PUREMIND will deliver the first Integrated Mental Healthcare Ecosystem (IMHE) to predict/early identify Mental Health Disorders (MHD) and create more optimal personalised interventions to prevent MHD and thereby improving wellbeing in children, adolescents, and young adults (0–25 years). The ecosystem will mitigate key challenges associated with MHDs, specifically 1)Detection: 1 in 7 undetected and untreated MHD cases, 2)Efficiency of treatment: lack of tools and guidelines for personalised multidisciplinary interventions that work, 3)Access to Support and Care: long waiting times for care due to lack of trained personnel, 4)Inequality: disparate and inadequate inter- and intra-country mental healthcare services and 5)Modern Cultures and Lifestyle: the increasingly recognised risk factor of digital addiction resulting in sedentary, socially isolated lifestyle contributing to MHD. These will be addressed by PUREMIND’s approach of combining analytical modelling of dynamical systems in the cyber-physical context of a subject’s personal natural environment-gene-gut-brain-MHD interactions process creating a much-needed personalised intervention synthesis framework that will be exploited by an AI engine to deliver optimised personalised intervention, and a unique digital twin educating young people how MHD might develop depending on their environment and lifestyle. These 2 components will be combined in an accessible/ adaptable mobile app MyMind to measure at scale and allow a subject to seamlessly access a 4-tier service architecture involving family, community, clinical and emergency services, to support prediction/early detection of MHD, empowering them to monitor their own mental health at home/educational/community settings and taking preventive actions against MHD. The IMHE will be designed using Implementation Science approach and will be validated in a 12month pilot study in 7 European countries and 2 LMICs covering different socioeconomic and cultural scenarios.

Climate change is one of several drivers of recurrent outbreaks and geographical range expansion of zoonotic infectious diseases in Europe. Policy and decision-makers need tailored monitoring of climate-induced disease risk, and decision-support tools for timely early warning and impact assessment for proactive preparedness and timely responses. The abundance of open data in Europe allows the establishment of more effective, accessible, and cost-beneficial prevention and control responses. IDAlert will co-create novel policy-relevant pan-European indicators that track past, present, and future climate-induced disease risk across hazard, exposure, and vulnerability domains at the animal, human and environment interface. Indicators will be sub-national, and disaggregated through an inequality lens. We will generate tools to assess cost-benefit of climate change adaptation and mitigation measures across sectors and scales, to reveal novel policy entry points and opportunities. Surveillance, early warning and response systems will be co-created and prototyped to increase health system resilience at regional and local levels, and explicitly reduce socio-economic inequality. Indicators and tools will be co-produced through multilevel engagement, innovative methodologies, existing and new data streams and citizen science, taking advantage of intelligence generated from selected hotspots in Spain, Greece, The Netherlands, Sweden, and Bangladesh that are experiencing rapid urban transformation and heterogeneous climate-induced disease threats. For implementation, IDAlert has assembled European authorities in climate modelling, infectious disease epidemiology, social sciences, environmental economics, One Health and EcoHealth. Further, by engaging critical stakeholders from the start, IDAlert will ensure long-lasting impacts on EU climate policy, and provide new evidence and tools for the European Green Deal to strengthen population health resilience to climate change.

Mental illnesses represent a huge burden for society, the economy, and the aMental illnesses represent a huge burden for society, the economy, and the affected individuals. To significantly increase citizens? mental health, today?s symptom-based diagnoses need to be complemented by biological criteria accounting for individual and sex differences. Furthermore, early detection and prevention measures need to be improved. RE-MEND addresses the current gaps and challenges with an interdisciplinary approach by: i) focussing on four critical life stages in which an individual?s susceptibility to mental illness is strongly influenced by changes in endocrine signalling, including sex hormones, namely early life, puberty, peripartum, and transition into old age; ii) integrating data from large population-based longitudinal cohort studies allowing for discovery of risk and protective factors as well as biological patterns that influence mental states in the general population across these life stages; iii) complementing epidemiological with experimental studies to establish correlative and causative links leading to mechanistic understanding; iv) using advanced biostatistics as well as machine learning and artificial intelligence for data integration and biomarker and drug target discovery; v) combining the biological approaches with communication science studies to efficiently translate its results to societal impact. Ultemately, RE-MEND will result in: i) Significantly increased mental health literacy among stakeholders and citizens; ii) Validated biomarkers for assessing mental health state and its predisposition as well as more accurate diagnoses and personalised preventive and therapeutic measures; iii) Recommendations for early detection, better prevention, and drug design strategies to protect vulnerable individuals from mental illness in sensitive life stages; and iv) strategies on how these advances can be used to decrease stigma and increase prevention behaviour.