Yearly Traffic Safety Analysis

393 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Iowa County recorded 393 total traffic crashes, a 12.6% increase from the 349 crashes documented in 2023. This period also saw a rise in total injuries from 94 to 100 and an increase in fatalities from 5 to 6. The most significant year-over-year change was the increase in single-vehicle, non-collision incidents, which rose from 163 in 2023 to 228 in 2024.

393

▲ 12.6%was 349

Total Crash Events

6

▲ 20.0%was 5

Persons Killed

100

▲ 6.4%was 94

Persons Injured

6

▲ 20.0%was 5

Fatal Crash Events

Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Iowa County indicates a rising trend in 2024 compared to the previous year. Total crashes increased by 12.6%, from 349 to 393 incidents. Similarly, the number of people injured rose by 6.4% to 100, and fatalities increased from 5 to 6.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

6

Motorists Killed

Prior: 5↑20.0%

1

Cyclists Injured

Prior: 2↓-50.0%

99

Motorists Injured

Prior: 92↑7.6%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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 2023 and 2024. The most common day for a crash moved from Thursday (72 crashes) in the prior year to Friday (80 crashes) in the current year. While the peak hour for crashes remained unchanged at 6 a.m. with 33 incidents in both periods, other hourly patterns varied; for instance, crashes during the 3 p.m. hour decreased from 28 to 14.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes remained broadly consistent year-over-year, though with a slight increase in fatal outcomes. The fatal crash rate rose from 1.43% in 2023 to 1.53% in 2024, corresponding to an increase from 5 to 6 fatal incidents. The total number of serious injury crashes held steady at 5 in both periods. The overall proportion of crashes involving any injury (serious, minor, or possible) was nearly unchanged, shifting from 20.6% in 2023 to 20.1% in 2024.

Outcome by Severity (Crash Events)

Fatal6fatal crashes1.5%
↑20.0%prior 5
Serious Injury5serious injury crashes1.3%
→0.0%prior 5
Minor Injury30minor injury crashes7.6%
↑20.0%prior 25
Possible Injury44possible injury crashes11.2%
↑4.8%prior 42
No Injury308no injury crashes78.4%
↑13.2%prior 272

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the leading contributing factor in both periods, with the count rising from 125 to 131 incidents. 'Driving too fast for conditions' became a more prominent factor, increasing by 38.7% from 31 to 43 incidents and moving from the third to the second-ranked cause. Conversely, crashes attributed to 'Lost Control' decreased from 29 to 25. Notably, incidents involving an inattentive or distracted driver increased from 2 in 2023 to 11 in 2024.

Officer-Reported Primary Contributing Cause

Animal131 (33.3%)↑4.8%prior 125
Driving too fast for conditions43 (10.9%)↑38.7%prior 31
Ran off road - straight33 (8.4%)→0.0%prior 33
Lost Control25 (6.4%)↓-13.8%prior 29
Followed too close22 (5.6%)↓-8.3%prior 24
Ran off road - left15 (3.8%)↓-28.6%prior 21
FTYROW: From stop sign13 (3.3%)↑44.4%prior 9
Driver Distraction: Inattentive/lost in thought11 (2.8%)
Other (explain in narrative): Other10 (2.5%)
FTYROW: From parked position8 (2%)↑60.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes across different environmental conditions showed some year-over-year changes. The proportion of crashes occurring on adverse road surfaces like ice, snow, or slush increased slightly from 20.6% to 22.9% of all incidents, with crashes on icy roads more than doubling from 17 to 35. While the share of crashes in daylight grew from 41.3% to 45.8%, the proportion of incidents in unlit, dark conditions decreased from 22.6% to 15.8%. The overall share of crashes during adverse weather remained stable at approximately 34%.

Weather

Clear145 (51.6%)
↑9.8%prior 132
Cloudy72 (25.6%)
↑14.3%prior 63
Snow24 (8.5%)
↓-17.2%prior 29
Blowing Snow16 (5.7%)
↑166.7%prior 6
Rain9 (3.2%)
↓-35.7%prior 14
Freezing rain/drizzle8 (2.8%)
Fog, smoke, smog6 (2.1%)
↓-14.3%prior 7
Severe Winds1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight180 (63.2%)
↑25.0%prior 144
Dark - roadway not lighted62 (21.8%)
↓-21.5%prior 79
Dark - roadway lighted17 (6.0%)
→0.0%prior 17
Dusk12 (4.2%)
↑71.4%prior 7
Dawn11 (3.9%)
↑57.1%prior 7
Dark - unknown roadway lighting3 (1.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry181 (64.4%)
↑8.4%prior 167
Ice/frost35 (12.5%)
↑105.9%prior 17
Snow28 (10.0%)
↑21.7%prior 23
Wet25 (8.9%)
→0.0%prior 25
Gravel10 (3.6%)
↓-23.1%prior 13
Slush2 (0.7%)
↓-71.4%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

An analysis of vehicles involved shows that Ford and Chevrolet remained the top two makes, with their counts increasing from 77 to 85 and 59 to 68, respectively. Freightliner trucks saw a notable rise in crash involvement, nearly doubling from 19 to 36 incidents and moving into the third-ranked position for 2024. The demographics of persons involved in crashes also shifted, with the 35-44 age group becoming the most represented (99 people), replacing the 26-34 age group from the prior year (101 people). Notably, the number of individuals aged 16-20 involved in crashes decreased from 88 to 56.

Top Vehicle Makes (549 vehicles)

1
FORD85 (15.5%)
↑10.4%prior 77
2
CHEV68 (12.4%)
↑15.3%prior 59
3
FREIGHTLINER36 (6.6%)
↑89.5%prior 19
4
DODG21 (3.8%)
↓-12.5%prior 24
5
CHEVROLET21 (3.8%)
↑23.5%prior 17
6
TOYO20 (3.6%)
↓-4.8%prior 21
7
GMC19 (3.5%)
↓-5.0%prior 20
8
HOND17 (3.1%)
↑6.3%prior 16
9
KIA17 (3.1%)
↑41.7%prior 12
10
NR15 (2.7%)
↑150.0%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (300 persons with recorded sex)

Male203 (67.7%)
↓-29.0%prior 286
Female97 (32.3%)
↓-37.0%prior 154

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 393
  • Total persons involved: 572
  • Total vehicles involved: 549

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: 2024." Published September 9, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2024-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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