Achieving timely prevention, detection, and response to infectious disease threats, while maintaining equitable access to essential services—depends on robust, well-governed health systems. In Africa’s diverse contexts, strengthening these systems requires integrated policy frameworks, adaptive management practices, and innovative technologies that address gaps in surveillance, workforce capacity, supply chains, and community engagement.

This Article Collection examines multidisciplinary strategies to enhance health system resilience and epidemic preparedness across the continent. We focus on:

- Policy and Governance: Crafting adaptive national and subnational policies, financing models, and regulatory environments that incentivize rapid outbreak response and sustain routine care.

- Health System Management: Optimizing human resources for health, supply-chain logistics, and facility-level coordination to maintain continuity of care during emergencies.

- Digital Health & Informatics: Deploying electronic surveillance platforms, mobile health (mHealth) tools, and data-analytics dashboards for real-time monitoring, early warning, and evidence-based decision-making.

- Surveillance & Laboratory Networks: Expanding laboratory capacity, sample-transport systems, and integrated One Health approaches to detect zoonoses and emerging pathogens.

- Community Engagement & Risk Communication: Leveraging regional partnerships, local governance, and culturally tailored messaging to build trust and promote preventive behaviors.

- Operational Research & Evaluation: Implementing outbreak simulations, performance metrics, and rapid-cycle evaluations to refine interventions and inform scalable best practices.

We welcome submissions that generate practical, scalable solutions for African health systems. By uniting insights from policymakers, health managers, informaticians, and frontline practitioners, this Collection aims to inform evidence-driven investments, strengthen preparedness capacities, and improve health outcomes across the continent.

This collection invites original research articles, reviews, and case studies at the intersection of Computational Intelligence (CI), Artificial Intelligence (AI), and healthcare informatics and healthcare records, with a focus on Large Language Models (LLMs) methods and architectures. The aim is to showcase innovative methodologies and applications that bridge cutting-edge CI techniques with real-world challenges in healthcare.

We welcome contributions that present novel algorithms, frameworks, and applications of AI and CI in areas such as, clinical decision support, healthcare informatics, and ethical or legal aspects of medical AI. Special attention will be given to interdisciplinary work that highlights translational potential, system-level integration, or demonstrates real-world deployment within health systems. This collection seeks to foster collaboration among researchers, clinicians, data scientists, and system designers to promote advances that will shape the future of intelligent health technologies.

Topics of Interest Include, but Are Not Limited To:

- Integration of LLMs with electronic health records (EHRs) and clinical decision support systems

- Ethical, legal, and regulatory considerations in deploying LLMs in healthcare

- Case studies demonstrating real-world implementation of LLMs in health systems

Any study solely on development of an LLM application in healthcare records maintenance or health informatics should have application analysis to support.

Keywords: Computational Intelligence, Artificial Intelligence, Large Language Models, Healthcare Informatics, Clinical Decision Support, Intelligent Medical Systems。