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 September, one below-trend signal and three sustained structural shifts. The structural pattern is broadly downward across both violent and property crime, with robbery, theft from vehicle, and motor vehicle theft all running well below where they were a year ago.
Burglary is the sharpest single-month signal, down to 33 incidents over the trailing 12 months against 41 in the prior year, a 19.5% decline. Robbery and theft from vehicle are both carrying sustained-shift signals in the decrease direction: robbery dropped from 108 to 68 over the same window, down 37.0%, while theft from vehicle fell from 359 to 222, down 38.2%. Aggravated assault is the one category moving the other way, up 23.5% year over year, 42 incidents against 34, and sits outside the otherwise downward pattern across Edgewood this month.
Notable signals 1
Burglary
The past 12 months saw 33 incidents — about 50% below the 66 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 103, down 63% from 281 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 222, down 38% from 359 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 68, down 37% from 108 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 September 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.