This review examined the rapid expansion of telehealth and virtual nursing consultation across rural communities and long-term care environments, with emphasis on adoption, effectiveness, implementation conditions, and equity. A structured narrative review approach was used to synthesise peer-reviewed evidence published before and in 2021, drawing on studies from North America, Europe, Asia, Nigeria, and other African settings. The analysis considered delivery models, nursing roles, organisational readiness, clinical and operational outcomes, user experiences, ethical concerns, and long-term policy requirements.
The findings indicate that virtual care improved access to specialist advice, continuity, triage, chronic disease monitoring, caregiver support, and coordination, while reducing travel, infection exposure, and some avoidable institutional transfers. Nurses were central to remote assessment, education, documentation, escalation, and interdisciplinary liaison. However, effectiveness varied according to broadband availability, digital literacy, platform usability, workforce competence, reimbursement, interoperability, and clinical appropriateness. Rural residents, frail older adults, people with cognitive or sensory impairment, low-income households, and minority-language populations remained disproportionately exposed to exclusion. Evidence also showed that emergency adoption often outpaced governance, privacy safeguards, technical support, and evaluation.
The review concludes that telehealth should be embedded within hybrid, person-centred systems rather than treated as a substitute for all face-to-face care. Sustainable implementation requires stable financing, accessible technologies, clear regulatory standards, workforce development, and reliable referral pathways. Greater participation by patients, caregivers, nurses, and local communities is also necessary to ensure culturally responsive service design. It is recommended that future research prioritise longitudinal effectiveness, cost, safety, nursing workload, resident autonomy, and equity, particularly in underrepresented rural and African contexts, while ensuring transparent oversight of remote monitoring, artificial intelligence, and predictive technologies.
Abimbola Caleb Adesemoye, Esther Sydney, Glory Ohunyon· International Journal of Mul...· 0 citations
Humanitarian and disaster response supply chains operate under extreme uncertainty, time pressure, and resource constraints, where delays or misallocations directly translate into human suffering and loss of life. In recent years, predictive intelligence models have emerged as critical enablers for enhancing supply chain resilience by improving anticipatory decision-making, situational awareness, and adaptive coordination across complex humanitarian networks. This review examines conceptual advances in predictive intelligence models applied to humanitarian and disaster response supply chains, with emphasis on their theoretical foundations, methodological evolution, and resilience-oriented capabilities. The paper synthesizes developments across data-driven forecasting, probabilistic risk modeling, machine learning, and hybrid human–AI decision frameworks, highlighting how these approaches support demand anticipation, disruption prediction, inventory pre-positioning, and logistics network reconfiguration. Particular attention is given to the integration of real-time data streams from remote sensing, social media, Internet of Things devices, and institutional reporting systems, as well as the role of explainability and trust in high-stakes humanitarian contexts. The review also discusses persistent challenges, including data sparsity, ethical constraints, model transferability across disaster types and regions, and governance issues related to inter-agency coordination. By organizing the literature around resilience dimensions—robustness, adaptability, and recoverability—the paper offers a unifying conceptual lens for evaluating predictive intelligence models beyond pure accuracy metrics. The study concludes by identifying research gaps and proposing future directions, including human-centered predictive systems, federated and privacy-preserving learning, and policy-aligned intelligence architectures. Overall, the review provides a structured foundation for researchers, practitioners, and policymakers seeking to leverage predictive intelligence to strengthen humanitarian supply chain resilience in increasingly volatile disaster environments.
Abiola Idowu, Abimbola Caleb Adesemoye, Esther Sydney et al.· International Journal of Mul...· 0 citations
Public sector supply chains are frequently challenged by limited transparency, weak accountability mechanisms, fragmented data management, and persistent risks of corruption and inefficiency. These challenges undermine public trust and reduce the effectiveness of government procurement and service delivery systems, particularly in developing and transitional economies. Blockchain technology has emerged as a promising governance infrastructure capable of addressing these systemic weaknesses through its decentralized, immutable, and auditable data architecture. This review paper examines the role of blockchain-based governance frameworks in enhancing transparency, traceability, and accountability across public sector supply chains. Drawing on peer-reviewed literature, policy reports, and real-world implementation cases, the study synthesizes current applications of blockchain in public procurement, logistics coordination, asset tracking, and contract execution. The review critically evaluates how core blockchain features, including distributed ledgers, smart contracts, and cryptographic verification, enable real-time visibility, reduce information asymmetry, and strengthen institutional oversight. Additionally, the paper discusses governance design considerations such as interoperability with legacy systems, regulatory alignment, data privacy, and stakeholder adoption challenges. Particular attention is given to the implications of blockchain deployment for anti-corruption efforts, performance monitoring, and public value creation. By consolidating fragmented research across technology, governance, and supply chain domains, this review provides a structured conceptual foundation for policymakers, public administrators, and researchers seeking to implement or evaluate blockchain-enabled governance models. The paper concludes by identifying research gaps and proposing future directions for scalable, ethical, and context-sensitive blockchain adoption in public sector supply chains.
A. Idowu, Abimbola Caleb Adesemoye, Esther Sydney et al.· International Journal of Mul...· 0 citations
National emergency supply chains face increasing pressure from climate-induced disasters, pandemics, cyber-physical disruptions, and geopolitical instability. These shocks expose persistent coordination failures, regulatory fragmentation, and limited real-time visibility across public and private response networks. Recent advances in artificial intelligence offer a critical opportunity to redesign emergency supply chain preparedness through data-driven compliance monitoring and adaptive coordination mechanisms. This review synthesizes conceptual advances in AI-enabled compliance and coordination models that support national emergency supply chain readiness before, during, and after large-scale disruptions. The paper examines how machine learning, natural language processing, multi-agent systems, and digital twin architectures are being integrated into regulatory intelligence, inter-agency coordination, and risk-aware logistics planning frameworks. Particular attention is given to AI-driven compliance automation for emergency procurement, inventory governance, and cross-jurisdictional policy alignment, as well as coordination models that enable dynamic resource allocation and decentralized decision-making under uncertainty. The review also evaluates emerging governance challenges, including algorithmic transparency, accountability, data sovereignty, and interoperability across heterogeneous emergency management systems. By consolidating theoretical perspectives and recent implementation models, this paper develops an integrative conceptual framework that links AI-enabled compliance assurance with resilient coordination across national emergency supply networks. The findings contribute to policy design, system architecture development, and future research on resilient, compliant, and adaptive emergency supply chain ecosystems capable of supporting national preparedness objectives in an era of complex systemic risk.
Abiola Idowu, Esther Sydney, Glory Ohunyon et al.· International Journal of Mul...· 0 citations