Search

Background: The use of big data in public health will facilitate more specialised, targeted research and clinical trials that will help stratify and separate groups of people who are at risk for various health issues. During the recent COVID-19 pandemic, big data was used to store enormous information about COVID-19 patients, which was used to identify cases and allocate public health resources appropriately. This also allowed scientists, health workers, and epidemiologists to make informed decisions and inspire medical innovation. Objectives: This scoping systematic review aimed to systematically describe the application of big data analytics in contact tracing for covid-19 surveillance. Materials and Methods: A systematic search was conducted in Scopus, ScienceDirect and EBSCOhost following Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) guidelines, from November until December 2022. The following keywords were used for searching related articles: “big data analytic” AND “contact tracing” OR “closed contact*” AND “Covid19” OR “SARS-CoV2” AND “surveillance”. All included original articles were published in English from the year 2020 until 2022 were imported into EndNote20 for further storage, organization and review processes. Result: Upon rigorous searching and screening, a total of seven studies met the inclusion and exclusion criteria: 3 eligible articles were from China, 1 from Taiwan, 1 from Saudi Arabia, 1 from the United States, and 1 from Italy. Types of big data are digital technology using mobile apps and mobile Geo positioning, spatial-temporal GPS information, earth cognitive system satellites data and visualization tool data-driven documents. Conclusion: Big Data Analysis is essential because it can process and analyse large amounts of data quickly, allowing rapid reactions and timely solutions. Compared to traditional methods, it plays a substantial and effective role in the prevention and management of COVID-19. This analysis shows that this technology is a useful tool for contact tracing, breaking the chain of transmission, and guaranteeing quarantine compliance. [ABSTRACT FROM AUTHOR]

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]

Background: Health insurance is the primary mechanism that enables people to obtain health care services. There are three major types of health insurance involves private health insurance, social health insurance and community-based health insurance. Aims: This systematic review aims to identify the implication on equity after implementation of health insurance focusing on selected Asian countries. The review is based on the three dimensions of universal health coverage (UHC): population coverage, and service coverage and financial coverage. Materials and methods: A systematic search for articles was conducted form 4 search engines, Scopus, Science Direct, Proquest, and Google scholar. A total of 13 articles were selected after screenings and equity implications were concluded in three UHC dimensions based on equity index reported or equity improvement observed in time series studied. Result and discussion: All the three health insurance has different implication on equity between countries or within country. In terms of population coverage, SHI in Thailand showed an equitable coverage. Philippine also reported to have equitable population coverage in terms of geographical while in Vietnam, CBHI showed inequitable population coverage. The financial coverage has showed an inequity of CBHI in India, China, and Thailand. The inequity was also observed for SHI in Philippine, Vietnam and Philippines. More apparent is inequity in PHI for Malaysia and Philippines. The only equitable financial coverage reported was Thailand for its SHI. The final aspect is on service delivery coverage with equity has been observed in CBHI in China and SHI in Vietnam and Thailand. Conclusion: Social health insurance schemes can be further improved in addressing equity in all UHC aspects. CBHI of which showed some equitable measures for certain population subgroups, such as the poor, and formal workers can collectively be the way to go for SHI. [ABSTRACT FROM AUTHOR]