The limited volume of COVID‐19 data from Africa raises concerns for global genome research, which requires a diversity of genotypes for accurate disease prediction, including on the provenance of the new SARS‐CoV‐2 mutations. The Virus Outbreak Data Network (VODAN)‐Africa studied the possibility of increasing the production of clinical data, finding concerns about data ownership, and the limited use of health data for quality treatment at point of care. To address this, VODAN Africa developed an architecture to record clinical health data and research data collected on the incidence of COVID‐19, producing these as human‐ and machine‐readable data objects in a distributed architecture of locally governed, linked, human‐ and machine‐readable data. This architecture supports analytics at the point of care and—through data visiting, across facilities—for generic analytics. An algorithm was run across FAIR Data Points to visit the distributed data and produce aggregate findings. The FAIR data architecture is deployed in Uganda, Ethiopia, Liberia, Nigeria, Kenya, Somalia, Tanzania, Zimbabwe, and Tunisia.
This study explores the possibility of opening a policy window for the adoption of the FAIR Guidelines – that data be Findable, Accessible, Interoperable, and Reusable (FAIR) – in Uganda's eHealth sector. Although the FAIR Guidelines were not mentioned in any of the policy documents relevant to Uganda's eHealth sector, the study found that 83% of the documents mentioned FAIR Equivalent efforts, such as the adoption of the National Identification Number (NIN) as a unique identifier in Uganda's national Electronic Health Management Information System (eHMIS) (findability), the planned/ongoing integration of various information systems (interoperability), and the alignment of various projects with international best practices/standards (reusability). A FAIR Equivalency Score (FE-Score), devised in this study as an aggregate score of the mention of the equivalent of FAIR facets in the policy documents, showed that the documents at the core of Uganda's digital health/eHealth policy have the highest score of all the documents analysed, indicating that there is a degree of alignment between Uganda's National eHealth Vision and the FAIR Guidelines. Therefore, it can be concluded that favourable conditions exist for the adoption and implementation of the FAIR Guidelines in Uganda's eHealth sector. Hence, it is recommended that the FAIR community adopt a capacity building strategy through organisations with a worldwide mandate, such as the World Health Organization, to promote the adoption of the FAIR Guidelines as part of international best practices.
The incompleteness of patient health data is a threat to the management of COVID-19 in Africa and globally. This has become particularly clear with the recent emergence of new variants of concern. The Virus Outbreak Data Network (VODAN)-Africa has studied the curation of patient health data in selected African countries and identified that health information flows often do not involve the use of health data at the point of care, which renders data production largely meaningless to those producing it. This modus operandi leads to disfranchisement over the control of health data, which is extracted to be processed elsewhere. In response to this problem, VODAN-Africa studied whether or not a design that makes local ownership and repositing of data central to the data curation process would 2 have a greater chance of being adopted. The design team based their work on the legal requirements of the European Union's General Data Protection Regulation (GDPR); the FAIR Guidelines on curating data as Findable, Accessible (under well-defined conditions), Interoperable and Reusable (FAIR); and national regulations applying in the context where the data is produced. The study concluded that the visiting of data curated as machine actionable and reposited in the locale where the data is produced and renders services has great potential for access to a wider variety of data. A condition of such innovation is that the innovation team is intradisciplinary, involving stakeholders and experts from all of the places where the innovation is designed, and employs a methodology of co-creation and capacity-building.
Cyber-attacks on Industrial Control Systems (ICS) are no longer matters of anticipation. Industrial infrastructures are continually being targeted by malicious cyber actors with very little resistance on their paths. From network breaches to data theft, denial of service attacks to privilege escalation; command and control functions have in some way been exerted on targeted industrial systems. Safety, security, resilience, reliability and performance require private industrial control system user organizations and the public sector to device strategies and steps towards dealing decisively to these emerging and increasing ICS cyber security concerns. There are already couple security solutions proposed by governments, private organizations, academia, and industries for achieving this goal. This discourse reviews the ICS security risk landscape, current security strategies and solutions with a view to discovering the gaps or weaknesses in the effective mitigation of cyber-attacks, and the enhancement of cyber security. Notable fissures in existing ICS security solutions include: greater emphasis on technology security while discounting other critical bits like people and processes, which is clearly incongruent with emerging security threats and attack trends, the unilateral dimension strategy towards security which focuses more on SCADA systems, and the emergence of more sector-specific solutions as against generic security solutions. Better solutions include approaches that follow similar evolutionary patterns as the problem trend. These include cyber security measures that would embrace constant evolution in response to changes in the threat, vulnerabilities, attacks, and impact domains. Solutions that recognise and capture; people, process, and technology security enhancement into a single system entity with holistic provisioning that can meet all three-entity vulnerabilities for a more secured ICS environment.
The coronavirus disease of 2019 (COVID-19) is a pandemic that is ravaging Nigeria and the world at large. This data article provides a dataset of daily updates of COVID-19 as reported online by the Nigeria Centre for Disease Control (NCDC) from February 27, 2020 to September 29, 2020. The data were obtained through web scraping from different sources and it includes some economic variables such as the Nigeria budget for each state in 2020, population estimate, healthcare facilities, and the COVID-19 laboratories in Nigeria. The dataset has been processed using the standard of the FAIR data principle which encourages its findability, accessibility, interoperability, and reusability and will be relevant to researchers in different fields such as Data Science, Epidemiology, Earth Modelling, and Health Informatics.
Adopting the FAIR Guidelines – that data should be Findable, Accessible, Interoperable and Reusable (FAIR) – in the health data system in Nigeria will help protect data against use by unauthorised parties, while also making data more accessible to legitimate users. However, little is known about the FAIR Guidelines and their compatibility with data and health laws and policies in Nigeria. This study assesses the governance framework for digital and health/eHealth policies in Nigeria and explores the possibility of a policy window opening for the FAIR Guidelines to be adopted and implemented in Nigeria's eHealth sector. Ten Nigerian policy documents were examined for mention of the FAIR Guidelines (or FAIR Equivalent terminology) and the 15 sub-criteria or facets. The analysis found that although the FAIR Guidelines are not explicitly mentioned, 70% of the documents contain FAIR Equivalent terminology. The Nigeria Data Protection Regulation contained the most FAIR Equivalent principles (73%) and some of the remaining nine documents also contained some FAIR Equivalent principles (between 0–60%). Accordingly, it can be concluded that a policy window is open for the FAIR Guidelines to be adopted and implemented in Nigeria's eHealth sector.
The field of health data management poses unique challenges in relation to data ownership, the privacy of data subjects, and the reusability of data. The FAIR Guidelines have been developed to address these challenges. The Virus Outbreak Data Network (VODAN) architecture builds on these principles, using the European Union's General Data Protection Regulation (GDPR) framework to ensure compliance with local data regulations, while using information knowledge management concepts to further improve data provenance and interoperability. In this article we provide an overview of the terminology used in the field of FAIR data management, with a specific focus on FAIR compliant health information management, as implemented in the VODAN architecture.
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