SPIKE · SEXUAL ASSAULTAUGUST 2026 BRIEFINGCHICAGO · 21.1K residents

Douglas Crime Rate Trends — Chicago

Douglas is a Near South Side community area named for Senator Stephen A. Douglas (whose tomb is here), organized around the Illinois Institute of Technology campus and the 35th Street corridor. Anchored by the Lake Meadows and Prairie Shores apartment complexes, the historic Stephen A. Douglas Tomb State Memorial, and the Green Line's 35th-Bronzeville-IIT station.

SEXUAL ASSAULT · 24-MO COUNT08 2026 · 2
04812-mo avg: 3.3
DOUGLASCITYWIDE TREND (RESCALED)+1% 12MO YOY
-33%MoM
+25%12mo YoY
40last 12mo
2this month
01 · TL;DR

Douglas registered two signals in August 2026, one in each direction. Burglary is up 48.6% against the prior 12 months and motor vehicle theft is up 24.0%, but neither crossed the anomaly threshold this month. The two signals that did: sexual assault spiked above its multi-year trend, and robbery ran below it.

Sexual assault reached 40 incidents over the current 12-month window, up 25.0% from 32 in the prior year. Robbery moved the other way, falling to 50 incidents from 66, a drop of 24.2% against the prior 12 months. Aggravated assault also declined year-over-year, down 15.2% to 112 incidents, but that move was within the normal range and did not register as a distinct signal. Everything else, including vandalism and other larceny, was broadly within trend.

1 spike1 drop
02 · Notable signals

Notable signals 2

SPIKE · SEXUAL ASSAULT

Sexual Assault

The past 12 months saw 40 incidents — about 75% above the 23 average from prior years.

DROP · ROBBERY

Robbery

The past 12 months saw 50 incidents — about 38% below the 80 average from prior years.

03 · By category

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.

Homicidebelow threshold
2024-092026-08
Robbery-24%
2024-092026-08
Aggravated Assault-15%
2024-092026-08
Sexual Assault+25%
2024-092026-08
Burglary+49%
2024-092026-08
Other Larceny+3%
2024-092026-08
Motor Vehicle Theft+24%
2024-092026-08
Vandalism+20%
2024-092026-08
Arsonbelow threshold
2024-092026-08
05 · Forecast

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

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Arson

NO FORECAST

Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.

Burglary

SEPTEMBER 2026
Most likely 6 next month — likely between 2 and 10.
+29% vs 12-month average (≈4.6)

Homicide

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Motor Vehicle Theft

SEPTEMBER 2026
Most likely 38 next month — likely between 12 and 63.
+22% vs 12-month average (≈31.4)

Other Larceny

SEPTEMBER 2026
Most likely 71 next month — likely between 48 and 95.
+18% vs 12-month average (≈60.3)

Robbery

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Sexual Assault

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Vandalism

SEPTEMBER 2026
Most likely 35 next month — likely between 19 and 50.
+5% vs 12-month average (≈33.1)
06 · Context & comps

How Douglas compares

Peer neighborhoods picked by closest 12-month sexual assault 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 sexual assault levels.”

SPATIAL SPILLOVER · NEW

Do crime spikes here spill over to adjacent neighborhoods?

Douglasdoesn'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.

Douglas historical spike-event spillover by crime category (3-month lookahead, adjacent neighborhoods via shared boundary).
CategorySpike eventsSame-category spillover
Sexual assault1— too few

Each row shows Douglas'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 Chicago); 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.

07 · Patterns

Recurring local terms (last 12 months)

Top terms in incident descriptions for Douglas, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

simpledomesticaggravatedhandguntelephoneharassmentunlawfulretailbuildingfeetfistshandsinjuryweaponlandpossessionfinancialidentitythreatforciblefraudelectronicmeansminordangerous
When does it happen?

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.

HOUR OF DAY · ALL CATEGORIES
044789312am6am12pm6pm11pm

Hour 0 is mildly inflated by reports without a known time defaulting to midnight — see methodology.

DAY OF WEEK · ALL CATEGORIES
01,0852,169MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
07391,478JanFebMarAprMayJunJulAugSepOctNovDec
08 · Methodology

How we built this page

Data → Anomalies → Forecast → Page

Incident data is pulled from CPD's open dataset on the City of Chicago Open Data portal — IUCR-coded and mapped to 9 UCR-aligned categories (theft from vehicle isn't reliably separable in the public feed and rolls into other larceny). Aggregated to community area × 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.