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 categories moved in Chinatown this September, a light month with a clear directional lean. Two registered single-month below-trend signals, burglary and motor vehicle theft, while robbery's multi-month structural decline is now reflected as a sustained shift, a longer trend rather than a one-month dip. The overall shape is downward across property and violent crime alike.
Burglary is the strongest signal: 58 incidents in the trailing 12 months against 80 in the year before, down 27.5%. Motor vehicle theft also ran below trend, 30 incidents versus 40 in the prior period, a 25.0% year-over-year decline. Robbery tells the most durable story: 27 incidents in the current 12 months compared to 53 in the prior year, down 49.1%, a shift sustained long enough to register as structural. Every other tracked category, including aggravated assault, theft from vehicle, vandalism, and other larceny, came in within its expected range this month.
Notable signals 2
Burglary
The past 12 months saw 58 incidents — about 47% below the 109 average from prior years.
Motor Vehicle Theft
The past 12 months saw 30 incidents — about 40% below the 50 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.
- Robbery has reset to a lower baseline.
The trailing 12-month count is 27, down 49% from 53 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.
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.”
Inner Richmond
56 incidents over the past 12 months — 2 below Chinatown's 58.
Open page →Inner Sunset
62 incidents over the past 12 months — 4 above Chinatown's 58.
Open page →North Beach
54 incidents over the past 12 months — 4 below Chinatown's 58.
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.