In-Silico Approaches in Sports Epidemiology and their Contribution to the Research on Prevention through Physical Activity in Childhood

Introduction: Physical inactivity in childhood is a global public health concern. Traditional epidemiological approaches often fail to capture the complex interplay of behavioral, environmental, and social determinants. In-silico methods—computational modeling and simula- tions—offer a promising alternative to analyze and predict physical activity (PA) behaviors and intervention effects in youth populations. › Methods: This Rapid Review applied a systematic search strategy in Scopus and PubMed to identify peer-reviewed studies (published until May 2025) employing in-silico approaches in the context of physical activity promotion among children and adolescents. Screening and data extraction followed a structured eight-step framework aligned with Cochrane Rapid Review guidelines. Eligible studies included modeling techniques such as agent-based models (ABM), system dynamics models (SDM), and microsimulations. Results: Out of 59 initial records, 24 studies met all inclusion criteria. Most studies applied ABM or SDM to simulate physical activity outcomes under varying policy or environmental conditions. Common themes included school-based interventions, spatial layout impacts, and peer network influences. While most models clearly stated their objectives, empirical validation and use of device-based activity data were lacking. The reviewed studies demonstrate potential but also highlight gaps in data integration, validation practices, and stakeholder engagement. Discussion: In-silico approaches can substantially advance the design and evaluation of PA interventions in youth. However, their practical utility depends on stronger empirical grounding and participatory development. Future research should emphasize model transparency, validation with real-world data, and broader contextual diversity to ensure relevance and impact in public health policy and practice.