Yearly Traffic Safety Analysis

293 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Henry County recorded 293 total crashes, a 6.1% decrease from the 312 crashes reported in 2023. Despite the overall decline in collisions, the number of fatalities increased from one in the prior period to three in the current period, and the number of fatal crashes also rose from one to three.

293

▼ -6.1%was 312

Total Crash Events

3

▲ 200.0%was 1

Persons Killed

73

▲ 7.4%was 68

Persons Injured

3

▲ 200.0%was 1

Fatal Crash Events

Note: "Persons Killed" (3) 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

Overall, total crashes in Henry County decreased by 6.1% year-over-year, falling from 312 in 2023 to 293 in 2024. However, this period saw an increase in crash severity, with total injuries rising from 68 to 73 and total fatalities increasing from one to three.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 1↑200.0%

1

Pedestrians Injured

Prior: 2↓-50.0%

2

Cyclists Injured

Prior: 0→%

70

Motorists Injured

Prior: 66↑6.1%

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

Temporal crash patterns shifted between the two periods. The day with the highest crash volume moved from Wednesday (53 crashes) in 2023 to Friday (61 crashes) in 2024. The peak hour for crashes also shifted slightly later, from the 5 p.m. hour in the prior period (27 crashes) to the 6 p.m. hour in the current period (28 crashes).

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

Crash severity increased in 2024 compared to 2023. The number of fatal crashes rose from one to three, and the corresponding fatal crash rate increased from 0.32 to 1.02 per 100 crashes. While the share of serious injury crashes decreased from 3.5% to 3.1%, the proportion of crashes involving possible injuries grew from 7.7% to 11.9% of all incidents.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1%
↑200.0%prior 1
Serious Injury9serious injury crashes3.1%
↓-18.2%prior 11
Minor Injury21minor injury crashes7.2%
↓-12.5%prior 24
Possible Injury35possible injury crashes11.9%
↑45.8%prior 24
No Injury225no injury crashes76.8%
↓-10.7%prior 252

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 were the leading contributing factor in both periods, accounting for an identical 114 crashes in both 2024 and 2023. Crashes attributed to 'Lost Control' remained stable, with 22 incidents in 2024 compared to 23 in the prior year. Notably, crashes where the driver 'Ran off road - straight' decreased significantly from 21 to 7, while incidents of 'Failure to Yield Right of Way from a stop sign' increased from 12 to 15.

Officer-Reported Primary Contributing Cause

Animal114 (38.9%)→0.0%prior 114
Lost Control22 (7.5%)↓-4.3%prior 23
FTYROW: From stop sign15 (5.1%)↑25.0%prior 12
Operating vehicle in an reckless, erratic, careless, negligent manner10 (3.4%)↓-16.7%prior 12
Ran Stop Sign10 (3.4%)↑11.1%prior 9
Ran off road - left8 (2.7%)↓-11.1%prior 9
Driving too fast for conditions8 (2.7%)↓-20.0%prior 10
Other (explain in narrative): Other8 (2.7%)↓-20.0%prior 10
FTYROW: Making left turn7 (2.4%)
Ran off road - straight7 (2.4%)↓-66.7%prior 21

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

Road & Environmental Conditions

Crash conditions remained broadly consistent year-over-year, with the majority of incidents in both periods occurring in clear weather and during daylight hours. Most crashes also happened on dry road surfaces, which accounted for 133 incidents in 2024 versus 162 in 2023. However, there was a notable increase in the count of crashes on gravel surfaces, rising from 10 to 17, and a smaller increase in crashes on wet roads, from 15 to 20.

Weather

Clear136 (71.2%)
↓-11.7%prior 154
Cloudy25 (13.1%)
↑13.6%prior 22
Rain11 (5.8%)
↑22.2%prior 9
Snow10 (5.2%)
↓-9.1%prior 11
Fog, smoke, smog7 (3.7%)
Freezing rain/drizzle1 (0.5%)
Blowing Snow1 (0.5%)

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

Lighting

Daylight126 (63.0%)
↓-3.8%prior 131
Dark - roadway not lighted38 (19.0%)
↓-19.1%prior 47
Dark - roadway lighted13 (6.5%)
↓-18.8%prior 16
Dawn10 (5.0%)
↑66.7%prior 6
Dark - unknown roadway lighting9 (4.5%)
Dusk4 (2.0%)
↓-33.3%prior 6

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

Road Surface

Dry133 (70.0%)
↓-17.9%prior 162
Wet20 (10.5%)
↑33.3%prior 15
Gravel17 (8.9%)
↑70.0%prior 10
Snow13 (6.8%)
↑44.4%prior 9
Ice/frost6 (3.2%)
↑20.0%prior 5
Mud, dirt1 (0.5%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes were consistent, with Chevrolet (63 incidents vs. 60 prior) and Ford (57 vs. 53) leading in both periods. The total number of persons involved in crashes decreased from 619 to 423. This decline was observed across most age groups, particularly the 35-44 age bracket, which saw its involvement decrease from 107 persons to 60.

Top Vehicle Makes (409 vehicles)

1
CHEV63 (15.4%)
↑5.0%prior 60
2
FORD57 (13.9%)
↑7.5%prior 53
3
GMC24 (5.9%)
↑26.3%prior 19
4
DODG19 (4.6%)
↓-9.5%prior 21
5
JEEP18 (4.4%)
↓-28.0%prior 25
6
TOYT17 (4.2%)
↓-37.0%prior 27
7
CHEVROLET16 (3.9%)
↑6.7%prior 15
8
HOND15 (3.7%)
↑7.1%prior 14
9
NISS13 (3.2%)
↓-18.8%prior 16
10
KIA12 (2.9%)
↓-7.7%prior 13

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

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

Sex Distribution (204 persons with recorded sex)

Male127 (62.3%)
↓-46.9%prior 239
Female77 (37.7%)
↓-53.6%prior 166

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: 293
  • Total persons involved: 423
  • Total vehicles involved: 409

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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