SUSTAINED DROP · OTHER LARCENYAPRIL 2026 BRIEFINGDENVER · 4.0K residents

Clayton Crime Rate Trends — Denver

Clayton is a small northeast neighborhood east of Five Points and Whittier, organized around East 32nd Avenue and York Street. Predominantly early-20th-century working-class residential with a mix of bungalows and modest two-story homes.

OTHER LARCENY · 24-MO COUNT04 2026 · 3
0132512-mo avg: 3.5
CLAYTONCITYWIDE TREND (RESCALED)+8% 12MO YOY
-50%MoM
-60%12mo YoY
42last 12mo
3this month
01 · TL;DR

April 2026 produced a single signal in Clayton: a sustained structural shift in other larceny. One category moved, one flag type registered, and everything else — robbery, aggravated assault, burglary, theft from vehicle, motor vehicle theft, vandalism — sat within normal range for the month.

The sustained shift in other larceny is the meaningful data point here. Over the trailing 12 months, the category logged 42 incidents against 104 in the prior 12-month period — a 59.6% reduction that reflects a multi-month structural change, not a single quiet month. Aggravated assault (up 28.6% to 27 incidents) and theft from vehicle (up 27.6% to 37 incidents) are worth tracking in coming months, but neither crossed an anomaly threshold this period.

1 sustained shift
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 Assault+29%
2024-052026-04
Burglary-8%
2024-052026-04
Theft from Vehicle+28%
2024-052026-04
Other Larceny-60%
2024-052026-04
Motor Vehicle Theft-31%
2024-052026-04
Vandalism+18%
2024-052026-04
Arsonbelow 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.

Arson

NO FORECAST

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

Burglary

MAY 2026
Most likely 4 next month — likely between 1 and 7.
+24% vs 12-month average (≈3.1)

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

MAY 2026
Most likely 1 next month — likely between 0 and 5.
39% vs 12-month average (≈2.3)

Other Larceny

MAY 2026
Most likely 5 next month — likely between 0 and 12.
+57% vs 12-month average (≈3.5)

Robbery

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

MAY 2026
Most likely 4 next month — likely between 0 and 7.
+17% vs 12-month average (≈3.1)

Vandalism

MAY 2026
Most likely 7 next month — likely between 4 and 10.
+55% vs 12-month average (≈4.4)
06 · Context & comps

How Clayton 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.”

SPATIAL SPILLOVER · NEW

Do crime spikes here spill over to adjacent neighborhoods?

When Clayton has spiked other larceny historically (5 events on record), an adjacent neighborhood spiked the same category within 3 months 0% of the time. The strongest-travelling categories sit at the top of the table.

Clayton historical spike-event spillover by crime category (3-month lookahead, adjacent neighborhoods via shared boundary).
CategorySpike eventsSame-category spillover
Other larceny50%

Each row shows Clayton's historical spike events for that category, and how often any of its 6 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 Denver); 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.

07 · Patterns

Recurring local terms (last 12 months)

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

drugweapontrespassingitemspossdischargeforceunlawfulordersimpleaggravatedparaphernaliaresidencecourtpartspolicebusinessinjurethreatsbldgfraudoffenderpowpoprevbicycle
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
05611112am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
0129257MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
087175JanFebMarAprMayJunJulAugSepOctNovDec
08 · Methodology

How we built this page

Data → Anomalies → Forecast → Page

Incident data is pulled from Denver Open Data — DPD's NIBRS-coded crime offenses on ArcGIS Hub — mapped to 9 NIBRS-aligned categories (sexual assault is excluded because DPD redacts victim-bearing rows from the public feed). The feed publishes a 5-year rolling window so the analysis baseline starts at 2021-01. Aggregated to statistical neighborhood × 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.