Family-Centered Longitudinal Twin Modeling Across OBGYN and Pediatric Contexts

Maternal and pediatric care pathways are deeply longitudinal, context-sensitive, and family-centered. Current healthcare systems preserve fragmented encounters across specialties, providers, and organizations, but they do not preserve adaptive continuity models that span pregnancy, postpartum recovery, child development, adherence patterns, caregiver context, and longitudinal behavioral trajectories.

This paper proposes a family-centered Digital Twin for Health framework in which maternal, pediatric, and household context can contribute to bounded longitudinal Twin infrastructure. DT4H integrates cohort-aware initialization, reference-human priors, calibration events, and runtime state transitions into a persistent adaptive modeling layer. StateK computes trajectory and confidence, while SETPOINT executes practices, protocols, and feedback loops.

The proposed infrastructure may support continuity during provider transitions, postpartum follow-up gaps, developmental monitoring, and family-context interpretation. ArenaK behavioral systems may later contribute adaptive engagement and resilience signals for longitudinal family-state modeling. The framework is intentionally bounded as infrastructure support rather than diagnostic authority.