Clifton Crime Rate Trends — Cincinnati
Clifton is a hillside residential neighborhood north of the University of Cincinnati, anchored by the Ludlow Avenue commercial strip in the Gaslight District and Clifton Avenue running north-south. Mostly historic single-family homes, with Burnet Woods park and Mt. Storm park on the bluff edges.
August 2026 produced a single notable signal in Clifton: a sustained structural shift in burglary, not a one-month dip but a multi-month pattern that has reshaped the trailing 12-month total. Every other tracked category came in within its normal range.
Burglary is down 48.1% against the prior 12 months, 28 incidents versus 54 in the year before, a move large enough to register as a longer-term structural change rather than noise. Theft from vehicle is the one category running the other direction, up 28.1% over the same window, 82 incidents against 64. Robbery and aggravated assault are also well below their prior-year levels, 6 versus 16 and 11 versus 17 respectively, though neither crossed the threshold for a distinct signal this month.
Notable signals 0
Nothing notable surfaced this month — every category sits within normal range against its baseline.
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.
- Burglary has reset to a lower baseline.
The trailing 12-month count is 28, down 48% from 54 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
What next month likely looks like
Forecasts trained through August 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 Clifton compares
Peer neighborhoods picked by closest 12-month burglary 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 burglary levels.”
Recurring local terms (last 12 months)
Top terms in incident descriptions for Clifton, 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.