Limitations of standard public health surveillance and shifting to a strengths-based approach

Abstract Population health monitoring systems face challenges when applied to racially/ethnically minoritized communities. Beginning with inadequate representation, as small sample sizes fail to capture sufficient data, and diverse groups are inappropriately aggregated, masking specific health trends. Methodological barriers compound these issues, with racial misclassification rates reaching 30% and survey methods relying on telephone and internet access excluding households without reliable service, disproportionately affecting minoritized populations. The governance of conventional monitoring systems represents another problem. For example, in the United States, data ownership typically remains with federal or state agencies rather than Indigenous communities, creating a power imbalance that undermines trust and participation. This structural arrangement prevents the development of more responsive and effective health interventions tailored to community needs. In Europe, the estimated 12 million Roma people are Europe's largest and most marginalized minority group. Roma population experience persistent health inequities rooted in systemic discrimination and social exclusion. Roma voices have often been excluded from shaping culturally sensitive and sustainable research. Due to structural barriers in education, Roma are underrepresented in academic research roles and therefore alternative forms of participation are essential to ensure representation in research concerning Roma communities. Generic ethical frameworks often overlook cultural risks specific to Roma. The presentation emphasizes that truly effective health monitoring requires fundamental shifts in approach - moving to strength-based frameworks and ensuring minoritized communities maintain power over their own data. Then, health surveillance systems can more accurately represent minoritized populations and support community-driven solutions to persistent health inequities.