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.
April 2026 was a quiet month in Clifton. No tracked category moved enough to register a signal — zero notable shifts across all six tracked crime types. The dominant story is structural and sits in the 12-month totals rather than any single-month move.
Burglary is down 34.5% against the prior 12 months (38 incidents vs. 58), and robbery is down 28.6% (10 vs. 14). Motor vehicle theft dropped 19.7% over the same window. Theft from vehicle and other larceny were close to flat — off 8.2% and up 3.7%, respectively — while aggravated assault edged up 13.3% (17 vs. 15), the one category running above its prior-year pace.
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.
No sustained shifts surfaced this month.
What next month likely looks like
Forecasts trained through April 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 other larceny 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 other larceny levels.”
College Hill
111 incidents over the past 12 months — 0 below Clifton's 111.
Open page →Evanston
119 incidents over the past 12 months — 8 above Clifton's 111.
Open page →Mt. Airy
101 incidents over the past 12 months — 10 below Clifton's 111.
Open page →Do crime spikes here spill over to adjacent neighborhoods?
When Clifton has spiked other larceny historically (5 events on record), an adjacent neighborhood spiked the same category within 3 months 100% of the time. The strongest-travelling categories sit at the top of the table.
| Category | Spike events | Same-category spillover |
|---|---|---|
| Other larceny | 5 | 100% |
| Burglary | 4 | — too few |
| Aggravated assault | 1 | — too few |
Each row shows Clifton's historical spike events for that category, and how often any of its 5 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 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.