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DIGITAL CONTACT TRACING (DCT) IN COVID-19 DISEASE MANAGEMENT DURING EARLY PANDEMIC IN MALAYSIA, NEW ZEALAND AND CHINA.
- Source :
- International Journal of Public Health & Clinical Sciences (IJPHCS); 2022, Vol. 9 Issue 3, p1-18, 18p
- Publication Year :
- 2022
-
Abstract
- Background: Digital contact tracing (DCT) is a method of tracing contact relying on tracking systems using artificial intelligence (AI) as an epidemic prevention solution for the COVID-19 pandemic. This review compares the DCT systems such as Bluetooth, Quick Response (QR) code, Global Positioning System (GPS) or Radio Frequency Identification (RFID) technologies that are used in Malaysia, New Zealand and China during early COVID-19 pandemic. Materials and Methods: A review was conducted based on the multiple data sources from existing electronic articles, newspapers, press releases, government documents, reports and web pages that are available online. Result: There are five mobile applications and one Bluetooth device in used by these countries; Malaysia uses MySejahtera app and MyTrace app, New Zealand uses NZ Covid Trace and Bluetooth COVIDCard and China uses a Health Code app that is available in WeChat and Alipay. All apps are available in Apple store, Google Play and App Gallery, except the NZ COVID tracer is not supported by the App Gallery. All 3 countries utilise the QR code as the main DCT with additional features in a centralised data architecture framework. Based on other available databases; MySejahtera has recorded around 74.9% users in Malaysia as at December 2020, NZ CovidTrace logged around 55.1% as at 19th April 2021, and Alipay tracked around 64.3% as at early 2021. . Conclusion: Effective human resources management with digitalisation is crucial in managing pandemics with multi-approach public health interventions which could enhance public health outcomes with less public rejection. Integration of DCT during pandemic is advantageous and valuable for successful disease control. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 22897577
- Volume :
- 9
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- International Journal of Public Health & Clinical Sciences (IJPHCS)
- Publication Type :
- Academic Journal
- Accession number :
- 158169153