Yearly Traffic Safety Analysis

478 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In Plymouth County, total crashes rose from 372 in 2017 to 478 in 2018, a 28.5% increase. Despite this rise in total incidents, the number of fatalities decreased from 4 to 3, and total injuries fell slightly from 180 to 174. The most notable year-over-year shift was a substantial increase in crashes occurring on icy road surfaces and those attributed to driving too fast for conditions.

478

▲ 28.5%was 372

Total Crash Events

3

▼ -25.0%was 4

Persons Killed

174

▼ -3.3%was 180

Persons Injured

3

▼ -25.0%was 4

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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

Plymouth County experienced an upward trend in the total number of traffic crashes, which increased by 106 incidents (28.5%) from 2017 to 2018. This increase in crash volume did not correspond to a rise in severity. Total reported injuries decreased from 180 to 174, and the number of fatalities fell from 4 to 3 year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 3→0.0%

4

Pedestrians Injured

Prior: 2↑100.0%

3

Cyclists Injured

Prior: 6↓-50.0%

167

Motorists Injured

Prior: 171↓-2.3%

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 temporal patterns of crashes shifted year-over-year. In 2018, the peak day for crashes was Wednesday with 85 incidents, a change from Friday (66 crashes) in 2017. The peak hour also shifted from the 7 a.m. morning commute hour in 2017 (28 crashes) to the 3 p.m. afternoon hour in 2018 (36 crashes).

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

While total crashes increased, the overall severity of those crashes trended downward. Fatal crashes decreased from 4 to 3, and their share of all crashes fell from 1.1% to 0.6%. Similarly, serious injury crashes dropped from 20 to 13, with their proportion decreasing from 5.4% to 2.7%. Consequently, the share of crashes resulting in no injury increased from 65.1% in 2017 to 72.4% in 2018.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.6%
↓-25.0%prior 4
Serious Injury13serious injury crashes2.7%
↓-35.0%prior 20
Minor Injury54minor injury crashes11.3%
↑3.8%prior 52
Possible Injury62possible injury crashes13%
↑14.8%prior 54
No Injury346no injury crashes72.4%
↑43.0%prior 242

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 leading contributing factor in both periods, with the count increasing from 87 in 2017 to 107 in 2018. The most significant change was in crashes due to "Driving too fast for conditions," which increased in count from 15 to 43, becoming the second-most common factor in 2018. The count of crashes involving failure to yield from a stop sign also grew from 21 to 30.

Officer-Reported Primary Contributing Cause

Animal107 (22.4%)↑23.0%prior 87
Driving too fast for conditions43 (9%)↑186.7%prior 15
Lost Control42 (8.8%)↑7.7%prior 39
FTYROW: From stop sign30 (6.3%)↑42.9%prior 21
Other (explain in narrative): Other27 (5.6%)↑35.0%prior 20
Ran off road - straight23 (4.8%)↑27.8%prior 18
Followed too close20 (4.2%)↑11.1%prior 18
FTYROW: At uncontrolled intersection18 (3.8%)↑50.0%prior 12
Ran off road - left15 (3.1%)↓-16.7%prior 18
Driver Distraction: Other interior distraction13 (2.7%)

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

Road & Environmental Conditions

A significant shift occurred in crashes under adverse conditions. Crashes on icy or frosty road surfaces increased from 11 in 2017 to 53 in 2018, and collisions on snowy surfaces rose from 24 to 38. This corresponds with an increase in crashes reported during freezing rain, which grew from 3 to 19 incidents. The proportion of crashes occurring in daylight and on dry surfaces remained relatively stable.

Weather

Clear238 (61.5%)
↑22.7%prior 194
Cloudy66 (17.1%)
↓-4.3%prior 69
Snow25 (6.5%)
↑78.6%prior 14
Rain19 (4.9%)
↑90.0%prior 10
Freezing rain/drizzle19 (4.9%)
Blowing Snow7 (1.8%)
Fog, smoke, smog6 (1.6%)
Severe Winds3 (0.8%)
Sleet, hail2 (0.5%)
Other (explain in narrative)2 (0.5%)

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

Lighting

Daylight248 (63.8%)
↑29.2%prior 192
Dark - roadway not lighted86 (22.1%)
↑34.4%prior 64
Dark - roadway lighted33 (8.5%)
↑32.0%prior 25
Dawn11 (2.8%)
↑37.5%prior 8
Dusk11 (2.8%)
↑83.3%prior 6

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

Road Surface

Dry241 (62.3%)
↑8.1%prior 223
Ice/frost53 (13.7%)
↑381.8%prior 11
Wet39 (10.1%)
↑95.0%prior 20
Snow38 (9.8%)
↑58.3%prior 24
Slush7 (1.8%)
Gravel6 (1.6%)
↓-50.0%prior 12
Other (explain in narrative)1 (0.3%)
Mud, dirt1 (0.3%)
Water (standing or moving)1 (0.3%)

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

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes, with their counts increasing in line with the overall rise in incidents. An analysis of persons involved in crashes reveals a substantial increase in the 16-20 age group, which grew from 94 individuals in 2017 to 160 in 2018. The 35-44 age group also saw a notable increase in involvement, from 89 to 131 persons.

Top Vehicle Makes (710 vehicles)

1
FORD133 (18.7%)
↑47.8%prior 90
2
CHEV109 (15.4%)
↑67.7%prior 65
3
CHEVROLET44 (6.2%)
↑2.3%prior 43
4
JEEP32 (4.5%)
↑113.3%prior 15
5
GMC32 (4.5%)
↑60.0%prior 20
6
PONT25 (3.5%)
↑127.3%prior 11
7
DODG25 (3.5%)
→0.0%prior 25
8
BUIC20 (2.8%)
↓-20.0%prior 25
9
KIA20 (2.8%)
↑100.0%prior 10
10
HOND17 (2.4%)
↑70.0%prior 10

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

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

Sex Distribution (540 persons with recorded sex)

Male321 (59.4%)
↑36.0%prior 236
Female219 (40.6%)
↑41.3%prior 155

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: 478
  • Total persons involved: 882
  • Total vehicles involved: 710

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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