The rapid global spread of infectious diseases, epitomized by the recent COVID-19 pandemic, has highlighted the critical need for effective cross-border pandemic management strategies. Digital health passports (DHPs), which securely store and facilitate the sharing of critical health information, including vaccination records and test results, have emerged as a promising solution to enable safe travel and access to essential services and economic activities during pandemics. However, the implementation of DHPs faces several significant challenges, both related to geographical disparities and practical considerations, necessitating a comprehensive approach for successful global adoption. In this narrative review article, we identify and elaborate on the critical geographical and practical barriers that hinder global adoption and the effective utilization of DHPs. Geographical barriers are complex, encompassing disparities in vaccine access, regulatory inconsistencies, differences across countries in data security and users' privacy policies, challenges related to interoperability and standardization, and inadequacies in technological infrastructure and limited access to digital technologies. Practical challenges include the possibility of vaccine contraindications and breakthrough infections, uncertainties surrounding natural immunity, and limitations of standard tests in assessing infection risk. To address geographical disparities and enhance the functionality and interoperability of DHPs, we propose a framework that emphasizes international collaboration to achieve equitable access to vaccines and testing resources. Furthermore, we recommend international cooperation to establish unified vaccine regulatory frameworks, adopting globally accepted standards for data privacy and protection, implementing interoperability protocols, and taking steps to bridge the digital divide. Addressing practical challenges requires a meticulous approach to assessing individual risk and augmenting DHP implementation with rigorous health screenings and personal infection prevention measures. Collectively, these initiatives contribute to the development of robust and inclusive cross-border pandemic management strategies, ultimately promoting a safer and more interconnected global community in the face of current and future pandemics.

The growing prevalence of chronic diseases such as diabetes, cardiovascular diseases (CVDs), and hypertension calls for innovative strategies for disease surveillance and management. Digital health technologies (DHTs) offer a transformative approach to chronic disease management through real-time, personalized health monitoring and enhanced patient engagement; however, they also present inherent limitations. This narrative review synthesizes current applications of DHTs in the management of diabetes, CVDs, and hypertension, with a focus on advancements in artificial intelligence, digital therapeutics, and remote patient monitoring. A framework of solutions is proposed, comprising six key pillars: (1) data accuracy and standardization through artificial intelligence–enhanced calibration and multisensor fusion; (2) user engagement and compliance supported by gamification and behavioral science; (3) interoperability and clinical integration through Fast Healthcare Interoperability Resources and Health Level Seven standards; (4) accessibility and cost barriers addressed through frugal innovation, open-source platforms, reimbursement policies, and user education; (5) privacy and ethics, employing blockchain and federated learning for secure data governance; and (6) regulatory and policy considerations, advocating for global harmonization and supportive reimbursement models. This framework aims to enhance the reliability, accessibility, and effectiveness of DHTs in chronic disease management. The review provides actionable insights for stakeholders, including developers, healthcare professionals, and policymakers, on optimizing the design, implementation, and regulation of DHTs, ultimately improving chronic disease outcomes.

Africa’s dual burden of rising incidence of infectious diseases and increasing prevalence of non-communicable diseases (NCDs), such as cardiovascular diseases and diabetes, demands innovative approaches to disease surveillance, response, and cross-border health management in response to growing economic integration and global connectivity. In this context, we propose a discursive framework for the development and implementation of a multi-disease digital health passport (MDDHP) in Africa. The MDDHP would serve as a secure platform for storing and sharing individual health data, offering a comprehensive solution to track and respond to infectious diseases, facilitate the management of NCDs, and improve healthcare access across borders. Empowering individuals to proactively manage their health and improve overall outcomes is a key aspect of the MDDHP. In the paper, we examine the key elements necessary to effectively implement MDDHP, focusing on minimizing risks, maintaining efficacy, and driving its adoption while also taking into consideration the unique contexts of the continent. The paper is intended to provide an understanding of the key principles involved and contribute to the discussion on the development and successful implementation of MDDHP in Africa.

