A network of the involved institutions and stakeholders will be constituted through dedicated agreements, including data sharing. A multidisciplinary team will coordinate pilots and activities within spoke 2 and with the other spokes and will contribute to the activities in WP1 of spoke 1, monitoring selected indicators within the pilots in coordination with spoke 1.
This task will coordinate the deployment of a local advanced second-level IT infrastructure for High-Performance Computing compliant with the standards and interoperability profiles developed in spoke 1. This infrastructure will integrate health, occupational, environmental, and climate data extracted from primary sources and databases. In terms of hardware resources, the infrastructure will integrate a data stream management system for various wearable/IoT/IoMT devices and mobile apps selected/developed together with spoke 1.
A set of services will be developed and delivered for data access and processing: Database services (storage, computation, relational and non-relational DBs), Application Programming Interface for web and mobile application connection, and AI/ML-based services to develop centralized and federated models to highlight any possible or unexpected correlation or association.
The aim is to share views and needs about data management, provision, and organization of services, business models, and funding opportunities. This task will also coordinate communication and dissemination activities.
To develop and enhance advanced digital functions for innovative community-based surveillance, primary prevention, and preparedness response.
The digital infrastructure deployed in WP1 will support an innovative cancer surveillance system based on data-driven models and state-of-the-art ML techniques with advanced functions for:
a) integrating epidemiological data with data from environmental monitoring and occupational settings, health determinants, and lifestyles profiling to improve cancer primary prevention;
b) interoperating population-based registries, specialized clinical registries and biobanks for high-resolution studies;
c) developing advanced models to assess the effectiveness of preventive interventions.
A web-based interoperable platform will be set up to collect and cross-check health data, environmental data, and individual data in order to:
a) study the effects of environmental exposures across the lifespan on health outcomes in different target populations (newborns, children, pregnant women, adults, elderly) using suitable data mining solutions;
b) protect public health and the environment from high-intensity pollution impact, adopting an ‘Assess, WArn & Response’ (AWARE) approach in a coordinated interinstitutional effort;
c) provide preparedness against infectious diseases and surveillance on antibiotic resistance.
An integrated multidisciplinary approach will be used to estimate the individual and cumulative risk of exposure to emerging pollutants from environmental contamination or transfer along the trophic chain. In addition, strategies for safer/healthier management of new-tech tools/products end-life from the green and digital era, and their components, will be developed.
To develop and implement new digital approaches to prevent occupational and environmental risks and promote population health.
A dedicated function of the digital infrastructure deployed in WP1 will be implemented to collect individual data on lifestyles, health determinants, and genomic data for systematic and longitudinal surveillance of communities and specific target populations. Descriptive and predictive models on complex diseases will be developed to study relationships between health outcomes and lifestyles (dietary patterns, physical activity, behaviors, and psychological traits).
The digital infrastructure deployed in WP1 will be expanded to conduct community intervention trials to assess the effectiveness of digital tools used alone or in combination with genomic data for innovative primary prevention paths and personalized approaches.
Senior workers, particularly vulnerable to innovation and transformation induced by Industry 4.0, will be enrolled to study the supportive role of data collection of environmental and wearable sensors and context-aware systems. Data will be analysed by new techniques based on machine and deep learning, to support a better balance of work and life. A similar approach will be adapted to young workers with a low skill level in their first work experience.
The effectiveness of specific programs for primary prevention of gastric, liver, and cervical and oropharyngeal cancers will be assessed within the routine occupational medical surveillance of healthcare workers (HCWs). We will collect data on a) Helicobacter pylori infection and treatment; b) screening of Hepatitis C virus infection and treatment; and c) primary prevention of cervical and oropharyngeal cancers. In addition, programs will be extended to the household members of the recruited HCWs.
To design, implement, and demonstrate how digital tools for primary prevention can support integration and effectiveness between primary and hospital care.
Different monitoring and predictive models will be combined through data analytics techniques and big-data collection into a unique set of statistical tools to detect change points in the trend of daily hospitalizations at different spatiotemporal scales. This approach will also allow the surveillance of environmental exposures related to climate change.
Digital-based innovative paths will be conceived to enhance the territory-hospital collaboration for vaccination programs against specific vaccine-preventable diseases dedicated to the most fragile patients. Innovative approaches will include sharing dedicated paths in a protected setting, computerized booking methods, information social media channels, and AI tools to investigate vaccination hesitancy.
Digital prevention pathways for diabetes and metabolic diseases will be developed and tested, with a focus on improving glycemic control. Digital tools for continuous monitoring and therapeutic education will be included.
Data source mapping and harmonization of clinical and psychological/mental health data from real-world and research-based data sources will be performed, spanning from prenatal through aging life. Requirements and methods for interoperability profiles and standards will be identified in coordination with WP3 in spoke 1.
Mapping and harmonization of additional data sources and extension of the data model to include health-related data, including socioeconomic and environmental data.
Proof of viability studies performed using advanced computational risk stratification analyses and innovative modeling approaches.
Upscaling of data models and platforms for including communities recruited and established cohort consortia.
Sustainability of the established data platforms will be ensured by exploiting the interest of public and private companies in conducting clinical trials and comparative effectiveness studies. Exploitability of the results will be assessed together with WP2 in spoke 1.
Establishing education, research, and career pathways for the sake of spoke 2.
Professional retraining and advanced training courses for the peculiar needs of spoke 2 .
Enhancing and supporting human resources for the peculiar needs of spoke 2 .
To ensure the long-term sustainability of spoke 2 and valorisation/exploitation of research results, positively impacting communities and stakeholders.
Sustainability Management Plan for spoke 2 .
IPR management and exploitation for spoke 2.
Support for entrepreneurship, spin-offs, and start-ups for the sake of spoke 2.
Cascade funding management for the sake of spoke 2.