NetMAHIB publishes original research articles and reviews reporting how graph theory, statistics, linear algebra and machine learning techniques can be effectively used for modelling and analysis in health informatics and bioinformatics. It aims at creating a synergy between these disciplines by providing a forum for disseminating the latest developments and research findings; hence, results can be shared with readers across institutions, governments, researchers, students, and the industry. The journal emphasizes fundamental contributions on new methodologies, discoveries and techniques that have general applicability and which form the basis for network based modelling,  knowledge discovery, knowledge sharing and decision support to the benefit of patients, healthcare professionals and society in traditional and advanced emerging settings, including eHealth and mHealth . Topics covered by NetMAHIB include but are not limited to cutting-edge and novel findings on the latest trends and developments in network modelling and analysis in health informatics and bioinformatics, encompassing areas such as: Clinical and hospital human resource management and performance analysis Metabolic pathway and regulatory network modelling, evolution, simulation, analysis, control and engineering Controlled and optimized utilization of resources Decision support systems for healthcare and wellbeing Models, methods, simulation, evaluation and systems for healthcare services eHealth and mHealth services and interventions Patient tracking, prediction and monitoring, e.g., diagnostics and deterioration detection Spread and control of epidemics Drug design, disease diagnosis and control Signal pathways and cell control Modular biology and systems biology Computational biomedicine, genomics, proteomics, transcriptomics, metabolomics, sociogenomics Social network modelling and analysis in health informatics and bioinformatics Future developments in technologies and applications.