Yearly Traffic Safety Analysis

788 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Des Moines County, total traffic crashes increased from 759 in 2023 to 788 in 2024, a rise of 3.8%. While overall crash volume saw a modest increase, the number of fatalities rose significantly, from one death in the prior period to three in the current period. Concurrently, total injuries increased slightly from 167 to 175.

788

▲ 3.8%was 759

Total Crash Events

3

▲ 200.0%was 1

Persons Killed

175

▲ 4.8%was 167

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

Traffic safety outcomes in Des Moines County showed a negative trend year-over-year. Total crashes increased by 3.8%, from 759 to 788. This was accompanied by a 4.8% increase in injuries (from 167 to 175) and a doubling of fatalities from one to three.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 1↑100.0%

0

Other Killed

Prior: 0→0.0%

4

Pedestrians Injured

Prior: 5↓-20.0%

5

Cyclists Injured

Prior: 3↑66.7%

165

Motorists Injured

Prior: 159↑3.8%

1

Other Injured

Prior: 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 daily pattern of crashes shifted between the two periods. The peak day for crashes moved from Friday (131 crashes) in the prior year to Monday (137 crashes) in the current year. However, the peak hour for collisions remained consistent, occurring at 5 p.m. in both periods, with 69 crashes in 2023 and 65 crashes in 2024 during that hour.

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 worsened year-over-year, with fatal crashes increasing from one to three. Consequently, the fatal crash rate rose from 0.13% to 0.38%. While fatal incidents increased, the number of serious injury crashes decreased from 16 to 10. The proportion of crashes resulting in no injuries remained stable, accounting for 78.1% of incidents in the prior year and 78.7% in the current year.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.4%
↑200.0%prior 1
Serious Injury10serious injury crashes1.3%
↓-37.5%prior 16
Minor Injury62minor injury crashes7.9%
→0.0%prior 62
Possible Injury93possible injury crashes11.8%
↑6.9%prior 87
No Injury620no injury crashes78.7%
↑4.6%prior 593

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 contributing factors remained consistent year-over-year, with 'Animal' being the top cause in both periods, increasing slightly from 152 to 159 crashes. 'Driver Distraction: Other interior distraction' was the second-most cited factor in both years, rising from 61 to 64 incidents. Crashes attributed to 'Followed too close' saw a notable increase in count, rising from 46 to 56, and moving from the fourth to the third-ranked cause.

Officer-Reported Primary Contributing Cause

Animal159 (20.2%)↑4.6%prior 152
Driver Distraction: Other interior distraction64 (8.1%)↑4.9%prior 61
Followed too close56 (7.1%)↑21.7%prior 46
Other (explain in narrative): Other53 (6.7%)↑1.9%prior 52
FTYROW: From stop sign44 (5.6%)↑10.0%prior 40
Ran off road - left35 (4.4%)↑6.1%prior 33
FTYROW: Making left turn31 (3.9%)↑29.2%prior 24
Lost Control30 (3.8%)↑42.9%prior 21
Operating vehicle in an reckless, erratic, careless, negligent manner27 (3.4%)↑50.0%prior 18
Driving too fast for conditions24 (3%)↑14.3%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

While most crashes in both periods occurred in clear weather and on dry roads, there was a notable increase in incidents during adverse winter conditions. Crashes occurring in snow increased from 19 to 35 year-over-year. Similarly, collisions on snow-covered road surfaces rose significantly, from 15 incidents in the prior period to 44 in the current period.

Weather

Clear482 (76.4%)
↓-0.4%prior 484
Cloudy64 (10.1%)
↓-9.9%prior 71
Snow35 (5.5%)
↑84.2%prior 19
Rain27 (4.3%)
↓-12.9%prior 31
Freezing rain/drizzle7 (1.1%)
↓-22.2%prior 9
Fog, smoke, smog7 (1.1%)
Blowing Snow4 (0.6%)
Severe Winds2 (0.3%)
Other (explain in narrative)2 (0.3%)
Sleet, hail1 (0.2%)

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

Lighting

Daylight425 (66.8%)
↓-5.6%prior 450
Dark - roadway lighted117 (18.4%)
↑9.3%prior 107
Dark - roadway not lighted59 (9.3%)
↑31.1%prior 45
Dusk16 (2.5%)
↓-5.9%prior 17
Dark - unknown roadway lighting13 (2.0%)
Dawn6 (0.9%)
→0.0%prior 6

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

Road Surface

Dry495 (78.2%)
↓-5.0%prior 521
Wet63 (10.0%)
↑14.5%prior 55
Snow44 (7.0%)
↑193.3%prior 15
Ice/frost17 (2.7%)
↑13.3%prior 15
Gravel8 (1.3%)
↓-38.5%prior 13
Slush5 (0.8%)
↓-16.7%prior 6
Water (standing or moving)1 (0.2%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained largely unchanged, with Ford (216 current vs. 212 prior) and Chevrolet (161 current vs. 173 prior) being the most common in both years. Analysis of persons involved shows a decrease in several age demographics, notably a drop in the 26-34 age group from 205 individuals to 141 and the 16-20 age group from 201 to 173.

Top Vehicle Makes (1,301 vehicles)

1
FORD216 (16.6%)
↑1.9%prior 212
2
CHEV161 (12.4%)
↓-6.9%prior 173
3
TOYO66 (5.1%)
↑57.1%prior 42
4
DODG66 (5.1%)
↓-7.0%prior 71
5
KIA65 (5%)
↑3.2%prior 63
6
JEEP61 (4.7%)
↑45.2%prior 42
7
GMC56 (4.3%)
↑40.0%prior 40
8
NISS52 (4%)
↑26.8%prior 41
9
CHEVROLET51 (3.9%)
↓-3.8%prior 53
10
NR49 (3.8%)
↓-14.0%prior 57

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

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

Sex Distribution (753 persons with recorded sex)

Male407 (54.1%)
↓-30.9%prior 589
Female346 (45.9%)
↓-25.1%prior 462

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: 788
  • Total persons involved: 1,336
  • Total vehicles involved: 1,301

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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