In the context of modern healthcare, the concept of patient-centered care (PCC) has emerged as a crucial aspect, prompting the need for innovative frameworks to empower patients and enhance healthcare outcomes. This paper introduces the Patient-Oriented Medical Ontology Conceptual Framework (POMOCF), a powerful framework aimed at giving patients control over their personal and healthcare information. It prioritizes patient independence by allowing for direct control of electronic health records (EHRs) and facilitates the gathering of information through document upload or scanning. In the POMOCF front-end framework, we propose to maintain scalability, along with robust authorization, authentication, and secure data protocols, all of which are detailed within the framework. This approach enhances data accuracy and security, improving data management efficiency. As part of our ongoing development, we are planning to implement an innovative inference system that will automatically analyze and extract relevant details from the uploaded authorized document, provide real-time updates, and maintain data accuracy. This approach further strengthens data accuracy and prevents unauthorized modifications, thereby making the data management process more efficient. POMOCF leverages medical ontology principles to ensure standardized clinical concepts and improved semantic interoperability. Our integration plans involve integrating genotypic data for personalized medicine initiatives and strengthening the front-end infrastructure. By linking front-end interfaces with advanced technological solutions, we aim to provide effective healthcare delivery, promoting personalized care and enhancing patient outcomes.

UNSTRUCTURED Health informatics and artificial intelligence (AI) technologies present unprecedented opportunities for transforming pediatric healthcare delivery globally. Following post-pandemic digital health acceleration and rising demands for equitable pediatric care, this viewpoint explores how public health informatics systems, combined with AI-powered clinical decision support systems, electronic health record (EHR) integration, and telemedicine platforms, can enhance pediatric care quality and accessibility. Case studies analyzing the Pediatric Emergency Care Applied Research Network (PECARN) clinical decision rules, AI-enhanced neonatal sepsis detection systems, and automated autism screening protocols demonstrate successful health informatics implementations in pediatric settings. Key benefits include improved diagnostic accuracy through computer-aided detection, personalized treatment protocols facilitated by clinical decision support, enhanced accessibility via telehealth platforms, and early intervention capabilities enabled by predictive modeling. However, implementation faces significant challenges, including issues with health information system interoperability, data standardization, gaps in digital health infrastructure, and concerns regarding health equity and access to technology. Strategic recommendations emphasize collaborative development of interoperable health information systems, standardized data governance frameworks, and equitable digital health infrastructure to ensure global pediatric care transformation through public health informatics innovation.

Health informatics and artificial intelligence (AI) technologies are increasingly influencing pediatric health care delivery across diverse health system contexts. These technologies offer opportunities to improve diagnostic accuracy, personalized treatment approaches, and access to care globally. This viewpoint examines how health and public health informatics frameworks, when integrated with AI technologies, may help address persistent challenges in global pediatric care delivery. This paper is a viewpoint informed by selected published studies and international digital health guidance rather than a systematic review. Evidence from clinical implementations suggests that AI applications embedded in standardized electronic health records can facilitate improved pediatric diagnostic processes. For instance, machine learning–based algorithms to diagnose serious bacterial infections among febrile infants have shown high diagnostic accuracy and reduced unnecessary invasive procedures in certain clinical contexts. Case studies from the Pediatric Emergency Care Applied Research Network decision rules, neonatal intensive care units, and autism screening programs reflect diverse applications of AI-enabled clinical decision support across pediatric settings. However, there are concerns regarding implementation due to limitations in interoperability of health information systems, gaps in data standardization, inadequate digital infrastructure in resource-limited settings, and issues related to algorithmic bias and equitable access. We argue that strategic development of interoperable health information systems, standardized data governance frameworks, and equitable digital infrastructure is essential to responsibly realize the potential of AI-enhanced pediatric care at scale.