Yearly Traffic Safety Analysis

293 CRASHES IN
IOWA, IA
2018

All metrics benchmarked against2017

In 2018, Hardin County recorded 293 total crashes, a 3.6% decrease from the 304 crashes reported in 2017. Despite the overall decline in collisions, the most significant year-over-year change was the increase in traffic fatalities, which rose from zero in 2017 to four in 2018. The total number of injuries saw a slight decrease from 87 to 79.

293

▼ -3.6%was 304

Total Crash Events

4

Persons Killed

79

▼ -9.2%was 87

Persons Injured

4

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

The overall trend in traffic crashes in Hardin County showed a slight decline from 2017 to 2018. Total crashes decreased by 3.6%, from 304 to 293 incidents. Similarly, the number of people injured fell by 9.2% from 87 to 79, though this period saw the emergence of fatal crashes, with four fatalities recorded in 2018 compared to none in the prior year.

Vulnerable Road User Casualties

4

Motorists Killed

Prior: 0→%

79

Motorists Injured

Prior: 83↓-4.8%

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

Temporal patterns of crashes showed some shifts between 2017 and 2018. While Friday remained the peak day for crashes in both years (54 in 2017, 48 in 2018), the peak hour for collisions shifted two hours later, from 5 p.m. in 2017 (29 crashes) to 7 p.m. in 2018 (26 crashes). The evening hours from 5 p.m. to 8 p.m. represented a high-frequency period for crashes in both years.

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 in 2018 with the introduction of fatal incidents. Four fatal crashes were recorded, accounting for 1.4% of all crashes, compared to zero in 2017. The number of serious injury crashes remained stable at five incidents in both years. Crashes resulting in minor or possible injuries decreased, with their combined share of total crashes falling from 21.4% in 2017 to 18.1% in 2018.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.4%
Serious Injury5serious injury crashes1.7%
→0.0%prior 5
Minor Injury25minor injury crashes8.5%
↓-16.7%prior 30
Possible Injury28possible injury crashes9.6%
↓-20.0%prior 35
No Injury231no injury crashes78.8%
↓-1.3%prior 234

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 an animal remained the leading contributing factor in both periods, though the count decreased slightly from 103 crashes in 2017 to 99 in 2018. 'Lost Control' remained the second-most cited factor, with its count increasing by 24% from 25 to 31 incidents. Notably, crashes attributed to 'Failure to Yield Right of Way from a stop sign' saw a significant decrease, falling from 14 incidents in 2017 to 6 in 2018.

Officer-Reported Primary Contributing Cause

Animal99 (33.8%)↓-3.9%prior 103
Lost Control31 (10.6%)↑24.0%prior 25
Other (explain in narrative): Other20 (6.8%)↑17.6%prior 17
Ran off road - left17 (5.8%)↓-10.5%prior 19
Ran off road - straight16 (5.5%)↓-20.0%prior 20
Driving too fast for conditions16 (5.5%)↑6.7%prior 15
Driver Distraction: Other interior distraction8 (2.7%)↑14.3%prior 7
FTYROW: From stop sign6 (2%)↓-57.1%prior 14
Operating vehicle in an reckless, erratic, careless, negligent manner6 (2%)→0.0%prior 6
Ran Stop Sign6 (2%)→0.0%prior 6

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

Road & Environmental Conditions

Crashes in both years predominantly occurred in clear weather and on dry road surfaces. In 2018, 138 crashes happened in 'Clear' weather and 137 on 'Dry' roads, compared to 149 for each condition in 2017. However, the proportion of crashes occurring on adverse road surfaces like snow, wet, or ice increased from 16.1% of all crashes in 2017 to 19.5% in 2018. The distribution of crashes by lighting conditions remained relatively stable, with 'Daylight' accounting for the largest share in both periods.

Weather

Clear138 (67.6%)
↓-7.4%prior 149
Cloudy31 (15.2%)
↓-11.4%prior 35
Snow14 (6.9%)
↑16.7%prior 12
Rain7 (3.4%)
↓-50.0%prior 14
Freezing rain/drizzle5 (2.5%)
Fog, smoke, smog4 (2.0%)
Blowing Snow3 (1.5%)
Sleet, hail1 (0.5%)
Severe Winds1 (0.5%)

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

Lighting

Daylight130 (64.0%)
↓-5.1%prior 137
Dark - roadway not lighted35 (17.2%)
↓-20.5%prior 44
Dark - roadway lighted16 (7.9%)
↓-5.9%prior 17
Dawn10 (4.9%)
↑66.7%prior 6
Dusk10 (4.9%)
↑25.0%prior 8
Dark - unknown roadway lighting2 (1.0%)
↓-60.0%prior 5

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

Road Surface

Dry137 (67.2%)
↓-8.1%prior 149
Snow21 (10.3%)
↑40.0%prior 15
Wet17 (8.3%)
↓-15.0%prior 20
Ice/frost14 (6.9%)
→0.0%prior 14
Gravel8 (3.9%)
↓-46.7%prior 15
Slush5 (2.5%)
Mud, dirt2 (1.0%)
↓-60.0%prior 5

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

Vehicles & Demographics

An analysis of vehicles involved in crashes shows a shift in the top makes. While Ford was the most common make in 2017 with 99 vehicles, it was surpassed by Chevrolet in 2018, which was involved in 106 crashes compared to Ford's 83. Examining the age of persons involved, the 16-20 age group saw an increase in representation from 67 individuals in 2017 to 75 in 2018. Conversely, the number of persons in the 26-34 age group decreased from 76 to 69 over the same period.

Top Vehicle Makes (387 vehicles)

1
FORD83 (21.4%)
↓-16.2%prior 99
2
CHEV78 (20.2%)
↑95.0%prior 40
3
CHEVROLET28 (7.2%)
↓-24.3%prior 37
4
DODG21 (5.4%)
↑61.5%prior 13
5
CHRY15 (3.9%)
↑15.4%prior 13
6
JEEP13 (3.4%)
↑116.7%prior 6
7
GMC12 (3.1%)
↓-20.0%prior 15
8
DODGE10 (2.6%)
↑25.0%prior 8
9
PONT10 (2.6%)
↓-23.1%prior 13
10
HOND8 (2.1%)
↑60.0%prior 5

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

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

Sex Distribution (280 persons with recorded sex)

Male171 (61.1%)
↓-3.9%prior 178
Female109 (38.9%)
↑9.0%prior 100

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: 293
  • Total persons involved: 488
  • Total vehicles involved: 387

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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