Big Data Visualization and Visual Analytics of COVID-19 Data

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The challenge of privacy and security when using technology to track people in times of COVID-19 pandemic

Since the start of the Coronavirus disease 2019 (COVID-19) governments and health authorities across the world have find it very difficult in controlling infections. Digital technologies such as artificial intelligence (AI), big data, cloud computing, blockchain and 5G have effectively improved the efficiency of efforts in epidemic monitoring, virus tracking, prevention, control and treatment. Surveillance to halt COVID-19 has raised privacy concerns, as many governments are willing to overlook privacy implications to save lives. The purpose of this paper is to conduct a focused Systematic Literature Review (SLR), to explore the potential benefits and implications of using digital technologies such as AI, big data and cloud to track COVID-19 amongst people in different societies. The aim is to highlight the risks of security and privacy to personal data when using technology to track COVID-19 in societies and identify ways to govern these risks. The paper uses the SLR approach to examine 40 articles published during 2020, ultimately down selecting to the most relevant 24 studies. In this SLR approach we adopted the following steps; formulated the problem, searched the literature, gathered information from studies, evaluated the quality of studies, analysed and integrated the outcomes of studies while concluding by interpreting the evidence and presenting the results. Papers were classified into different categories such as technology use, impact on society and governance. The study highlighted the challenge for government to balance the need of what is good for public health versus individual privacy and freedoms. The findings revealed that although the use of technology help governments and health agencies reduce the spread of the COVID-19 virus, government surveillance to halt has sparked privacy concerns. We suggest some requirements for government policy to be ethical and capable of commanding the trust of the public and present some research questions for future research

Big Data Analytics for Integrated Infectious Disease Surveillance in sub-Saharan Africa

Background: Infectious disease outbreaks are common in sub-Saharan Africa (SSA). Consequently, integrated public health surveillance has become increasingly essential for the region. Health surveillance systems enable early detection and monitoring of emerging and re-emerging disease outbreaks, thus informing preparedness and response measures. However, complex and intertwined factors obstruct a successful integrated public health surveillance in SSA, with dire consequences. Objectives: The objective of this article was to establish how big data analytics can be used to enhance integrated infectious disease surveillance and response in SSA. Method: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was used to identify and select relevant articles. A total of 10 studies that addressed the article’s objective were selected. Results: Findings reveal several barriers to the application of big data analytics for public health surveillance in SSA. These include the absence of regulatory and data governance frameworks for big data management in healthcare, disparities in digital health infrastructure across SSA’s healthcare systems, and the digital and analytical skills required for data capture and interpretation. The development of regulatory frameworks is essential for the ethical application of analytical technologies such as artificial intelligence. Conclusion: This article’s contributions emphasise the need for comprehensive strategies for the application of big data analytics for public health surveillance, as well as addressing barriers to its successful application by highlighting the requirements for an integrated infectious disease surveillance and response system in SSA. Contribution: The article contributes to the body of knowledge on the interplay between the public health space and digital health interventions by emphasising the beneficial applications of big data analytics for surveillance and response to address emerging and re-emerging infectious disease outbreaks in the health systems of sub-Saharan Africa