Communication design for health. Territorial and digital networks

In the wake of the Covid-19 pandemic emergency, there has been renewed interest in issues related to health, prevention and community well-being. Health communication and the promotion of disease prevention now require a theoretical and design approach that first and foremost requires the identification of appropriate tools to enhance ‘intersectorality’, ‘collaboration’ and ‘outreach’ among the different areas of expertise of the well-being and healthcare actors involved in the territory. The aim is to strengthen the process of community ‘empowerment’. This study investigates the communicative strategies suitable for enhancing the physical, virtual and digital relationships among the active presences in the territory, choosing those capable of mediating needs, promoting well-being and building a dialogue between citizens and health facilities, thus finally creating a ‘territorial health network’

Architectures and Key Technical Challenges for 5G Systems Incorporating Satellites

Satellite Communication systems are a promising solution to extend and complement terrestrial networks in unserved or under-served areas. This aspect is reflected by recent commercial and standardisation endeavours. In particular, 3GPP recently initiated a Study Item for New Radio-based, i.e., 5G, Non-Terrestrial Networks aimed at deploying satellite systems either as a stand-alone solution or as an integration to terrestrial networks in mobile broadband and machine-type communication scenarios. However, typical satellite channel impairments, as large path losses, delays, and Doppler shifts, pose severe challenges to the realisation of a satellite-based NR network. In this paper, based on the architecture options currently being discussed in the standardisation fora, we discuss and assess the impact of the satellite channel characteristics on the physical and Medium Access Control layers, both in terms of transmitted waveforms and procedures for enhanced Mobile BroadBand (eMBB) and NarrowBand-Internet of Things (NB-IoT) applications. The proposed analysis shows that the main technical challenges are related to the PHY/MAC procedures, in particular Random Access (RA), Timing Advance (TA), and Hybrid Automatic Repeat reQuest (HARQ) and, depending on the considered service and architecture, different solutions are proposed.Comment: Submitted to Transactions on Vehicular Technologies, April 201

Data circulation in health landscapes

This is the final version. Available from Alma DL Journals via the URL in this record. The crossing boundaries intends to open a dialogue between Science and Technology Studies, Social studies of Health and the emerging Data Journalism perspective. It explores major issues at stake in contemporary practices of producing and sharing data, with a focus on the COVID-19 pandemic

Data-Driven Key Performance Indicators and Datasets for Building Energy Flexibility: A Review and Perspectives

Energy flexibility, through short-term demand-side management (DSM) and energy storage technologies, is now seen as a major key to balancing the fluctuating supply in different energy grids with the energy demand of buildings. This is especially important when considering the intermittent nature of ever-growing renewable energy production, as well as the increasing dynamics of electricity demand in buildings. This paper provides a holistic review of (1) data-driven energy flexibility key performance indicators (KPIs) for buildings in the operational phase and (2) open datasets that can be used for testing energy flexibility KPIs. The review identifies a total of 81 data-driven KPIs from 91 recent publications. These KPIs were categorized and analyzed according to their type, complexity, scope, key stakeholders, data requirement, baseline requirement, resolution, and popularity. Moreover, 330 building datasets were collected and evaluated. Of those, 16 were deemed adequate to feature building performing demand response or building-to-grid (B2G) services. The DSM strategy, building scope, grid type, control strategy, needed data features, and usability of these selected 16 datasets were analyzed. This review reveals future opportunities to address limitations in the existing literature: (1) developing new data-driven methodologies to specifically evaluate different energy flexibility strategies and B2G services of existing buildings; (2) developing baseline-free KPIs that could be calculated from easily accessible building sensors and meter data; (3) devoting non-engineering efforts to promote building energy flexibility, such as designing utility programs, standardizing energy flexibility quantification and verification processes; and (4) curating datasets with proper description for energy flexibility assessments.Comment: 30 pages, 14 figures, 4 table

Problem-solving for problem-solving: Data analytics to identify families for service intervention

The article draws on Bacchi’s ideas about problematisation (2020) and links to technological solutionism as governing logics of our age, to explore the double-faceted problem-solving logic operating in the UK family policy and early intervention field. Families with certain characteristics are identified as problematic, and local authorities are tasked with intervening to fix that social problem. Local authorities thus need to identify these families for problem-solving intervention, and data analytics companies will solve that problem for them. In the article, we identify discourses of transmitted deprivation and anti-social behaviour in families and the accompanying costly public sector burden as characteristics that produce families as social problems, and discursive themes around delivering powerful knowledge, timeliness and economic efficiently in data analytic companies’ problem solving claims for their data linkage and predictive analytics systems. These discursive rationales undergird the double-faceted problem-solving for problem-solving logic that directs attention away from complex structural causes

Impact of chronic liver disease upon admission on COVID-19 in-hospital mortality: Findings from COVOCA study

