Systems Thinking Application to Ethical and Privacy Considerations in AI-Enabled Syndromic Surveillance Systems: Requirements for Under-Resourced Countries in Southern Africa

This paper examines the ethical and privacy considerations of implementing AI-enabled syndromic surveillance systems in under-resourced Southern African countries. It highlights the rise of digital health technologies and big data in public health, which enables early disease outbreak detection and monitoring. In Southern Africa, where health systems are uniquely complex and dynamic, such advancements pose a chance to raise significant ethical and privacy concerns. The study employed a multifaceted methodology, combining literature review, systems dynamics modelling (SDM), systems thinking, and causal loop diagrams (CLDs) to analyse these issues. The research focuses on countryspecific case studies to gain insights into the local context. Findings from the study identified factors such as data collection and privacy, data quality, algorithm performance and bias, regulatory frameworks, surveillance infrastructure, data sharing, community trust, capacity building, and education as critical when considering ethics and privacy issues in AI-enabled syndromic surveillance systems. In conclusion, the study emphasises the application of systems thinking principles and methodologies as a comprehensive approach to address these ethical and privacy challenges in Southern Africa. By considering the complex interplay of stakeholders, potential risks, and specific regional needs, the paper advocates for responsible and beneficial deployment of AI surveillance systems, ensuring the protection of individual rights and public interests.