Edgewood Crime Rate Trends — Washington DC
Edgewood is the Northeast neighborhood between Rhode Island Avenue and the Metropolitan Branch Trail, with mid-century apartment complexes and a Rhode Island Avenue Metro station that anchors its commercial life. The cluster includes Bloomingdale and Truxton Circle to the south plus Eckington along the Red Line tracks, a stretch that has shifted from industrial to mixed residential over the past two decades.
Four categories moved in Edgewood this August, and the shape is broadly downward. One registered as a single-month below-trend signal, burglary, while three others, robbery, theft from vehicle, and motor vehicle theft, are showing sustained multi-month structural declines rather than one-off quiet readings. The overall picture is a neighborhood where property crime has been running lower across multiple categories for an extended stretch.
Robbery stands out on the 12-month totals: 65 incidents against 121 in the prior year, down 46.3%. Theft from vehicle followed a similar arc, 236 current versus 356 prior, a 33.7% reduction. Motor vehicle theft has moved the most dramatically over the trailing year, 105 incidents against 291, down 63.9%. Aggravated assault is the one counter-trend, up 24.2% year-over-year at 41 incidents versus 33, and is the category to watch against an otherwise downward-trending mix.
Notable signals 1
Burglary
The past 12 months saw 32 incidents — about 52% below the 67 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.
- Motor Vehicle Theft has reset to a lower baseline.
The trailing 12-month count is 105, down 64% from 291 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Theft from Vehicle has reset to a lower baseline.
The trailing 12-month count is 236, down 34% from 356 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Robbery has reset to a lower baseline.
The trailing 12-month count is 65, down 46% from 121 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 Edgewood 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 Edgewood, 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 DC Open Data — MPD's per-year Crime Incidents layers on the DCGIS ArcGIS Hub — mapped to 8 UCR Part 1 categories (vandalism and arson are not exposed in MPD's public feed and are excluded). The feed covers 2018-current and updates daily. Aggregated to neighborhood cluster × category × month, with each cluster page identified by its colloquial lead constituent (Adams Morgan, Petworth, Capitol Hill, etc.) rather than the numbered 'Cluster N' identifier.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.