Yearly Traffic Safety Analysis

2,051 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In Dubuque County, a total of 2,051 vehicle crashes were recorded in 2018, an increase of 4.5% from the 1,962 crashes documented in 2017. While total incidents rose, the most notable year-over-year change was a 40% decrease in traffic fatalities, which fell from 10 in 2017 to 6 in 2018. Concurrently, the number of people injured in crashes increased by 10.7%, from 561 to 621.

2,051

▲ 4.5%was 1,962

Total Crash Events

6

▼ -40.0%was 10

Persons Killed

621

▲ 10.7%was 561

Persons Injured

6

▼ -40.0%was 10

Fatal Crash Events

Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in Dubuque County shows a rise in traffic incidents year-over-year. Total crashes increased by 4.5% from 1,962 to 2,051, and total injuries rose by 10.7% from 561 to 621. In contrast, fatalities saw a significant downward trend, decreasing by 40% from 10 in the prior year to 6 in the current year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 1→0.0%

0

Cyclists Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 9↓-44.4%

20

Pedestrians Injured

Prior: 19↑5.3%

10

Cyclists Injured

Prior: 11↓-9.1%

591

Motorists Injured

Prior: 531↑11.3%

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted between the two periods. In 2018, the peak day for crashes was Monday with 329 incidents, a change from 2017 when Friday was the peak day with 356 crashes. The peak hour also moved from 3 p.m. in 2017 (202 crashes) to 5 p.m. in 2018 (192 crashes), indicating a shift in the busiest time for collisions.

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity patterns showed a positive shift, with the fatal crash rate decreasing from 0.51% of all crashes in 2017 to 0.29% in 2018. The proportion of crashes involving serious injuries remained stable, moving from 0.9% to 0.8%. However, the share of crashes resulting in minor injuries increased from 7.2% to 8.0%, and possible injury crashes rose slightly from 14.5% to 14.9% of the total.

Outcome by Severity (Crash Events)

Fatal6fatal crashes0.3%
↓-40.0%prior 10
Serious Injury17serious injury crashes0.8%
↓-5.6%prior 18
Minor Injury165minor injury crashes8%
↑17.0%prior 141
Possible Injury305possible injury crashes14.9%
↑7.0%prior 285
No Injury1,558no injury crashes76%
↑3.3%prior 1,508

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors remained consistent year-over-year, though their counts changed. 'Ran off road - left' was the top factor in both periods, increasing in count by 17.1% from 427 incidents in 2017 to 500 in 2018. Collisions involving an 'Animal' also grew, rising 19.4% from 191 to 228 incidents. Conversely, incidents attributed to 'Lost Control' decreased by 12.4% (from 105 to 92), and 'Followed too close' incidents dropped by 13.4% (from 97 to 84).

Officer-Reported Primary Contributing Cause

Ran off road - left500 (24.4%)↑17.1%prior 427
Animal228 (11.1%)↑19.4%prior 191
Ran Stop Sign106 (5.2%)↓-5.4%prior 112
FTYROW: From stop sign104 (5.1%)↑9.5%prior 95
Ran Traffic Signal103 (5%)↑3.0%prior 100
Lost Control92 (4.5%)↓-12.4%prior 105
Followed too close84 (4.1%)↓-13.4%prior 97
FTYROW: Making left turn81 (3.9%)→0.0%prior 81
Made improper turn79 (3.9%)↑8.2%prior 73
Driving too fast for conditions71 (3.5%)↑36.5%prior 52

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes across different lighting and weather conditions was largely consistent between 2017 and 2018. However, there was a notable shift in road surface conditions. The proportion of crashes occurring on dry surfaces decreased from 72.3% in 2017 to 66.7% in 2018. Correspondingly, the share of crashes on roads with snow, ice, or slush increased from 7.3% to 9.6% of all incidents.

Weather

Clear1,036 (55.6%)
↑1.9%prior 1,017
Cloudy522 (28.0%)
↑1.6%prior 514
Rain138 (7.4%)
↑3.8%prior 133
Snow96 (5.2%)
↓-7.7%prior 104
Freezing rain/drizzle39 (2.1%)
↑69.6%prior 23
Fog, smoke, smog12 (0.6%)
↑20.0%prior 10
Sleet, hail11 (0.6%)
↑120.0%prior 5
Blowing Snow8 (0.4%)
Severe Winds1 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Weather condition at time of crash

Lighting

Daylight1,315 (70.5%)
↑3.0%prior 1,277
Dark - roadway lighted294 (15.8%)
↓-6.4%prior 314
Dark - roadway not lighted169 (9.1%)
↑14.2%prior 148
Dusk53 (2.8%)
↑17.8%prior 45
Dawn23 (1.2%)
↓-14.8%prior 27
Dark - unknown roadway lighting12 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Lighting condition field

Road Surface

Dry1,368 (73.4%)
↓-3.5%prior 1,418
Wet290 (15.6%)
↑18.9%prior 244
Snow95 (5.1%)
↑26.7%prior 75
Ice/frost62 (3.3%)
↑26.5%prior 49
Slush40 (2.1%)
↑110.5%prior 19
Gravel9 (0.5%)
↑50.0%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Road surface condition field

Vehicles & Demographics

The primary vehicle makes involved in collisions, led by Chevrolet and Ford, remained consistent between 2017 and 2018. An analysis of persons involved in crashes shows a slight shift in age demographics. The proportion of individuals in the 26-34 age group increased from 13.8% to 14.8% of all persons involved, and the 65+ age group's representation also grew from 11.5% to 12.5%.

Top Vehicle Makes (3,685 vehicles)

1
FORD544 (14.8%)
↑9.0%prior 499
2
CHEV510 (13.8%)
↑4.7%prior 487
3
CHEVROLET299 (8.1%)
↑4.5%prior 286
4
TOYT159 (4.3%)
↑12.8%prior 141
5
JEEP158 (4.3%)
↑2.6%prior 154
6
HOND140 (3.8%)
↑7.7%prior 130
7
DODG128 (3.5%)
↓-7.9%prior 139
8
GMC120 (3.3%)
↑27.7%prior 94
9
KIA113 (3.1%)
↑36.1%prior 83
10
DODGE102 (2.8%)
↓-5.6%prior 108

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records

526 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (2,913 persons with recorded sex)

Male1,587 (54.5%)
↑13.4%prior 1,400
Female1,326 (45.5%)
↑11.1%prior 1,194

Source: Iowa Crash Data · ArcGIS Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: ArcGIS Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2018-01-01 through 2018-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2018-01-01 through 2018-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 2,051
  • Total persons involved: 4,346
  • Total vehicles involved: 3,685

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "iowa, IA Crash Intelligence Report: 2018." Published September 9, 2026. Reporting period: 2018-01-01 to 2018-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2018-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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