Deanwood Crime Rate Trends — Washington DC
Deanwood is the far-Northeast neighborhood east of the Anacostia River, with single-family bungalows and a Deanwood Metro station that anchors a small commercial strip on Sheriff Road. The cluster reaches into Burrville, Grant Park, Lincoln Heights, and Fairmont Heights, a contiguous residential band on the city's eastern edge.
Six categories moved in Deanwood in September 2026, with the mix split between two single-month below-trend signals and four sustained structural shifts. The structural pattern is broadly downward across both property crime and robbery, with multi-year volume changes dominating the picture rather than any single noisy month.
Robbery is the strongest signal, down 39.7% over the trailing 12 months, 41 incidents against 68 in the prior year. Theft from vehicle also ran below trend this month and carries a 12-month total of 72 against 155 the year before, a 53.5% reduction. Aggravated assault and burglary move in the opposite direction, up 79.4% and 65.2% respectively over the same 12-month window, both registered as sustained shifts rather than single-month swings, so those gains reflect structural changes, not one outlier period.
Notable signals 2
Robbery
The past 12 months saw 41 incidents — about 55% below the 91 average from prior years.
Theft from Vehicle
The past 12 months saw 72 incidents — about 56% below the 163 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.
- Theft from Vehicle has reset to a lower baseline.
The trailing 12-month count is 72, down 54% from 155 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Motor Vehicle Theft has reset to a lower baseline.
The trailing 12-month count is 79, down 48% from 153 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Aggravated Assault is climbing.
The trailing 12-month count is 61, up 79% from 34 the year before. If the trend holds another quarter, it will pull the multi-year baseline up.
- Robbery has reset to a lower baseline.
The trailing 12-month count is 41, down 40% from 68 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 Deanwood compares
Peer neighborhoods picked by closest 12-month robbery 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 robbery levels.”
Recurring local terms (last 12 months)
Top terms in incident descriptions for Deanwood, 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.