ZERO EVENT · HOMICIDEAPRIL 2026 BRIEFINGCINCINNATI · 2.2K residents

English Woods_North Fairmount Crime Rate Trends — Cincinnati

English Woods and North Fairmount are merged here as a single Census-aligned SNA in the western hills above the Mill Creek Valley. Predominantly low-density residential, with public housing redevelopment and large open spaces along the hillside.

HOMICIDE · 24-MO COUNT04 2026 · 0
01112-mo avg: 0.0
ENGLISH WOODS_NORTH FAIRMOUNTCITYWIDE TREND (RESCALED)-4% 12MO YOY
MoM
12mo YoY
0last 12mo
0this month
01 · TL;DR

April 2026 was a structurally quiet month for English Woods_North Fairmount. The one tracked signal is a zero-event reading for Homicide — a category that has recorded no incidents in the current window. No other category crossed an anomaly threshold.

The 12-month trend lines across the neighborhood are broadly downward on property and violent crime. Aggravated assault is down 71.4% against the prior year (2 incidents vs. 7), motor vehicle theft is down 80.0% (1 vs. 5), and burglary is down 40.0% (3 vs. 5). Other larceny held flat at 9 incidents in both periods. Everything else tracked this month ran within expected range.

1 zero-event
02 · Notable signals

Notable signals 0

Nothing notable surfaced this month — every category sits within normal range against its baseline.

03 · By category

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.

Homicidebelow threshold
2024-052026-04
Robberybelow threshold
2024-052026-04
Aggravated Assaultbelow threshold
2024-052026-04
Sexual Assaultbelow threshold
2024-052026-04
Burglarybelow threshold
2024-052026-04
Theft from Vehiclebelow threshold
2024-052026-04
Other Larcenybelow threshold
2024-052026-04
Motor Vehicle Theftbelow threshold
2024-052026-04
05 · Forecast

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

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Burglary

NO FORECAST

Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.

Homicide

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Motor Vehicle Theft

NO FORECAST

Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.

Other Larceny

NO FORECAST

Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.

Robbery

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Sexual Assault

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Theft from Vehicle

NO FORECAST

Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.

06 · Context & comps

How English Woods_North Fairmount compares

Peer neighborhoods picked by closest 12-month homicide 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 homicide levels.”

07 · Patterns

Recurring local terms (last 12 months)

Top terms in incident descriptions for English Woods_North Fairmount, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

partpersonalstrangulation
When does it happen?

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.

HOUR OF DAY · ALL CATEGORIES
0163212am6am12pm6pm11pm

Hour 0 is mildly inflated by reports without a known time defaulting to midnight — see methodology.

DAY OF WEEK · ALL CATEGORIES
02143MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
01325JanFebMarAprMayJunJulAugSepOctNovDec
08 · Methodology

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.