Yearly Traffic Safety Analysis

259 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Hardin County, total traffic crashes decreased from 285 in 2022 to 259 in 2023, a decline of approximately 9.1%. The most significant year-over-year change was the reduction in traffic fatalities, which fell from 4 in the prior period to zero in the current period. Total reported injuries also saw a decrease from 89 to 66.

259

▼ -9.1%was 285

Total Crash Events

0

▼ -100.0%was 4

Persons Killed

66

▼ -25.8%was 89

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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic safety trends in Hardin County improved from 2022 to 2023. The total number of crashes fell by 9.1%, from 285 to 259. This positive trend was also reflected in a 25.8% decrease in total injuries, which dropped from 89 to 66, and the elimination of fatalities, which fell from 4 to 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 4↓-100.0%

66

Motorists Injured

Prior: 88↓-25.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes in Hardin County shifted between 2022 and 2023. The peak day for collisions moved from Friday (50 crashes) in the prior year to Thursday (59 crashes) in the current year. A more significant change occurred in the peak hour, which shifted from the 6 p.m. hour (23 crashes) in 2022 to the 7 a.m. hour (22 crashes) in 2023, indicating a move from evening to morning commute times for the highest crash frequency.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity improved significantly, with fatal crashes dropping from 4 in 2022 to zero in 2023, bringing the fatal crash rate from 1.4% down to 0%. While the number of serious injury crashes increased from 7 to 12, their share of all crashes also rose from 2.5% to 4.6%. Conversely, the proportions of both minor injury crashes (from 7.7% to 5.0%) and possible injury crashes (from 15.8% to 13.1%) decreased year-over-year.

Outcome by Severity (Crash Events)

Serious Injury12serious injury crashes4.6%
↑71.4%prior 7
Minor Injury13minor injury crashes5%
↓-40.9%prior 22
Possible Injury34possible injury crashes13.1%
↓-24.4%prior 45
No Injury200no injury crashes77.2%
↓-3.4%prior 207

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving animals remained the top contributing factor in both periods, with a nearly identical count of 82 in 2022 and 83 in 2023. The factor 'Lost Control' saw its count decrease by 15.4% from 26 to 22 crashes, though it remained the second-leading cause. Crashes attributed to 'Driving too fast for conditions' experienced a notable 29.2% drop in count, falling from 24 incidents in 2022 to 17 in 2023.

Officer-Reported Primary Contributing Cause

Animal83 (32%)↑1.2%prior 82
Lost Control22 (8.5%)↓-15.4%prior 26
Other (explain in narrative): Other19 (7.3%)↓-17.4%prior 23
Driving too fast for conditions17 (6.6%)↓-29.2%prior 24
Followed too close12 (4.6%)↑33.3%prior 9
Ran off road - straight10 (3.9%)↓-16.7%prior 12
Ran off road - left9 (3.5%)↓-10.0%prior 10
FTYROW: From stop sign9 (3.5%)↓-18.2%prior 11
Driver Distraction: Exterior distraction8 (3.1%)↑33.3%prior 6
Operating vehicle in an reckless, erratic, careless, negligent manner6 (2.3%)↑20.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes under ideal conditions decreased year-over-year, consistent with the overall trend. Collisions in clear weather fell from 156 to 135, and those on dry road surfaces dropped from 161 to 151. Crashes occurring in daylight saw a notable reduction from 148 to 122. There was also a decrease in crashes on winter-related road surfaces (snow, ice, or slush), which collectively fell from 38 incidents in 2022 to 28 in 2023.

Weather

Clear135 (69.6%)
↓-13.5%prior 156
Cloudy33 (17.0%)
↑3.1%prior 32
Snow8 (4.1%)
↓-20.0%prior 10
Rain6 (3.1%)
↓-33.3%prior 9
Blowing Snow5 (2.6%)
↓-28.6%prior 7
Fog, smoke, smog3 (1.5%)
Freezing rain/drizzle2 (1.0%)
Other (explain in narrative)1 (0.5%)
Blowing sand, soil, dirt1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight122 (62.9%)
↓-17.6%prior 148
Dark - roadway not lighted53 (27.3%)
↑43.2%prior 37
Dark - roadway lighted10 (5.2%)
↓-44.4%prior 18
Dawn5 (2.6%)
↓-37.5%prior 8
Dusk4 (2.1%)
↓-20.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry151 (77.8%)
↓-6.2%prior 161
Ice/frost19 (9.8%)
↑35.7%prior 14
Wet13 (6.7%)
↓-23.5%prior 17
Snow6 (3.1%)
↓-70.0%prior 20
Slush3 (1.5%)
Mud, dirt1 (0.5%)
Gravel1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet were the two most common vehicle makes involved in crashes in both periods. The number of Fords involved increased from 70 to 81, while the combined count for Chevrolet vehicles ('CHEV' and 'CHEVROLET') decreased from 86 to 69. The demographic profile of persons involved in crashes also shifted; the 35-44 age group became the most represented in 2023 with 103 individuals, up from 75 in the prior year. This displaced the 26-34 age group, which was the largest in 2022 with 89 individuals.

Top Vehicle Makes (346 vehicles)

1
FORD81 (23.4%)
↑15.7%prior 70
2
CHEV56 (16.2%)
↓-9.7%prior 62
3
DODG18 (5.2%)
↓-21.7%prior 23
4
TOYT16 (4.6%)
↑23.1%prior 13
5
JEEP13 (3.8%)
↓-35.0%prior 20
6
CHEVROLET13 (3.8%)
↓-45.8%prior 24
7
BUIC12 (3.5%)
↑140.0%prior 5
8
NISS10 (2.9%)
↓-9.1%prior 11
9
GMC10 (2.9%)
↓-41.2%prior 17
10
TOYOTA9 (2.6%)
↑80.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (323 persons with recorded sex)

Male192 (59.4%)
↓-14.3%prior 224
Female131 (40.6%)
↓-10.3%prior 146

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 259
  • Total persons involved: 496
  • Total vehicles involved: 346

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-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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