CUF Crime Rate Trends — Cincinnati
CUF stands for Clifton Heights, University Heights, and Fairview, the dense neighborhood immediately south and west of the University of Cincinnati's main campus. Mixed student housing, hillside residential streets, and the McMillan Street and Calhoun Street commercial strips that serve the campus.
Five categories moved in CUF this September, a mix of two one-month spikes and three sustained structural shifts. The spikes land in theft from vehicle and aggravated assault, both running above trend, while burglary is the clearest sustained shift, moving in the opposite direction as part of a multi-year structural change.
Theft from vehicle is at 252 incidents over the trailing 12 months, up 46.5% against the prior year's 172. Aggravated assault has risen to 37 incidents from 26 over the same window, a 42.3% increase. Burglary, by contrast, is down 42.0%, 80 incidents now against 138 in the prior 12 months, a sustained decline that offsets some of the upward pressure in other property categories.
Notable signals 2
Theft from Vehicle
The past 12 months saw 252 incidents — about 53% above the 165 average from prior years.
Aggravated Assault
The past 12 months saw 37 incidents — about 148% above the 15 average from prior years.
All categories, last 24 months
Each panel: recent monthly count vs. trailing 12-month context. MoM is the most recent month vs. the one before; 12mo YoY compares the trailing year to the year before that.
What's been quietly true for a year
Spikes get attention. Sustained shifts shape policy. These are multi-quarter patterns where the past 12-month total differs meaningfully from the year before — they often precede the baseline resetting.
- Other Larceny has reset to a lower baseline.
The trailing 12-month count is 223, down 31% from 322 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Burglary has reset to a lower baseline.
The trailing 12-month count is 80, down 42% from 138 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Theft from Vehicle is climbing.
The trailing 12-month count is 252, up 47% from 172 the year before. If the trend holds another quarter, it will pull the multi-year baseline up.
What next month likely looks like
Forecasts trained through September 2026, with a likely range we're 95% confident the actual count will fall inside. Categories with too little recent volume — or violent categories at the neighborhood level — show no forecast and are surfaced through signals above instead. See the methodology page for the gating rules.
Aggravated Assault
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Burglary
Homicide
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Motor Vehicle Theft
Other Larceny
Robbery
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Sexual Assault
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Theft from Vehicle
How CUF compares
Peer neighborhoods picked by closest 12-month theft from vehicle volume — a pragmatic v1 of peer matching. Demographic / housing-stock peer matching isn't built yet (we deliberately don't ingest income or race data alongside crime). Volume similarity has the right intuition: “neighborhoods experiencing comparable theft from vehicle levels.”
Westwood
180 incidents over the past 12 months — 72 below CUF's 252.
Open page →East Price Hill
163 incidents over the past 12 months — 89 below CUF's 252.
Open page →Over-the-Rhine
343 incidents over the past 12 months — 91 above CUF's 252.
Open page →Do crime spikes here spill over to adjacent neighborhoods?
CUFdoesn't have enough spike history in any single category for a stable spillover rate yet (we want at least 5 events). The table below lists what we have.
| Category | Spike events | Same-category spillover |
|---|---|---|
| Aggravated assault | 2 | — too few |
| Theft from vehicle | 2 | — too few |
Each row shows CUF's historical spike events for that category, and how often any of its 7 adjacent neighborhoods spiked the same category within the next 3 months. A high same-category rate suggests a shock that travels (e.g. theft crews moving across Cincinnati); a low rate means spikes here tend to be local to the neighborhood. Categories with fewer than 5 historical spike events are listed but their rates are suppressed.
Recurring local terms (last 12 months)
Top terms in incident descriptions for CUF, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.
Hour-of-day, day-of-week, and seasonality
Distribution of bucketed incidents in this neighborhood across the full analysis window. Useful for routine context — shopping-strip thefts vs. late-night assaults read very differently when you can see when each typically happens.
How we built this page
Data → Anomalies → Forecast → Page
Incident data is pulled from Cincinnati Open Data — STARS Category Offenses post-2024-06-03 plus PDI Crime Incidents back to 2020 — mapped to 8 UCR-aligned categories (vandalism and arson aren't recoverable across the STARS migration boundary). Aggregated to Statistical Neighborhood Approximation × category × month.Anomalies are surfaced using strict thresholds (~p < 0.01). Forecasts are Prophet with low-count gating; violent categories at the neighborhood level skip the forecast and show rare-event / streak signals instead.
Spike rule: 12-mo total > baseline mean + 2.5σ AND ≥ 20 incidents AND 6-mo confirms. Drop rule: 12-mo total < baseline mean − 2.5σ AND baseline mean ≥ 20. Rare event: any incident in the last 90 days, no prior comparable in ≥ 5 years.