Digital technologies are being harnessed to support the public-health response to COVID-19 worldwide, including population surveillance, case identification, contact tracing and evaluation of interventions on the basis of mobility data and communication with the public. These rapid responses leverage billions of mobile phones, large online datasets, connected devices, relatively low-cost computing resources and advances in machine learning and natural language processing. This Review aims to capture the breadth of digital innovations for the public-health response to COVID-19 worldwide and their limitations, and barriers to their implementation, including legal, ethical and privacy barriers, as well as organizational and workforce barriers. The future of public health is likely to become increasingly digital, and we review the need for the alignment of international strategies for the regulation, evaluation and use of digital technologies to strengthen pandemic management, and future preparedness for COVID-19 and other infectious diseases. Public-health need Digital tool or technology Example of use Refs. Digital epidemiological surveillance Machine learning Web-based epidemic intelligence tools and online syndromic surveillance Web-based epidemic intelligence tools: 20-23,25 Based on social media or online search data: 30-33 Survey apps and websites Symptom reporting 37,38,48,49 Data extraction and visualization Data dashboard 39-45 Rapid case identification Connected diagnostic device Point-of-care diagnosis 58 Sensors including wearables Febrile symptoms checking 51-53 Machine learning Medical image analysis 65,66

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In the era of 'information overload', effective information provision is essential for enabling rapid response and critical decision making. In making sense of diverse information sources, dashboards have become an indispensable tool, providing fast, effective, adaptable, and personalized access to information for professionals and the general public alike. However, these objectives place heavy requirements on dashboards as information systems in usability and effective design. Understanding these issues is challenging given the absence of consistent and comprehensive approaches to dashboard evaluation. In this paper we systematically review literature on dashboard implementation in healthcare, where dashboards have been employed widely, and where there is widespread interest for improving the current state of the art, and subsequently analyse approaches taken towards evaluation. We draw upon consolidated dashboard literature and our own observations to introduce a general definition of dashboards which is more relevant to current trends, together with seven evaluation scenarios -task performance, behaviour change, interaction workflow, perceived engagement, potential utility, algorithm performance and system implementation. These scenarios distinguish different evaluation purposes which we illustrate through measurements, example studies, and common challenges in evaluation study design. We provide a breakdown of each evaluation scenario, and highlight some of the more subtle questions. We demonstrate the use of the proposed framework by a design study guided by this framework. We conclude by comparing this framework with existing literature, outlining a number of active discussion points and a set of dashboard evaluation best practices for the academic, clinical and software development communities alike.

The COVID-19 pandemic has had a profound impact on the life of our cities. While we have observed major disruption to collective activity, aspects of urban life have continued. In this study, we explore the changed spatiotemporal nature of mobility demand. Through a comparative analysis of New York City taxi records data, we observe how relative demand for taxis has displaced across land use zones and concentrated during daylight hours. We also find changes in payment methods that counter public health advice. These findings point to the fundamental mobility needs during the pandemic.