Antimicrobial resistance (AMR) is a growing global health threat requiring robust biosafety, biosecurity, and surveillance systems across human, animal, and environmental sectors. However, evidence on how these systems function at sub-national and facility levels remains limited, particularly in decentralized settings such as Kenya. This scoping review was conducted in line with PRISMA-ScR reporting standards to map evidence on AMR containment systems in Kenya. Peer-reviewed and grey literature covering governance, surveillance, laboratory capacity, workforce, biosafety and biosecurity, digital systems, and One Health integration between January 2022 - February 2026 were systematically identified and thematically synthesized, with methodological quality assessed using the Mixed Methods Appraisal Tool. A total of 31 studies (23 peer-reviewed and 8 grey literature) were included. Human health systems were the most frequently represented domain (n = 27), followed by data integration and digital platforms (n = 16) and animal health (n = 14). Governance and policy-related components were reported in fewer studies (n = 10), while environmental health was the least represented (n = 8). Despite strong national policies and digital platforms, implementation was uneven across counties and facility levels, with key constraints including workforce shortages, infrastructure gaps, fragmented financing, and limited use of surveillance data. These findings highlight persistent gaps in sub-national implementation and One Health integration that limit the effectiveness of AMR containment systems in Kenya.
Open access
Pharmaceutical and Antibiotic Environmental Impacts
John Chinemerem Ogbete, AbuYusuf Aminu-Ibrahim, Obinna Chima Iwuanyanwu
Scaling molecular diagnostic facilities is essential for meeting growing demands for infectious disease surveillance, oncology, genetic screening, and precision medicine, particularly across resource-constrained and rapidly expanding health systems. This study examines how standardized infrastructure and operational design models can enable scalable, high-quality molecular diagnostics while ensuring biosafety, regulatory compliance, and cost efficiency. It synthesizes insights from laboratory engineering, health systems planning, and diagnostic network design to propose an integrated approach to molecular facility expansion. Standardized infrastructure models emphasize modular laboratory layouts, flexible cleanroom zoning, validated airflow and contamination control systems, and harmonized utilities for power, water, and waste management. These design principles enable rapid replication, phased expansion, and adaptability to evolving assay technologies without compromising analytical integrity. Operational design models complement physical standardization through optimized workflow sequencing, sample logistics, equipment utilization, and quality management systems aligned with international laboratory standards. Together, these models reduce setup time, minimize variability, and support consistent performance across decentralized molecular testing sites. The study further highlights the role of digital enablement in scaling molecular diagnostics, including laboratory information management systems, remote monitoring platforms, and standardized data architectures that support traceability, quality assurance, and network-level oversight. Workforce-aligned operational models, incorporating task differentiation, competency-based training, and remote supervision, are identified as critical to sustaining performance in settings with limited specialist capacity. Financing and governance mechanisms, including pooled procurement, regional laboratory networks, and public–private partnerships, are discussed as enablers of affordability and long-term sustainability. The study concludes that scalable molecular diagnostic capacity depends on the integration of standardized infrastructure with adaptive operational design. By embedding flexibility, quality assurance, and interoperability into facility and workflow models, health systems can rapidly expand molecular testing while maintaining safety, reliability, and regulatory alignment. Such approaches strengthen outbreak preparedness, support routine disease management, and advance equitable access to advanced diagnostics across diverse healthcare contexts. Importantly, standardization does not constrain innovation but provides a stable platform for continuous technological evolution, network optimization, and resilient diagnostic system growth in low-, middle-, and high-income settings globally. These frameworks also facilitate benchmarking, performance comparison, regulatory audits, and coordinated scale-up across national, regional, and cross-border diagnostic ecosystems worldwide.
