Yearly Traffic Safety Analysis

628 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Jasper County, total traffic crashes increased by 8.8%, rising from 577 in 2023 to 628 in 2024. While total crashes and injuries (180, up from 176) increased, the number of fatalities fell from 7 to 4. One of the most notable changes in contributing factors was a 100% increase in crashes attributed to 'Driver Distraction: Other interior distraction,' which rose from 15 to 30 incidents.

628

▲ 8.8%was 577

Total Crash Events

4

▼ -42.9%was 7

Persons Killed

180

▲ 2.3%was 176

Persons Injured

3

▼ -57.1%was 7

Fatal Crash Events

Note: "Persons Killed" (4) 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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Jasper County showed an overall increase year-over-year. Total crashes rose by 8.8%, from 577 in the prior period to 628 in the current period. While the number of injuries remained relatively stable with a slight increase from 176 to 180, total fatalities decreased from 7 to 4.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 1↓-100.0%

4

Motorists Killed

Prior: 6↓-33.3%

0

Other Killed

Prior: 0→0.0%

5

Pedestrians Injured

Prior: 1↑400.0%

1

Cyclists Injured

Prior: 1→0.0%

173

Motorists Injured

Prior: 172↑0.6%

1

Other Injured

Prior: 2↓-50.0%

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 timing of crashes shifted significantly between the two periods. The peak day for crashes moved from Friday (92 crashes) in the prior year to Tuesday (104 crashes) in the current year. Similarly, the peak hour for collisions changed from the afternoon at 3 p.m. (44 crashes) to the morning commute at 7 a.m. (56 crashes), which saw more than double the number of incidents compared to the same hour in the previous year.

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

While total crashes increased, the severity of those crashes generally decreased year-over-year. Fatal crashes dropped from 7 incidents (1.2% of total) to 3 incidents (0.5% of total), and serious injury crashes fell from 20 to 15. Conversely, crashes resulting in minor injuries increased from 58 to 73, and property-damage-only crashes rose from 427 to 470.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.5%
↓-57.1%prior 7
Serious Injury15serious injury crashes2.4%
↓-25.0%prior 20
Minor Injury73minor injury crashes11.6%
↑25.9%prior 58
Possible Injury67possible injury crashes10.7%
↑3.1%prior 65
No Injury470no injury crashes74.8%
↑10.1%prior 427

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

The leading cause of crashes in both periods was collisions with an animal, with counts remaining stable at 154 in the current period compared to 152 previously. A significant year-over-year change was observed in crashes related to 'Driver Distraction: Other interior distraction,' which doubled from 15 to 30 incidents. Crashes involving 'Driving too fast for conditions' also increased from 28 to 38, while those from 'Lost Control' decreased slightly from 45 to 42.

Officer-Reported Primary Contributing Cause

Animal154 (24.5%)↑1.3%prior 152
Ran off road - straight46 (7.3%)↑21.1%prior 38
Lost Control42 (6.7%)↓-6.7%prior 45
Driving too fast for conditions38 (6.1%)↑35.7%prior 28
Ran off road - left34 (5.4%)↑30.8%prior 26
Followed too close32 (5.1%)→0.0%prior 32
Driver Distraction: Other interior distraction30 (4.8%)↑100.0%prior 15
FTYROW: From stop sign23 (3.7%)↑4.5%prior 22
Other (explain in narrative): Other21 (3.3%)↓-12.5%prior 24
Ran Stop Sign20 (3.2%)↑11.1%prior 18

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 proportion of crashes occurring under adverse conditions increased from the prior year. Crashes in adverse weather—including rain, snow, and fog—constituted 21.3% of all incidents in the current period, up from 16.8% in the prior period. A similar trend was seen with road surface conditions, where crashes on non-dry surfaces like wet or icy roads accounted for 16.9% of the total, compared to 14.6% the previous year.

Weather

Clear357 (72.7%)
↑7.2%prior 333
Cloudy56 (11.4%)
↑21.7%prior 46
Snow28 (5.7%)
↑16.7%prior 24
Rain22 (4.5%)
↑10.0%prior 20
Freezing rain/drizzle13 (2.6%)
Blowing Snow9 (1.8%)
Fog, smoke, smog5 (1.0%)
↓-64.3%prior 14
Severe Winds1 (0.2%)

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

Lighting

Daylight321 (64.2%)
↑8.4%prior 296
Dark - roadway not lighted88 (17.6%)
↓-1.1%prior 89
Dark - roadway lighted39 (7.8%)
↑44.4%prior 27
Dusk25 (5.0%)
↑47.1%prior 17
Dawn15 (3.0%)
↑50.0%prior 10
Dark - unknown roadway lighting12 (2.4%)
↑50.0%prior 8

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

Road Surface

Dry373 (76.1%)
↑5.4%prior 354
Wet43 (8.8%)
↑22.9%prior 35
Ice/frost29 (5.9%)
↑11.5%prior 26
Snow29 (5.9%)
↑61.1%prior 18
Gravel10 (2.0%)
→0.0%prior 10
Slush5 (1.0%)
Other (explain in narrative)1 (0.2%)

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

Vehicles & Demographics

The vehicle makes most frequently involved in crashes shifted, with Chevrolet models (148 vehicles) overtaking Ford (137 vehicles) for the top rank in the current period, reversing the prior period's order. Regarding the demographics of people involved in crashes, the age distribution remained largely consistent, though the 26-34 age group's share increased slightly from 16.8% to 17.4% of persons with a known age. Conversely, the share of persons in the 16-20 and 65+ age groups saw a small decrease.

Top Vehicle Makes (940 vehicles)

1
CHEV148 (15.7%)
↑34.5%prior 110
2
FORD137 (14.6%)
↓-8.1%prior 149
3
CHEVROLET54 (5.7%)
↑22.7%prior 44
4
HOND36 (3.8%)
→0.0%prior 36
5
TOYT36 (3.8%)
↑2.9%prior 35
6
JEEP34 (3.6%)
↓-12.8%prior 39
7
BUIC32 (3.4%)
↑60.0%prior 20
8
DODG30 (3.2%)
↓-37.5%prior 48
9
NISS28 (3%)
↑21.7%prior 23
10
FREIGHTLINER26 (2.8%)
↑36.8%prior 19

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

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

Sex Distribution (551 persons with recorded sex)

Male350 (63.5%)
↓-27.4%prior 482
Female201 (36.5%)
↓-32.1%prior 296

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: 628
  • Total persons involved: 970
  • Total vehicles involved: 940

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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