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Background: Pandemic management and preparedness are more needed than ever before and there is widespread governmental interest in learning from the COVID-19 pandemic in order to ensure the availability of evidence-based Infection Prevention and Control measures. Contact tracing is integral to Infection Prevention and Control, facilitating breaks in the chain of transmission in a targeted way, identifying individuals who have come into contact with an infected person, and providing them with instruction/advice relating to testing, medical advice and/or self-isolation., Aim: This study aims to improve our understanding of the use of contact tracing technologies in healthcare settings. This research seeks to contribute to the field of Infection Prevention and Control by investigating how these technologies can mitigate the spread of nosocomial infections. Ultimately, this study aims to improve the quality and safety of healthcare delivery., Methods: A systematic literature review was conducted, and journal articles investigating the use of contact tracing technologies in healthcare settings were retrieved from databases held on the OvidSP platform between March and September 2022, with no date for a lower limit., Results: In total, 277 studies were retrieved and screened, and 14 studies were finally included in the systematic literature review. Most studies investigated proximity sensing technologies, reporting promising results. However, studies were limited by small sample sizes and confounding factors, revealing contact tracing technologies remain at a nascent stage. Investment in research and development of new testing technologies is necessary to strengthen national and international contact tracing capabilities., Conclusion: This review aims to contribute to those who intend to create robust surveillance systems and implement infectious disease reporting protocols.

The use of AI in healthcare has sparked much debate among philosophers, ethicists, regulators and policymakers who raised concerns about the implications of such technologies. The presented scoping review captures the progression of the ethical and legal debate and the proposed ethical frameworks available concerning the use of AI-based medical technologies, capturing key themes across a wide range of medical contexts. The ethical dimensions are synthesised in order to produce a coherent ethical framework for AI-based medical technologies, highlighting how transparency, accountability, confidentiality, autonomy, trust and fairness are the top six recurrent ethical issues. The literature also highlighted how it is essential to increase ethical awareness through interdisciplinary research, such that researchers, AI developers and regulators have the necessary education/competence or networks and tools to ensure proper consideration of ethical matters in the conception and design of new AI technologies and their norms. Interdisciplinarity throughout research, regulation and implementation will help ensure AI-based medical devices are ethical, clinically effective and safe. Achieving these goals will facilitate successful translation of AI into healthcare systems, which currently is lagging behind other sectors, to ensure timely achievement of health benefits to patients and the public.

The COVID-19 pandemic highlighted the scale of global unpreparedness to deal with the fast-arising needs of global health threats. This problem was coupled with a crisis of governance and presented in the context of globally hitting climate crisis and disasters. Although such a pandemic was predictable due to the known effects of human intervention on the surrounding environment and its devastating secondary effects, such as climate change and increased zoonoses, most countries were unprepared to deal with the scale and scope of the pandemic. In this context, such as that of the climate crisis, the Global North and Global South faced several common challenges, including, first and foremost, the scarcity of resources required for health, policy, wellbeing and socioeconomic wellness. In this paper, we review the most recent evidence available in the literature related to pandemic preparedness and governance, focusing on principles and practices used during the COVID-19 pandemic, and we place it in the context of a European Parliament Interest Group meeting (this event took place on 21 March 2023 during the "European Health Tech Summit") to ground it within ongoing discussions and narratives of policy and praxis. The review identified key practices and principles required to better face future health threats and emergencies. Beyond health practices relying on technology and innovation, it is useful to mention the importance of contextualising responses and linking them to clear goals, improving the agreement between science and policymaking, thus building trust and enabling transparent communication with the general public based on clear ethical frameworks.

