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.
Two categories moved in Chinatown this August, both below trend. The shape of the month is narrow but consistent: burglary and motor vehicle theft each registered as below-trend signals, and the broader 12-month picture across most property and violent crime categories runs in the same direction.
Burglary is the stronger of the two signals, with 59 incidents over the trailing 12 months against 82 in the prior year, down 28.0%. Motor vehicle theft follows a similar pattern, 32 incidents in the current 12 months vs. 47 in the year before, down 31.9%. Robbery is also well below its prior-year level, 32 incidents against 48, a 33.3% reduction, though it did not cross the anomaly threshold this month. Other larceny is the one category moving in the opposite direction, up 8.1% year over year, and arson ticked up 60.0% on a small base, 8 incidents vs. 5. Everything else in the tracked set was within range.
Notable signals 2
Burglary
The past 12 months saw 59 incidents — about 46% below the 109 average from prior years.
Motor Vehicle Theft
The past 12 months saw 32 incidents — about 36% 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.
No sustained shifts surfaced this month.
What next month likely looks like
Forecasts trained through August 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
57 incidents over the past 12 months — 2 below Chinatown's 59.
Open page →Presidio Heights
63 incidents over the past 12 months — 4 above Chinatown's 59.
Open page →North Beach
53 incidents over the past 12 months — 6 below Chinatown's 59.
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.