Yearly Traffic Safety Analysis

2,006 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Black Hawk County, total traffic crashes increased by 2.5% from 1,958 in 2023 to 2,006 in 2024. Despite this slight rise in overall incidents, total injuries reported decreased by 7.4% from 715 to 662. The most significant year-over-year change was a 15.4% increase in fatalities, which rose from 13 to 15.

2,006

▲ 2.5%was 1,958

Total Crash Events

15

▲ 15.4%was 13

Persons Killed

662

▼ -7.4%was 715

Persons Injured

15

▲ 25.0%was 12

Fatal Crash Events

Note: "Persons Killed" (15) counts individual fatalities across all crash events. "Fatal" in the severity table below (15) 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 traffic crashes in Black Hawk County showed a slight upward trend, increasing by 2.5% from 1,958 in 2023 to 2,006 in 2024. In contrast, the number of people injured in these incidents decreased by 7.4% from 715 to 662. However, fatalities saw an increase from 13 to 15 year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 2↓-100.0%

0

Cyclists Killed

Prior: 1↓-100.0%

15

Motorists Killed

Prior: 10↑50.0%

0

Other Killed

Prior: 0→0.0%

15

Pedestrians Injured

Prior: 18↓-16.7%

22

Cyclists Injured

Prior: 11↑100.0%

624

Motorists Injured

Prior: 685↓-8.9%

1

Other Injured

Prior: 1→0.0%

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 temporal patterns of crashes remained largely consistent year-over-year. Friday was the peak day for crashes in both 2024 (331 crashes) and 2023 (337 crashes). The peak hour for incidents shifted later in the day, from the 3 p.m. hour in 2023 (166 crashes) to the 5 p.m. hour in 2024 (162 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

The severity of crashes increased in 2024 compared to the prior year. The number of fatal crashes rose from 12 to 15, and serious injury crashes increased from 38 to 43. Consequently, the share of fatal crashes grew from 0.6% to 0.7% of all incidents. In contrast, crashes resulting in minor injuries decreased in both count, from 192 to 162, and as a percentage of total crashes, from 9.8% to 8.1%.

Outcome by Severity (Crash Events)

Fatal15fatal crashes0.7%
↑25.0%prior 12
Serious Injury43serious injury crashes2.1%
↑13.2%prior 38
Minor Injury162minor injury crashes8.1%
↓-15.6%prior 192
Possible Injury336possible injury crashes16.7%
↑0.3%prior 335
No Injury1,450no injury crashes72.3%
↑5.0%prior 1,381

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 involving animals remained the leading contributing factor in both periods, with counts rising from 209 to 214. Crashes attributed to 'Failure to yield right of way making a left turn' increased significantly, from 85 incidents in 2023 to 109 in 2024. Conversely, crashes attributed to 'Failure to yield right of way from a stop sign' decreased from 144 to 126. 'Followed too close' became the third most common factor in 2024 with 139 incidents, up from 141 in the prior year but ranking higher.

Officer-Reported Primary Contributing Cause

Animal214 (10.7%)↑2.4%prior 209
Other (explain in narrative): Other177 (8.8%)↑2.9%prior 172
Followed too close139 (6.9%)↓-1.4%prior 141
FTYROW: From stop sign126 (6.3%)↓-12.5%prior 144
Ran Traffic Signal109 (5.4%)↓-1.8%prior 111
FTYROW: Making left turn109 (5.4%)↑28.2%prior 85
Ran off road - left106 (5.3%)↑10.4%prior 96
Driving too fast for conditions86 (4.3%)↑17.8%prior 73
Ran Stop Sign80 (4%)↓-12.1%prior 91
Driver Distraction: Other interior distraction78 (3.9%)↓-13.3%prior 90

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 majority of crashes in both 2024 and 2023 occurred in clear weather and on dry roads. However, there was a shift in crashes under adverse conditions, with incidents during rain increasing from 77 to 114 and collisions on wet road surfaces rising from 163 to 205. In contrast, crashes occurring during snowfall decreased from 85 to 54, while incidents on ice or frost-covered roads also fell from 68 to 58.

Weather

Clear1,337 (74.1%)
↓-1.3%prior 1,355
Cloudy242 (13.4%)
↑6.6%prior 227
Rain114 (6.3%)
↑48.1%prior 77
Snow54 (3.0%)
↓-36.5%prior 85
Blowing Snow18 (1.0%)
↑125.0%prior 8
Freezing rain/drizzle14 (0.8%)
↓-26.3%prior 19
Fog, smoke, smog10 (0.6%)
↓-9.1%prior 11
Other (explain in narrative)7 (0.4%)
Severe Winds6 (0.3%)
Sleet, hail3 (0.2%)

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

Lighting

Daylight1,269 (69.8%)
↑6.4%prior 1,193
Dark - roadway lighted301 (16.5%)
↓-11.2%prior 339
Dark - roadway not lighted147 (8.1%)
↓-7.0%prior 158
Dusk42 (2.3%)
→0.0%prior 42
Dawn40 (2.2%)
↑8.1%prior 37
Dark - unknown roadway lighting20 (1.1%)
↑25.0%prior 16

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

Road Surface

Dry1,424 (78.5%)
↓-1.3%prior 1,443
Wet205 (11.3%)
↑25.8%prior 163
Snow92 (5.1%)
↑9.5%prior 84
Ice/frost58 (3.2%)
↓-14.7%prior 68
Slush21 (1.2%)
↑75.0%prior 12
Gravel11 (0.6%)
↓-26.7%prior 15
Other (explain in narrative)2 (0.1%)
Mud, dirt1 (0.1%)

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, Ford and Chevrolet, remained consistent across both years. The number of Fords involved increased from 588 to 606, while Chevrolets saw a slight decrease from 675 to 652. Analysis of person-level data shows a shift in age demographics; the proportion of individuals aged 65 and older involved in crashes increased from 12.9% of the total in 2023 to 15.3% in 2024. Concurrently, the share of persons in the 16-20 and 21-25 age groups decreased.

Top Vehicle Makes (3,572 vehicles)

1
FORD606 (17%)
↑3.1%prior 588
2
CHEV440 (12.3%)
↓-14.2%prior 513
3
CHEVROLET212 (5.9%)
↑30.9%prior 162
4
TOYT180 (5%)
↓-19.6%prior 224
5
JEEP159 (4.5%)
↑30.3%prior 122
6
DODG127 (3.6%)
↑5.0%prior 121
7
HOND124 (3.5%)
↑3.3%prior 120
8
KIA120 (3.4%)
↑21.2%prior 99
9
GMC117 (3.3%)
↑4.5%prior 112
10
NISS115 (3.2%)
↓-1.7%prior 117

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

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

Sex Distribution (2,438 persons with recorded sex)

Male1,332 (54.6%)
↓-22.0%prior 1,707
Female1,106 (45.4%)
↓-23.3%prior 1,442

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: 2,006
  • Total persons involved: 3,722
  • Total vehicles involved: 3,572

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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