Policy and resource optimization based on spatial risk prediction models for child maltreatment

Abstract

Spatial risk prediction models describe the features of small spatial units which support or attract child maltreatment behaviors. Due to shared risk factors, community problems such as infant mortality, poor educational readiness, injury-related deaths, and a host of physical and mental health problems associated with toxic stress co-occur in these small areas. Based on administrative data, this spatial intelligence brings cross-sector stakeholders together to collaboratively plan for optimization of critical supports, capacity development for vital services, improvement of professional response, development of supportive infrastructure, and creation of healthier social norms. We present the policy and resource optimization strategies being developed in locations implementing the Predict-Align-Prevent program for child maltreatment prevention.