Yearly Traffic Safety Analysis

285 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Hardin County, total vehicle crashes remained stable year-over-year, with 285 incidents in 2022 compared to 282 in 2021, an increase of approximately 1%. Despite the steady volume of crashes, the severity worsened significantly. The most notable year-over-year shift was the increase in total fatalities from one person in 2021 to four in 2022.

285

▲ 1.1%was 282

Total Crash Events

4

▲ 300.0%was 1

Persons Killed

89

▲ 20.3%was 74

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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in Hardin County showed minimal change, increasing by just three incidents from 282 in 2021 to 285 in 2022. However, the outcomes of these crashes became more severe. The number of people injured rose by 20.3%, from 74 to 89, and total fatalities quadrupled from one to four, indicating a negative trend in crash severity.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 1↑300.0%

1

Pedestrians Injured

Prior: 0→%

88

Motorists Injured

Prior: 73↑20.5%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between the two periods. While Friday remained the peak day for crashes in both 2021 (47 crashes) and 2022 (50 crashes), the peak hour moved earlier in the day. In 2022, the highest number of crashes occurred during the 6 p.m. hour (23 crashes), a shift from the 9 p.m. peak hour observed in 2021 (22 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased notably from 2021 to 2022. The number of fatal crashes rose from one to four, and the corresponding fatality rate per 100 crashes increased from 0.35 to 1.4. While serious injury crashes decreased slightly from 9 to 7, this was offset by a large increase in possible injury crashes, which grew from 28 in 2021 to 45 in 2022. Consequently, the total number of people injured in crashes increased from 74 to 89.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.4%
↑300.0%prior 1
Serious Injury7serious injury crashes2.5%
↓-22.2%prior 9
Minor Injury22minor injury crashes7.7%
↓-21.4%prior 28
Possible Injury45possible injury crashes15.8%
↑60.7%prior 28
No Injury207no injury crashes72.6%
↓-4.2%prior 216

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the leading contributing factor in both periods, though the count of these incidents decreased by 17.2% from 99 in 2021 to 82 in 2022. In contrast, crashes where 'Driving too fast for conditions' was a factor saw a significant increase, rising by 71.4% from 14 incidents in 2021 to 24 in 2022. 'Lost Control' remained the second-most cited factor in both years, with a slight decrease from 28 to 26 crashes.

Officer-Reported Primary Contributing Cause

Animal82 (28.8%)↓-17.2%prior 99
Lost Control26 (9.1%)↓-7.1%prior 28
Driving too fast for conditions24 (8.4%)↑71.4%prior 14
Other (explain in narrative): Other23 (8.1%)↑21.1%prior 19
Ran off road - straight12 (4.2%)↓-14.3%prior 14
FTYROW: From stop sign11 (3.9%)↑10.0%prior 10
Ran off road - left10 (3.5%)↑42.9%prior 7
Driver Distraction: Other interior distraction9 (3.2%)↓-18.2%prior 11
Followed too close9 (3.2%)↓-35.7%prior 14
Driver Distraction: Exterior distraction6 (2.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with the majority of incidents in both periods occurring in clear weather and on dry road surfaces. In 2022, 156 crashes occurred in clear weather and 161 on dry roads, compared to 140 and 137, respectively, in 2021. There was a small increase in crashes during snowy conditions, which rose from 7 incidents in 2021 to 10 in 2022.

Weather

Clear156 (71.2%)
↑11.4%prior 140
Cloudy32 (14.6%)
↑23.1%prior 26
Snow10 (4.6%)
↑42.9%prior 7
Rain9 (4.1%)
↑50.0%prior 6
Blowing Snow7 (3.2%)
Freezing rain/drizzle4 (1.8%)
↓-33.3%prior 6
Severe Winds1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight148 (67.6%)
↑23.3%prior 120
Dark - roadway not lighted37 (16.9%)
↓-9.8%prior 41
Dark - roadway lighted18 (8.2%)
↑12.5%prior 16
Dawn8 (3.7%)
↑60.0%prior 5
Dusk5 (2.3%)
→0.0%prior 5
Dark - unknown roadway lighting3 (1.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry161 (73.2%)
↑17.5%prior 137
Snow20 (9.1%)
↑81.8%prior 11
Wet17 (7.7%)
↓-10.5%prior 19
Ice/frost14 (6.4%)
↓-6.7%prior 15
Gravel4 (1.8%)
↓-42.9%prior 7
Slush4 (1.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes, including Ford and Chevrolet, remained consistent in rank and volume across both years. Analysis of persons involved reveals a significant demographic shift, with the number of individuals aged 65 and older increasing from 58 in 2021 to 87 in 2022, a rise of nearly 50%. The 16-20 age group also saw an increase in involvement, from 73 persons in 2021 to 83 in 2022.

Top Vehicle Makes (391 vehicles)

1
FORD70 (17.9%)
→0.0%prior 70
2
CHEV62 (15.9%)
↑3.3%prior 60
3
CHEVROLET24 (6.1%)
↑20.0%prior 20
4
DODG23 (5.9%)
↑21.1%prior 19
5
JEEP20 (5.1%)
6
GMC17 (4.3%)
↑41.7%prior 12
7
TOYT13 (3.3%)
↓-13.3%prior 15
8
NISS11 (2.8%)
9
HOND11 (2.8%)
↓-26.7%prior 15
10
CHRY9 (2.3%)
→0.0%prior 9

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (370 persons with recorded sex)

Male224 (60.5%)
↑21.1%prior 185
Female146 (39.5%)
↑29.2%prior 113

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 285
  • Total persons involved: 561
  • Total vehicles involved: 391

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: 2022." Published September 9, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2022-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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