government: Research and Practice Volume 1, Issue 4

COVID-19 Commentaries

October 2020

75 pages

EISSN:2639-0175

DOI:10.1145/3411770

Editors:
Soon Ae Chun
City University of New York, USA
,
Beth Simone Noveck
The Governance Lab and New York University, USA

Issue’s Table of Contents

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 August 2020

Accepted: 01 July 2020

Revised: 01 July 2020

Received: 01 June 2020

Published in DGOV Volume 1, Issue 4

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Cited By

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https://doi.org/10.5753/jisa.2024.3781
Comer LDonelle LHiebert BSmith MKothari AStranges SGilliland JLong JBurkell JShelley JHall JShelley JCooke TNgole Dione MFacca D(2024)Short- and Long-Term Predicted and Witnessed Consequences of Digital Surveillance During the COVID-19 Pandemic: Scoping ReviewJMIR Public Health and Surveillance10.2196/4715410(e47154)Online publication date: 24-May-2024
https://doi.org/10.2196/47154
Senarath YMukhopadhyay APurohit HDubey A(2024)Designing a Human-centered AI Tool for Proactive Incident Detection Using Crowdsourced Data Sources to Support Emergency ResponseDigital Government: Research and Practice10.1145/36337845:1(1-19)Online publication date: 12-Mar-2024
https://dl.acm.org/doi/10.1145/3633784
Sheshadri SHara K(2024)Conversational LocalizationProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314047:4(1-32)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631404
Ray AWeaver IAgbozo GKong Y(2024)Mapping Interaction Design in Global Health Interventions: A Comparative Analysis of COVID-19 mHealth TechnologiesIEEE Transactions on Professional Communication10.1109/TPC.2024.338040867:2(173-191)Online publication date: Jun-2024
https://doi.org/10.1109/TPC.2024.3380408
Ramzy M(2024)Knowledge structure and theme trends on mHealth apps for COVID-19: bibliometric analysisAslib Journal of Information Management10.1108/AJIM-08-2024-0657Online publication date: 27-Sep-2024
https://doi.org/10.1108/AJIM-08-2024-0657
Narain M(2024)Practices on Aarogya Setu: Mapping Citizen Interaction with the Contact-Tracing App in the Time of COVID-19East Asian Science, Technology and Society: An International Journal10.1080/18752160.2024.231234218:3(334-354)Online publication date: 12-Mar-2024
https://doi.org/10.1080/18752160.2024.2312342
Huang CGuo BChen JWu Z(2024)Listening to Your Own Willingness to Continue Using Contact Tracing Apps: The Roles of Personal NormsInternational Journal of Human–Computer Interaction10.1080/10447318.2024.2375691(1-22)Online publication date: 15-Jul-2024
https://doi.org/10.1080/10447318.2024.2375691
Mushib SAli I(2024)Clustering endemic places of Covid-19 by using K-mean2ND INTERNATIONAL CONFERENCE FOR ENGINEERING SCIENCES AND INFORMATION TECHNOLOGY (ESIT 2022): ESIT2022 Conference Proceedings10.1063/5.0190479(020002)Online publication date: 2024
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Verma PTripathi VPant B(2024)Implementing Blockchain Technology in the Indian Context to Enable the Secure Exchange of Patients’ Information with Government AgenciesJournal of The Institution of Engineers (India): Series B10.1007/s40031-024-01112-0Online publication date: 12-Jul-2024
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