Blockchain technology, with its inherent security, transparency, and immutability, presents a novel approach to addressing critical challenges in public health. This paper explores the potential of blockchain to revolutionize data management, enhance disease surveillance, and empower communities in public health initiatives. We examine how blockchain can secure sensitive health data, facilitate interoperability among disparate systems, and enable decentralized data sharing for research and interventions. Furthermore, we discuss the applications of blockchain in supply chain management for pharmaceuticals, vaccine distribution, and the creation of secure digital identities for individuals. By leveraging blockchain's distributed ledger technology, we can foster trust, improve data integrity, and promote community engagement in public health, ultimately leading to more effective and equitable health outcomes.
AbuYusuf Aminu-Ibrahim, John Chinemerem Ogbete, Obinna Chima Iwuanyanwu
National diagnostic systems form the backbone of public health surveillance, outbreak response, and routine clinical decision-making, yet they are highly vulnerable to systemic shocks during public health stress conditions such as pandemics, natural disasters, and large-scale humanitarian emergencies. This study examines infrastructure resilience planning strategies for national diagnostic systems, focusing on how physical facilities, supply chains, digital platforms, and governance mechanisms can be designed to withstand, absorb, and rapidly recover from extreme stress. Drawing on resilience engineering, public health systems theory, and lessons from recent global health crises, the paper identifies critical resilience dimensions including redundancy, flexibility, surge capacity, interoperability, and decentralization. Particular emphasis is placed on diagnostic laboratory networks, specimen transport systems, data integration platforms, and workforce continuity planning. The analysis demonstrates that centralized systems without adaptive buffers are prone to cascading failures, whereas networked, modular infrastructures enhance continuity of diagnostic services under stress. Infrastructure resilience planning is shown to improve response time, testing coverage, and data reliability during emergencies while preserving routine diagnostic functions. The study also highlights the importance of governance coordination, scenario-based preparedness planning, and real-time performance monitoring to support rapid decision-making. Investment in resilient power supply, cold-chain logistics, digital connectivity, and cross-sector partnerships is identified as a critical enabler of national diagnostic stability. A conceptual resilience planning framework is proposed, integrating technical, organizational, and policy-level interventions across preparedness, response, and recovery phases. By positioning diagnostics as a strategic national asset rather than a passive service function, resilience planning strengthens health security, equity, and trust in public health systems. The paper provides practical insights for policymakers, health infrastructure planners, and emergency preparedness agencies seeking to future-proof diagnostic capacity against increasingly frequent and complex public health shocks. Future research should empirically assess resilience indicators across countries and quantify the relationship between diagnostic system resilience, mortality reduction, and socioeconomic recovery during prolonged public health emergencies. These findings underscore the urgency of embedding resilience metrics into national health investment decisions, enabling proactive planning, transparent accountability, adaptive financing mechanisms, coordinated intergovernmental action, and sustained diagnostic readiness that supports population health protection before, during, and after crises across diverse healthcare contexts.
Ronny Hauf, Robert Miehe, Oliver Schöllhammer, Thomas Bauernhansl
Biological transformation represents one of the most promising optimization strategies for a sustainable economy. The rapid convergence of biotechnology, information technology and production technology provides a vast area of innovation. From an economic and innovation policy perspective, cooperation structures and value creation systems will change significantly in a biointelligent transformation process. In the future, many industries will produce personalized products in a much more decentralized manner based on locally provided, renewable resources using autonomous non-expert systems. Such a profound change affects not only products and processes but also the organization of companies and how innovations are evaluated and implemented. In this paper, we thus discuss the need for a reorientation of innovation management in companies in the context of biological transformation. This article focused the central question of how the innovation management can change in the context of biointelligence so that companies can be helped to invest strategically in biointelligent innovations. We then outline the basic elements of a framework and discuss key challenges for future research and development. In this paper, we present initial thoughts on a framework for the management of biointelligent innovation that aims to solve the complex requirements of BioIntelligence. Our approach is based on a holistic view of different methods and techniques to provide a comprehensive solution to the challenges. We discuss the basic concepts and goals of this framework as well as potential application areas and challenges. Furthermore, we present first approaches for implementation and evaluation.