Surveillance without exclusion: strategies to include marginalised groups in behavioural monitoring
Year: 2025
Type: article
Abstract: Socially marginalised populations-including people in prison, migrants, and individuals facing social exclusion-experience a disproportionate burden of infectious diseases and often remain invisible in public health surveillance. Although behavioural responses to outbreaks are critical to epidemic dynamics, these groups are frequently excluded from both traditional and digital monitoring systems, limiting the scope and equity of behavioural surveillance. This presentation reflects on how structural barriers-such as poor data interoperability, the fragmentation of health records between institutional and community systems, and the lack of standardised indicators-affect our ability to monitor behaviours and design responsive interventions for high-risk populations. Using the prison setting as a case study, it explores how surveillance gaps compromise real-time insight into behavioural trends during outbreaks and perpetuate health inequities. Building on insights from the COVID-19 response, the presentation also considers how rapid improvements in data integration and monitoring were achieved when public health urgency aligned with political will. This offers lessons for building more inclusive systems that systematically collect and use behavioural data across all segments of the population. Closing these gaps is not only a matter of health equity but a prerequisite for effective and resilient epidemic preparedness. Behavioural surveillance must be designed with inclusion in mind-from data infrastructure to participation models-so that no group is left behind in public health decision-making.
Author: L Tavoschi
Institution: University of Pisa
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,181
OpenAlex ID: W7101425537
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