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BackgroundDigital contact tracing apps have the potential to augment contact tracing systems and disrupt COVID-19 transmission by rapidly identifying secondary cases prior to the onset of infectiousness and linking them into a system of quarantine, testing, and health care worker case management. The international experience of digital contact tracing apps during the COVID-19 pandemic demonstrates how challenging their design and deployment are. ObjectiveThis study aims to derive and summarize best practice guidance for the design of the ideal digital contact tracing app. MethodsA collaborative cross-disciplinary approach was used to derive best practice guidance for designing the ideal digital contact tracing app. A search of the indexed and gray literature was conducted to identify articles describing or evaluating digital contact tracing apps. MEDLINE was searched using a combination of free-text terms and Medical Subject Headings search terms. Gray literature sources searched were the World Health Organization Institutional Repository for Information Sharing, the European Centre for Disease Prevention and Control publications library, and Google, including the websites of many health protection authorities. Articles that were acceptable for inclusion in this evidence synthesis were peer-reviewed publications, cohort studies, randomized trials, modeling studies, technical reports, white papers, and media reports related to digital contact tracing. ResultsEthical, user experience, privacy and data protection, technical, clinical and societal, and evaluation considerations were identified from the literature. The ideal digital contact tracing app should be voluntary and should be equitably available and accessible. User engagement could be enhanced by small financial incentives, enabling users to tailor aspects of the app to their particular needs and integrating digital contact tracing apps into the wider public health information campaign. Adherence to the principles of good data protection and privacy by design is important to convince target populations to download and use digital contact tracing apps. Bluetooth Low Energy is recommended for a digital contact tracing app's contact event detection, but combining it with ultrasound technology may improve a digital contact tracing app's accuracy. A decentralized privacy-preserving protocol should be followed to enable digital contact tracing app users to exchange and record temporary contact numbers during contact events. The ideal digital contact tracing app should define and risk-stratify contact events according to proximity, duration of contact, and the infectiousness of the case at the time of contact. Evaluating digital contact tracing apps requires data to quantify app downloads, use among COVID-19 cases, successful contact alert generation, contact alert receivers, contact alert receivers that adhere to quarantine and testing recommendations, and the number of contact alert receivers who subsequently are tested positive for COVID-19. The outcomes of digital contact tracing apps' evaluations should be openly reported to allow for the wider public to review the evaluation of the app. ConclusionsIn conclusion, key considerations and best practice guidance for the design of the ideal digital contact tracing app were derived from the literature.

The emergence of a digital economy has changed companies' business and talent model. However, the gap between supply and demand for digital skills and talent poses a serious dilemma for many companies: do they acquire tech start-ups as a talent strategy or reinvent the company as a tech firm, hire new digital talent and reskill current employees? Recent research on start-up acquisitions and a new report from the US Business-Higher Education Forum and Burning Glass Technologies reframe this dilemma by shedding new light on foundational skills for the digital economy and strategies for acquiring new talent and reskilling employees.

This essay reviews the work of the US Business--Higher Education Forum (BHEF) in data science and analytics and offers a brief review of how BHEF catalysed responses from its academic members to meet the talent needs of its business members, highlighting implications for business and higher education in the future.

Agile development methods have become a standard in the software industry, including in large-scale projects. These methods share a set of underlying assumptions that distinguish them from more traditional plan-driven approaches. In this article, we adopt Alvesson and Sandberg's problematization approach to challenge three key assumptions that are prevalent in the large-scale agile literature: (1) agile and plan-driven methods are mutually exclusive; (2) self-managing and hierarchically organized teams are mutually exclusive; and (3) agile methods can scale through simple linear composition. Using a longitudinal case study of large-scale agile development, we describe a series of trigger events and episodes whereby the agile approach was tailored to address the needs of the large-scale development context, which was very much at odds with these fundamental assumptions. We develop a set of new underlying assumptions which suggest that agile and plan-driven practices are mutually enabling and necessary for coordination and scaling in large-scale agile projects. We develop nine propositions for large-scale agile projects based on these new alternative underlying assumptions. Finally, we summarize our theoretical contribution in a generic process model of continuously adjusting agile and plan-driven practices in order to accommodate process challenges in large-scale agile projects. [ABSTRACT FROM AUTHOR]

BHEF has achieved particular success in operationalizing its National Higher Education and Workforce Initiative (HEWI) through regional initiatives in data science and analytics (DSA). Leveraging its membership of corporate CEOs, university presidents and government agency leaders, BHEF seeded new undergraduate pathways in DSA at Case Western Reserve University in Ohio and Drake University in Iowa. Using BHEF's Strategic Business Engagement Model with higher education, these regional initiatives, as part of HEWI, successfully operationalize BHEF strategies. This article also describes how BHEF, with the support of its partners, has cultivated a community of practice around undergraduate data science for its members and the nation. [This article is the third in an occasional series written for "Industry and Higher Education" by the US Business-Higher Education Forum (BHEF). For the first article in the BHEF Case Study Series, see EJ1042400; for the second article in the BHEF Case Study Series, see EJ1076616. ]