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Ethical Governance, Security, and Data Protection in Public Health Informatics: Integrating Digital Health Technologies, Machine Learning, and Institutional Accountability in Resource-Constrained Contexts
Issue Vol. 2 No. 01 (2025): Volume 02 Issue 01 --- Section Articles
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Abstract
The accelerated digitalization of public health systems has fundamentally transformed how health data are generated, processed, governed, and acted upon across diverse institutional and socio-economic contexts. Public health informatics now occupies a central position in population-level surveillance, clinical decision support, emergency response, and policy formulation, particularly in the wake of global health crises and the rapid expansion of artificial intelligence-driven analytics. At the same time, the ethical, security, and data protection implications of these transformations have grown in complexity and urgency, especially in resource-constrained settings where infrastructural limitations, regulatory fragmentation, and social vulnerabilities intersect. This article develops a comprehensive, theoretically grounded, and critically reflective analysis of ethical governance, privacy, and security in contemporary public health informatics by synthesizing insights from public health ethics, data governance theory, cybersecurity scholarship, and digital health research. Drawing extensively on recent interdisciplinary literature, the study situates ethical considerations not as peripheral compliance requirements but as constitutive elements of effective, trustworthy, and sustainable informatics systems (Gashu & Guadie, 2024; Abernethy et al., 2022).
The article advances three core arguments. First, ethical governance in public health informatics must be understood as a dynamic, socio-technical process that integrates normative principles, institutional accountability, and technological design, rather than as a static set of rules applied after system deployment (Gashu & Guadie, 2024; Sargiotis, 2024). Second, security and privacy challenges in health information systems are inseparable from broader data protection regimes, machine learning practices, and digital infrastructure choices, demanding holistic approaches that bridge technical safeguards and organizational culture (Shojaei et al., 2024; Herzog et al., 2024). Third, resource-limited contexts require context-sensitive ethical frameworks that balance innovation, equity, and risk mitigation, recognizing historical inequalities in data extraction, governance capacity, and technological dependency (Wang et al., 2021; Herath et al., 2024).
Methodologically, the study adopts a qualitative, integrative research design grounded in critical literature synthesis and theoretical elaboration. Rather than producing empirical measurements, the article interprets patterns, tensions, and convergences across existing studies on public health informatics, digital health, machine learning, and data governance. The results are presented as analytically derived insights into governance models, ethical risk domains, and institutional practices, while the discussion offers an extended engagement with competing scholarly perspectives, limitations, and future research trajectories. By foregrounding ethics, privacy, and security as foundational to public health informatics, this article contributes a deeply elaborated conceptual framework aimed at informing policymakers, system designers, researchers, and public health practitioners navigating the evolving digital health landscape (Rajkomar et al., 2018; Yan et al., 2025).
Keywords
References
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