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The Application of Artificial Intelligence in Public Health Surveillance in Portugal: An Exploratory Study of Expert Perspectives

Year: 2026

Type: article

Abstract: Introduction: The application of AI in public health surveillance presents a transformative potential for more efficient work methodologies, offering new capabilities for the detection, notification, and response to public health threats. However, it is important to be aware of the associated risks and the ethical and legal challenges linked to AIs use in such a sensitive area as public health. The general objective of this study was to explore the application of AI in public health surveillance in Portugal, as viewed by Portuguese experts. Methods: The methodological approach employed was a qualitative study, utilising a descriptive and exploratory investigation. A content analysis was performed on 28 anonymised semi-structured interviews. This process identified concepts, themes, key ideas, and emergent patterns. The findings were then grouped into categories and subcategories, which allowed us to highlight significant consensuses and meaningful insights. Results: Experts recognised AIs transformative potential in enhancing predictive capacity, automating data processes, and supporting decision-making. However, they highlighted critical limitations of the Portuguese system, notably entrenched reactivity, fragmented infrastructures, under-utilisation of primary care and personal device data, and insufficient surveillance of non-communicable diseases. Key barriers include poor data quality and interoperability, absence of comprehensive data governance, shortage of AI-skilled professionals, resistance to organisational change, and limited financial sustainability. Ethical concerns, privacy, algorithmic bias, and explainability were emphasised as central to AIs legitimacy. Comparisons with international experiences revealed that progress depends less on technological readiness than on systemic reform, data harmonisation, and strong governance aligned with European Union (EU) and World Health Organization (WHO) frameworks. Conclusion: AI can shift Portuguese public health surveillance from reactive to predictive, but only if supported by robust data ecosystems, clear governance, and investment in human capital. A national roadmap is required, prioritising interoperability, sustainable financing, and ethical implementation, to ensure that AI serves as a complement to, rather than a replacement for, human judgement in protecting population health.

Source: Portuguese Journal of Public Health

DOI: 10.1159/000550578

Authors: Liliana Certo, Maurício Alves, Teresa Magalhães

Institutions: Universidade Nova de Lisboa, Comprehensive Health Research Centre

Language: English

Topic: Data-Driven Disease Surveillance

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDGs: Good health and well-being, Industry, innovation and infrastructure, Peace, justice, and strong institutions

Open Access status: gold

Estimated APC paid: $269