Let's Explore: An in-depth review of Predict-Align-Prevent's predictive analytics for child maltreatment prevention.

Through our programs with state child welfare agencies, we have discovered that the highest risk locations for child maltreatment collectively comprise ~10% of the total population in less than ~10% of a city's geography.

This fraction of the population experiences:

• 60% of child maltreatment
• 60% of all child fatalities
• 40% of diagnosed behavioral, conduct, and psychiatric diagnoses in children
• 70% of violent crimes against elders

A few examples of indicators for child maltreatment that we have identified during our research included: elevated lead levels in children, urinary tract infections, Substance Use Disorder, economic stability, economic supports, acute opioid use, animal abuse, diabetes, self-harm/suicide, asthma, maternal cannabis use, Children's Medicaid, SNAP/ food stamps, assault/community violence, Neonatal Abstinence Syndrome, building and health violations, and the list goes on.

Our model enables targeted prevention and alignment of services to equitably reach the greatest number of those most in need across each community. We have also discovered that ICD 10 health diagnosis codes with known correlation to toxic stress cluster in places with high child maltreatment risk.

These findings validate the theory behind the model: areas with high risk for child maltreatment represent the accumulation of ACEs in the underlying population. Preventing ACEs will prevent maltreatment and a host of other dire, ACEs-related outcomes.