Chinatown Crime Rate Trends — San Francisco
San Francisco's Chinatown is the oldest Chinatown in North America, a dense residential and commercial enclave packed into roughly 24 city blocks around Grant and Stockton. Beyond its famous Dragon Gate and tourist storefronts, it remains a tightly-knit residential district of active markets, alleys, and family associations dating to the 19th century.
Three signals surfaced in Chinatown this June — one single-month below-trend reading and two sustained structural shifts, both pointing downward. The shape of the month is consolidation, not volatility: no spikes, no rare events, just a neighborhood where property crime has been grinding lower across multiple categories for an extended stretch.
Burglary is the clearest mover. The trailing 12-month total stands at 57 against 108 the prior year — down 47.2% — and the data registers both a one-month below-trend signal and a sustained multi-year shift in the same category. Theft from vehicle carries its own sustained-shift signal: 134 incidents over the current 12 months against 196 before, a 31.6% decrease. The remaining tracked categories were within range, with robbery and vandalism also down on a 12-month basis but not generating signals this period.
Notable signals 1
Burglary
The past 12 months saw 57 incidents — about 48% below the 110 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.
- Burglary has reset to a lower baseline.
The trailing 12-month count is 57, down 47% from 108 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 134, down 32% from 196 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 June 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.
Arson
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
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
Vandalism
How Chinatown 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.”
North Beach
56 incidents over the past 12 months — 1 below Chinatown's 57.
Open page →Presidio Heights
58 incidents over the past 12 months — 1 above Chinatown's 57.
Open page →Inner Richmond
59 incidents over the past 12 months — 2 above Chinatown's 57.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Chinatown, 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 SFPD's open dataset on DataSF, mapped to 10 NIBRS-aligned categories, and aggregated to 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.