Yearly Traffic Safety Analysis

64 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In Wayne County, total traffic crashes increased by 16.4%, from 55 incidents in 2017 to 64 in 2018. While the number of crashes and injuries rose, the most significant year-over-year change was the complete elimination of traffic fatalities, which dropped from 4 in the prior year to 0 in the current year.

64

▲ 16.4%was 55

Total Crash Events

0

▼ -100.0%was 4

Persons Killed

29

▲ 26.1%was 23

Persons Injured

0

▼ -100.0%was 4

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 shows an increase in crash incidents and injuries year-over-year. Total crashes rose from 55 to 64, and the number of people injured increased from 23 to 29. In a positive development, however, traffic fatalities decreased from 4 in 2017 to 0 in 2018.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 4↓-100.0%

29

Motorists Injured

Prior: 23↑26.1%

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 Thursday with 18 incidents, a change from 2017 when Saturday was the peak day with 13 crashes. The peak hour also moved from 12 p.m. (5 crashes) in the prior year to 6 p.m. (7 crashes) in the current year.

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 saw a notable shift, with fatal crashes decreasing from 4 incidents in 2017 to 0 in 2018. Conversely, the number of serious injury crashes doubled from 3 to 6, and minor injury crashes increased from 5 to 8. Crashes resulting in no injury increased from 33 in 2017 to 42 in 2018, representing 65.6% of all incidents in the current period compared to 60% in the prior period.

Outcome by Severity (Crash Events)

Serious Injury6serious injury crashes9.4%
↑100.0%prior 3
Minor Injury8minor injury crashes12.5%
↑60.0%prior 5
Possible Injury8possible injury crashes12.5%
↓-20.0%prior 10
No Injury42no injury crashes65.6%
↑27.3%prior 33

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 involving animals remained the leading contributing factor in both years, with the count of such incidents increasing from 11 in 2017 to 20 in 2018. The second most common factor in 2018 was 'Lost Control,' which saw its count decrease from 9 to 6 incidents. 'Ran Stop Sign' incidents saw a notable increase, rising from 1 crash in 2017 to 5 crashes in 2018.

Officer-Reported Primary Contributing Cause

Animal20 (31.3%)↑81.8%prior 11
Lost Control6 (9.4%)↓-33.3%prior 9
Ran off road - straight5 (7.8%)
Ran Stop Sign5 (7.8%)
FTYROW: From stop sign3 (4.7%)
Other (explain in narrative): Other3 (4.7%)
Driving too fast for conditions3 (4.7%)
Followed too close3 (4.7%)
FTYROW: Making left turn2 (3.1%)
Ran off road - left2 (3.1%)

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

Road & Environmental Conditions

While most crashes in both years occurred in clear weather on dry roads, there was a notable increase in crashes under dark conditions. The number of incidents on unlighted dark roadways grew from 13 in 2017 to 19 in 2018. Crashes on wet road surfaces increased from 3 to 8 year-over-year, while crashes on gravel roads decreased from 12 to 8.

Weather

Clear41 (71.9%)
↑5.1%prior 39
Cloudy6 (10.5%)
↓-40.0%prior 10
Rain4 (7.0%)
Snow3 (5.3%)
Freezing rain/drizzle1 (1.8%)
Blowing Snow1 (1.8%)
Blowing sand, soil, dirt1 (1.8%)

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

Lighting

Daylight34 (59.6%)
↓-2.9%prior 35
Dark - roadway not lighted19 (33.3%)
↑46.2%prior 13
Dark - roadway lighted2 (3.5%)
Dusk2 (3.5%)

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

Road Surface

Dry37 (64.9%)
↑15.6%prior 32
Gravel8 (14.0%)
↓-33.3%prior 12
Wet8 (14.0%)
Ice/frost3 (5.3%)
Snow1 (1.8%)

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

Vehicles & Demographics

Ford remained the most common vehicle make involved in crashes in both periods, with its count increasing from 17 in 2017 to 19 in 2018. The age demographics of persons involved in crashes also shifted; the 16-20 age group's share of involvement decreased from 22.2% of all persons in 2017 to 10.3% in 2018. Concurrently, the representation of the 21-25 and 26-34 age groups increased.

Top Vehicle Makes (91 vehicles)

1
FORD19 (20.9%)
↑11.8%prior 17
2
DODG11 (12.1%)
↑83.3%prior 6
3
CHEVROLET10 (11%)
↓-23.1%prior 13
4
CHEV8 (8.8%)
↓-11.1%prior 9
5
BUIC6 (6.6%)
6
DODGE4 (4.4%)
7
GMC3 (3.3%)
8
HONDA3 (3.3%)
9
TOYT2 (2.2%)
10
INTERNATIONA2 (2.2%)

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

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

Sex Distribution (75 persons with recorded sex)

Male47 (62.7%)
↑20.5%prior 39
Female28 (37.3%)
↑55.6%prior 18

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: 64
  • Total persons involved: 116
  • Total vehicles involved: 91

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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