Yearly Traffic Safety Analysis

389 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In Hamilton County, total traffic crashes increased by 8.1% from 360 in 2017 to 389 in 2018. This period saw a significant rise in crash severity, with total fatalities increasing from one in 2017 to four in 2018. The most notable year-over-year shift was the substantial increase in crashes attributed to driving too fast for conditions, which rose by 77% from 35 to 62 incidents.

389

▲ 8.1%was 360

Total Crash Events

4

▲ 300.0%was 1

Persons Killed

120

▲ 21.2%was 99

Persons Injured

4

▲ 300.0%was 1

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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

Crash data for Hamilton County indicates a worsening trend in 2018 compared to the prior year. Total crashes rose by 8.1% from 360 to 389. More concerningly, the number of people injured increased by 21.2% (from 99 to 120), and fatalities quadrupled from one to four.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 1↑200.0%

1

Pedestrians Injured

Prior: 0→%

1

Cyclists Injured

Prior: 1→0.0%

118

Motorists Injured

Prior: 98↑20.4%

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 temporal patterns of crashes remained broadly similar year-over-year, with Friday being the peak day for crashes in both 2017 (66 crashes) and 2018 (71 crashes). However, the peak hour for collisions shifted earlier, moving from 5 p.m. in 2017 (25 crashes) to 3 p.m. in 2018 (28 crashes). The afternoon commute period consistently registered the highest crash volumes in both periods.

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 worsened significantly in 2018 compared to 2017. The number of fatal crashes increased from one to four, raising the fatal crash rate from 0.3% to 1.0% of all incidents. While the count of serious injury crashes decreased from 12 to 8, the number of crashes involving possible injuries grew from 40 to 57. Consequently, the proportion of crashes resulting in no injuries decreased from 76.9% in 2017 to 74.3% in 2018.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1%
↑300.0%prior 1
Serious Injury8serious injury crashes2.1%
↓-33.3%prior 12
Minor Injury31minor injury crashes8%
↑3.3%prior 30
Possible Injury57possible injury crashes14.7%
↑42.5%prior 40
No Injury289no injury crashes74.3%
↑4.3%prior 277

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

Collisions with animals remained the top contributing factor in both years, with a stable count of 81 in 2017 and 83 in 2018. The most significant change was in crashes attributed to 'driving too fast for conditions,' which surged by 77% from 35 incidents in 2017 to 62 in 2018, becoming the second-leading factor. Conversely, incidents of 'failure to yield from a stop sign' decreased from 18 to 12, and 'ran stop sign' crashes fell from 12 to 5.

Officer-Reported Primary Contributing Cause

Animal83 (21.3%)↑2.5%prior 81
Driving too fast for conditions62 (15.9%)↑77.1%prior 35
Ran off road - straight36 (9.3%)↑24.1%prior 29
Ran off road - left31 (8%)↑106.7%prior 15
Lost Control28 (7.2%)↓-15.2%prior 33
Other (explain in narrative): Other24 (6.2%)↑60.0%prior 15
Driver Distraction: Other interior distraction12 (3.1%)↑9.1%prior 11
FTYROW: From stop sign12 (3.1%)↓-33.3%prior 18
FTYROW: Making left turn9 (2.3%)↑80.0%prior 5
Other (explain in narrative): No improper action7 (1.8%)

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

Road & Environmental Conditions

There was a notable shift towards crashes occurring in adverse conditions in 2018. While crashes on dry roads decreased from 186 to 156, incidents on snowy, icy, or slushy surfaces increased substantially from 55 in 2017 to 118 in 2018. Similarly, crashes during clear weather decreased from 165 to 125, while those in snow or blowing snow more than doubled from 24 to 52 incidents, indicating weather was a more prominent factor in 2018's collisions.

Weather

Clear125 (39.2%)
↓-24.2%prior 165
Cloudy94 (29.5%)
↑51.6%prior 62
Snow32 (10.0%)
↑88.2%prior 17
Blowing Snow20 (6.3%)
↑185.7%prior 7
Rain16 (5.0%)
↓-20.0%prior 20
Freezing rain/drizzle15 (4.7%)
↑50.0%prior 10
Sleet, hail6 (1.9%)
Fog, smoke, smog6 (1.9%)
Severe Winds5 (1.6%)

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

Lighting

Daylight200 (62.5%)
↑9.3%prior 183
Dark - roadway not lighted63 (19.7%)
↑21.2%prior 52
Dark - roadway lighted30 (9.4%)
↓-3.2%prior 31
Dusk13 (4.1%)
↑18.2%prior 11
Dawn12 (3.8%)
↑33.3%prior 9
Dark - unknown roadway lighting2 (0.6%)

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

Road Surface

Dry156 (48.8%)
↓-16.1%prior 186
Ice/frost51 (15.9%)
↑54.5%prior 33
Snow48 (15.0%)
↑128.6%prior 21
Wet38 (11.9%)
↓-5.0%prior 40
Slush19 (5.9%)
Gravel4 (1.3%)
↓-50.0%prior 8
Mud, dirt3 (0.9%)
Other (explain in narrative)1 (0.3%)

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

Vehicles & Demographics

While the top vehicle makes involved in crashes remained consistent, their numbers shifted; Toyota involvement more than doubled from 24 to 50 vehicles, and Dodge involvement increased from 31 to 42. There was also a significant change in the age demographics of people involved in crashes, with notable increases in the 21-25 age group (from 64 to 102 persons) and the 35-44 age group (from 67 to 100 persons). Conversely, involvement of persons in the 55-64 and 65+ age groups decreased.

Top Vehicle Makes (533 vehicles)

1
FORD82 (15.4%)
↑5.1%prior 78
2
CHEV82 (15.4%)
↑49.1%prior 55
3
CHEVROLET38 (7.1%)
↓-43.3%prior 67
4
TOYT29 (5.4%)
↑123.1%prior 13
5
DODG24 (4.5%)
↑50.0%prior 16
6
JEEP18 (3.4%)
↑80.0%prior 10
7
DODGE18 (3.4%)
↑20.0%prior 15
8
TOYOTA16 (3%)
↑45.5%prior 11
9
FREIGHTLINER15 (2.8%)
↑25.0%prior 12
10
CHRY15 (2.8%)
↑25.0%prior 12

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

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

Sex Distribution (411 persons with recorded sex)

Male247 (60.1%)
↑5.1%prior 235
Female164 (39.9%)
↑10.1%prior 149

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: 389
  • Total persons involved: 678
  • Total vehicles involved: 533

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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