UPM Institutional Repository

The role of big data analytics in digital health for COVID-19 prevention and control in Asia


Citation

Azmi, Nazmi Ainaa and Mohd Noor, Norhafizah and Mud Shukri, Muhammad Ikhwan and Mahmud, Aidalina and Abdul Manaf, Rosliza (2022) The role of big data analytics in digital health for COVID-19 prevention and control in Asia. Malaysian Journal of Medicine and Health Sciences, 18 (4). pp. 173-181. ISSN 2636-9346

Abstract

Big data analytics (BDA) in digital health is critical for gaining the knowledge needed to make decisions, with Asia at the forefront of utilising this technology for the Coronavirus disease 2019 (COVID-19). This review aims to study how BDA was incorporated into digital health in managing the COVID-19 pandemic in six selected Asian countries, discuss its advantages and barriers and recommend measures to improve its adoption. A narrative review was conducted. Online databases were searched to identify all relevant literature on the roles of BDA in digital health for COVID-19 preventive and control measures. The findings showed that these countries had used BDA for contact tracing, quarantine compliance, outbreak prediction, supply rationing, movement control, information update, and symptom monitoring. Compared to conventional approaches, BDA in digital health plays a more efficient role in preventing and controlling COVID-19. It may inspire other countries to adopt this technology in managing the pandemic.


Download File

[img] Text
2022071815345624_MJMHS_1300.pdf

Download (133kB)

Additional Metadata

Item Type: Article
Divisions: Faculty of Medicine and Health Science
DOI Number: https://doi.org/10.47836/mjmhs18.4.24
Publisher: Faculty of Medicine and Health Sciences, Universiti Putra Malaysia
Keywords: Big data analytics; Digital health; COVID-19; Asia
Depositing User: Mohamad Jefri Mohamed Fauzi
Date Deposited: 22 Nov 2022 07:02
Last Modified: 22 Nov 2022 07:02
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.47836/mjmhs18.4.24
URI: http://psasir.upm.edu.my/id/eprint/98689
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item