Background Italy has been the first Western country to be heavily affected by the spread of SARS-COV-2 infection and among the pioneers of the clinical management of pandemic. To improve the outcome, identification of patients at the highest risk seems mandatory. Objectives Aim of this study is to identify comorbidities and clinical conditions upon admission associated with in-hospital mortality in several COVID Centers in Campania Region (Italy). Methods COVOCA is a multicentre retrospective observational cohort study, which involved 18 COVID Centers throughout Campania Region, Italy. Data were collected from patients who completed their hospitalization between March-June 2020. The endpoint was in-hospital mortality, assessed either from data at discharge or death certificate, whilst all exposure variables were collected at hospital admission. Results Among 618 COVID-19 hospitalized patients included in the study, 143 in-hospital mortality events were recorded, with a cumulative incidence of about 23%. At multivariable logistic analysis, male sex (OR 2.63, 95%CI 1.42–4.90; p = 0.001), Chronic Liver Disease (OR 5.88, 95%CI 2.39–14.46; p<0.001) and malignancies (OR 2.62, 95%CI 1.21–5.68; p = 0.015) disclosed an independent association with a poor prognosis, Glasgow Coma Scale (GCS) and Respiratory Severity Scale allowed to identify at higher mortality risk. Sensitivity analysis further enhanced these findings. Conclusion Mortality of patients hospitalized for COVID-19 appears strongly affected by both clinical conditions on admission and comorbidities. Originally, we observed a very poor outcome in subjects with a chronic liver disease, alongside with an increase of hepatic damage

Not Just a Pathogen? : Description of a Plant-Beneficial Pseudomonas syringae Strain

Plants develop in a microbe-rich environment and must interact with a plethora of microorganisms, both pathogenic and beneficial. Indeed, such is the case of Pseudomonas, and its model organisms P. fluorescens and P. syringae, a bacterial genus that has received particular attention because of its beneficial effect on plants and its pathogenic strains. The present study aims to compare plant-beneficial and pathogenic strains belonging to the P. syringae species to get new insights into the distinction between the two types of plant-microbe interactions. In assays carried out under greenhouse conditions, P. syringae pv. syringae strain 260-02 was shown to promote plant-growth and to exert biocontrol of P. syringae pv. tomato strain DC3000, against the Botrytis cinerea fungus and the Cymbidium Ringspot Virus. This P. syringae strain also had a distinct volatile emission profile, as well as a different plant-colonization pattern, visualized by confocal microscopy and gfp labeled strains, compared to strain DC3000. Despite the different behavior, the P. syringae strain 260-02 showed great similarity to pathogenic strains at a genomic level. However, genome analyses highlighted a few differences that form the basis for the following hypotheses regarding strain 260-02. P. syringae strain 260-02: (i) possesses nonfunctional virulence genes, like the mangotoxin-producing operon Mbo; (ii) has different regulation pathways, suggested by the difference in the autoinducer system and the lack of a virulence activator gene; (iii) has genes encoding DNA methylases different from those found in other P. syringae strains, suggested by the presence of horizontal-gene-transfer-obtained methylases that could affect gene expression

“A good little tool to get to know yourself a bit better”: a qualitative study on users’ experiences of app-supported menstrual tracking in Europe

Background: Menstrual apps facilitate observation and analysis of menstrual cycles and associated factors through the collection and interpretation of data entered by users. As a subgroup of health-related apps, menstrual apps form part of one of the most dynamic and rapidly growing developments in biomedicine and health care. However, despite their popularity, qualitative research on how people engaging in period-tracking use and experience these apps remains scarce. Results: An inductive content analysis was performed and eight characteristics of app-supported menstrual tracking were identified: 1) tracking menstrual cycle dates and regularities, 2) preparing for upcoming periods, 3) getting to know menstrual cycles and bodies, 4) verifying menstrual experiences and sensations, 5) informing healthcare professionals, 6) tracking health, 7) contraception and seeking pregnancy, and 8) changes in tracking. Our study finds that period-tracking via apps has the potential to be an empowering practice as it helps users to be more aware of their menstrual cycles and health and to gain new knowledge. However, we also show that menstrual tracking can have negative consequences as it leads to distress in some cases, to privacy issues, and the work it requires can result in cessation. Finally, we present practical implications for healthcare providers and app developers. Conclusions: This qualitative study gives insight into users’ practices and experiences of app-supported menstrual tracking. The results provide information for researchers, health care providers and app designers about the implications of app-supported period-tracking and describe opportunities for patient-doctor interactions as well as for further development of menstrual apps.This research has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 675378

A geroscience approach for Parkinson's disease: Conceptual framework and design of PROPAG-AGEING project

Advanced age is the major risk factor for idiopathic Parkinson's disease (PD), but to date the biological relationship between PD and ageing remains elusive. Here we describe the rationale and the design of the H2020 funded project “PROPAG-AGEING”, whose aim is to characterize the contribution of the ageing process to PD development. We summarize current evidences that support the existence of a continuum between ageing and PD and justify the use of a Geroscience approach to study PD. We focus in particular on the role of inflammaging, the chronic, low-grade inflammation characteristic of elderly physiology, which can propagate and transmit both locally and systemically. We then describe PROPAG-AGEING design, which is based on the multi-omic characterization of peripheral samples from clinically characterized drug-naïve and advanced PD, PD discordant twins, healthy controls and "super-controls", i.e. centenarians, who never showed clinical signs of motor disability, and their offspring. Omic results are then validated in a large number of samples, including in vitro models of dopaminergic neurons and healthy siblings of PD patients, who are at higher risk of developing PD, with the final aim of identifying the molecular perturbations that can deviate the trajectories of healthy ageing towards PD development