Global Examples of COVID-19 Surveillance Technologies : Flash Report

The fast spread of coronavirus (COVID-19) around the world has put health services under an enormous strain. Turning to digital means for collating data on the spread of the virus, the associated symptoms, as well as the routes through which it may be spreading has been a common response. The situation, the associated technologies and the practices of their use vary across the globe and evolve rapidly. This report provides a global snapshot of the different types of technologies in use or in development for surveillance of COVID-19 at the beginning of April 2020. By the time this report is published, the situation will have developed further. The body of the report presents short descriptions of a selection of different apps from around the world. More detailed data tables are in Appendix 1 and include references used

Do we need a Contact Tracing App?

The goal of this paper is to shed some light on the usefulness of a contact tracing smartphone app for the containment of the COVID-19 pandemic. We review the basics of contact tracing during the spread of a virus, we contextualize the numbers to the case of COVID-19 and we analyse the state of the art for proximity detection using Bluetooth Low Energy. Our contribution is to assess if there is scientific evidence of the benefit of a contact tracing app in slowing down the spread of the virus using present technologies. Our conclusion is that such evidence is lacking, and we should re-think the introduction of such a privacy-invasive measure

Use Of Participatory Apps In Contact Tracing: Options And Implications for Public Health, Privacy and Trust

On December 31st, 2019, the World Health Organisation received a report from the Chinese government detailing a cluster of cases of ‘pneumonia of unknown origin’, later identified as novel coronavirus. The virus, now referred to as COVID-19, quickly spread and was officially declared a global pandemic on March 11th. COVID-19 has put health services under enormous strain globally. Turning to digital methods for collating data on cases, associated symptoms and the routes through which the virus may be spreading has been a common response. Human-powered contact tracing, although resource-intensive, is still considered to be the most effective way of tracking and helping to curtail the spread of infectious diseasesi. Intense efforts are underway to develop digital tools that can augment and automate some of these processes, such as the NHSX app or Singapore’s TraceTogether app, however, these are often beset with technical and privacy-related issues. This report reviews digital approaches that involve citizens as co-actors in efforts to support contact tracing, which may include elements of both location/proximity monitoring and symptom reporting, the latter representing a type of crowdsourced disease surveillance.ii This is approached from the perspectives of public health data needs, privacy-centred architectures, technologies and standards, and digital ethics. The aim is to inform an approach to digital contact tracing that is consistent with Scottish policy around secure, transparent, participatory and privacy-respectful data sharing for health and wellbeing. As such, some of the insights and recommendations are applicable to broader aspects of digital health in Scotland. The report collates expert answers to the following questions: • What are the desirable outcomes arising from the automation of symptom and contact tracing data collection at scale? (Prof Jill Pell, Institute of Health and Wellbeing, University of Glasgow); • How might the distributed system be architected to be secure and respectful of privacy from the outset? (Prof Bill Buchanan, OBE, School of Computing, University of Napier); • What communications standards and methods would best support the approach? (Prof Muhammad Imran, James Watt School of Engineering, University of Glasgow); • What are the ethical challenges and what steps should Scottish Government take to secure public trust? (Prof Claudia Pagliari, Usher Institute, University of Edinburgh

PIVOT:Private and effective contact tracing

We propose, design, and evaluate PIVOT, a privacy-enhancing and effective contact tracing solution that aims to strike a balance between utility and privacy: one that does not collect sensitive information yet allowing effective tracing and notifying the close contacts of diagnosed users. PIVOT requires a considerably lower degree of trust in the entities involved compared to centralised alternatives while retaining the necessary utility. To protect users\u27 privacy, it uses local proximity tracing based on broadcasting and recording constantly changing anonymous public keys via short-range communication. These public keys are used to establish a shared secret key between two people in close contact. The three keys (i.e., the two public keys and the established shared key) are then used to generate two unique per-user-per-contact hashes: one for infection registration and one for exposure score query. These hashes are never revealed to the public. To improve utility, user exposure score computation is performed centrally, which provides health authorities with minimal, yet insightful and actionable data. Data minimisation is achieved by the use of per-user-per-contact hashes and by enforcing role separation: the health authority act as a mixing node, while the matching between reported and queried hashes is outsourced to a third entity, an independent matching service. This separation ensures that out-of-scope information, such as users\u27 social interactions, is hidden from the health authorities, whereas the matching service does not learn users\u27 sensitive information. To sustain our claims, we conduct a practical evaluation that encompasses anonymity guarantees and energy requirements

Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey

Until a safe and effective vaccine to fight the SARS-CoV-2 virus is developed and available for the global population, preventive measures, such as wearable tracking and monitoring systems supported by Internet of Things (IoT) infrastructures, are valuable tools for containing the pandemic. In this review paper we analyze innovative wearable systems for limiting the virus spread, early detection of the first symptoms of the coronavirus disease COVID-19 infection, and remote monitoring of the health conditions of infected patients during the quarantine. The attention is focused on systems allowing quick user screening through ready-to-use hardware and software components. Such sensor-based systems monitor the principal vital signs, detect symptoms related to COVID-19 early, and alert patients and medical staff. Novel wearable devices for complying with social distancing rules and limiting interpersonal contagion (such as smart masks) are investigated and analyzed. In addition, an overview of implantable devices for monitoring the effects of COVID-19 on the cardiovascular system is presented. Then we report an overview of tracing strategies and technologies for containing the COVID-19 pandemic based on IoT technologies, wearable devices, and cloud computing. In detail, we demonstrate the potential of radio frequency based signal technology, including Bluetooth Low Energy (BLE), Wi-Fi, and radio frequency identification (RFID), often combined with Apps and cloud technology. Finally, critical analysis and comparisons of the different discussed solutions are presented, highlighting their potential and providing new insights for developing innovative tools for facing future pandemics