Howard University Crime Rate Trends — Washington DC
The Howard University cluster covers the historically Black university campus and the Le Droit Park rowhouse district to its south, plus the Cardozo and Shaw fringes that connect it to U Street. Le Droit Park's late-19th-century blocks form one of the city's earliest planned suburbs, now folded into the urban grid.
Three categories moved in Howard University this April — all three sustained shifts downward, all three in the property and violent-crime buckets that drove the neighborhood's volume two years ago. There are no spikes, no rare events, no streak breaks this month. The story is structural decline across the board.
Motor vehicle theft is down 54.4% against the prior 12 months (73 incidents vs. 160), robbery is down 53.1% (69 vs. 147), and theft from vehicle is down 40.3% (243 vs. 407). All three registered as sustained shifts — meaning the gap has held across multiple months, not just this one. Everything else tracked this month was within normal range.
Notable signals 0
Nothing notable surfaced this month — every category sits within normal range against its baseline.
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 243, down 40% from 407 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 73, down 54% from 160 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 69, down 53% from 147 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 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
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 Howard University compares
Peer neighborhoods picked by closest 12-month motor vehicle theft 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 motor vehicle theft levels.”
Shaw
69 incidents over the past 12 months — 4 below Howard University's 73.
Open page →North Michigan Park
63 incidents over the past 12 months — 10 below Howard University's 73.
Open page →Woodridge
83 incidents over the past 12 months — 10 above Howard University's 73.
Open page →Do crime spikes here spill over to adjacent neighborhoods?
Howard Universitydoesn't have enough spike history in any single category for a stable spillover rate yet (we want at least 5 events). The table below lists what we have.
| Category | Spike events | Same-category spillover |
|---|---|---|
| Other larceny | 1 | — too few |
Each row shows Howard University's historical spike events for that category, and how often any of its 4 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 Washington DC); 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.
Recurring local terms (last 12 months)
Top terms in incident descriptions for Howard University, 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.