Introduction: Hypoglycaemia is a harmful potential complication in people with type 1 diabetes mellitus (T1DM) and can be exacerbated in patients receiving treatment, such as insulin therapies, by the very interventions aiming to achieve optimal blood glucose levels. Symptoms can vary greatly, including, but not limited to, trembling, palpitations, sweating, dry mouth, confusion, seizures, coma, brain damage or even death if untreated. A pilot study with healthy (euglycaemic) participants previously demonstrated that hypoglycaemia can be detected non-invasively with artificial intelligence (AI) using physiological signals obtained from wearable sensors. This protocol provides a methodological description of an observational study for obtaining physiological data from people with T1DM. The aim of this work is to further improve the previously developed AI model and validate its performance for glycaemic event detection in people with T1DM. Such a model could be suitable for integrating into a continuous, non-invasive, glucose monitoring system, contributing towards improving surveillance and management of blood glucose for people with diabetes., Methods and Analysis: This observational study aims to recruit 30 patients with T1DM from a diabetes outpatient clinic at the University Hospital Coventry and Warwickshire for a two-phase study. The first phase involves attending an inpatient protocol for up to 36 hours in a calorimetry room under controlled conditions, followed by a phase of free-living, for up to 3 days, in which participants will go about their normal daily activities unrestricted. Throughout the study, the participants will wear wearable sensors to measure and record physiological signals (eg, ECG and continuous glucose monitor). Data collected will be used to develop and validate an AI model using state-of-the-art deep learning methods., Ethics and Dissemination: This study has received ethical approval from National Research Ethics Service (ref: 17/NW/0277). The findings will be disseminated via peer-reviewed journals and presented at scientific conferences., Trial Registration Number: NCT05461144., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: To identify and assess the use of technologies, including mobile health technology, internet of things (IoT) devices and artificial intelligence (AI) in hypertension healthcare in sub-Saharan Africa (SSA)., Design: Systematic review., Data Sources: Medline, Embase, Scopus and Web of Science., Eligibility Criteria: Studies addressing outcomes related to the use of technologies for hypertension healthcare (all points in the healthcare cascade) in SSA., Methods: Databases were searched from inception to 2 August 2021. Screening, data extraction and risk of bias assessment were done in duplicate. Data were extracted on study design, setting, technology(s) employed and outcomes. Blood pressure (BP) reduction due to intervention was extracted from a subset of randomised controlled trials. Methodological quality was assessed using the Mixed Methods Appraisal Tool., Results: 1717 hits were retrieved, 1206 deduplicated studies were screened and 67 full texts were assessed for eligibility. 22 studies were included, all reported on clinical investigations. Two studies were observational, and 20 evaluated technology-based interventions. Outcomes included BP reduction/control, treatment adherence, retention in care, awareness/knowledge of hypertension and completeness of medical records. All studies used mobile technology, three linked with IoT devices. Short Message Service (SMS) was the most popular method of targeting patients (n=6). Moderate BP reduction was achieved in three randomised controlled trials. Patients and healthcare providers reported positive perceptions towards the technologies. No studies using AI were identified., Conclusions: There are a range of successful applications of key enabling technologies in SSA, including BP reduction, increased health knowledge and treatment adherence following targeted mobile technology interventions. There is evidence to support use of mobile technology for hypertension management in SSA. However, current application of technologies is highly heterogeneous and key barriers exist, limiting efficacy and uptake in SSA. More research is needed, addressing objective measures such as BP reduction in robust randomised studies., Prospero Registration Number: CRD42020223043., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Face masks help to limit transmission of infectious diseases entering through the nose and mouth. Beyond reprocessing and decontamination, antimicrobial treatments could extend the lifetime of face masks whilst also further reducing the chance of disease transmission. Here, we review the efficacy of treatments pertaining antimicrobial properties to medical face masks, filtering facepiece respirators and non-medical face masks. Searching databases identified 2113 studies after de-duplication. A total of 17 relevant studies were included in the qualitative synthesis. Risk of bias was found to be moderate or low in all cases. Sixteen articles demonstrated success in avoiding proliferation (if not elimination) of viruses and/or bacteria. In terms of methodology, no two articles employed identical approaches to efficacy testing. Our findings highlight that antimicrobial treatment is a promising route to extending the life and improving the safety of face masks. In order to reach significant achievements, shared and precise methodology and reporting is needed.

The eukaryotic replisome must faithfully replicate DNA and cope with replication fork blocks and stalling, while simultaneously promoting sister chromatid cohesion. Ctf18-RFC is an alternative PCNA loader that links all these processes together by an unknown mechanism. Here, we use integrative structural biology combined with yeast genetics and biochemistry to highlight the specific functions that Ctf18-RFC plays within the leading strand machinery via an interaction with the catalytic domain of DNA Pol ϵ. We show that a large and unusually flexible interface enables this interaction to occur constitutively throughout the cell cycle and regardless of whether forks are replicating or stalled. We reveal that, by being anchored to the leading strand polymerase, Ctf18-RFC can rapidly signal fork stalling to activate the S phase checkpoint. Moreover, we demonstrate that, independently of checkpoint signaling or chromosome cohesion, Ctf18-RFC functions in parallel to Chl1 and Mrc1 to protect replication forks and cell viability., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)