Yearly Traffic Safety Analysis

571 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Marion County recorded 571 total crashes, a 5.7% increase from the 540 crashes documented in 2023. While total injuries decreased from 152 to 142, the number of fatalities doubled, rising from 2 in the prior year to 4 in the current period. This increase in fatalities represents the most significant year-over-year change in crash outcomes.

571

▲ 5.7%was 540

Total Crash Events

4

▲ 100.0%was 2

Persons Killed

142

▼ -6.6%was 152

Persons Injured

4

▲ 100.0%was 2

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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, the crash trend in Marion County shows a slight increase year-over-year. The total number of crashes rose by 31, from 540 in 2023 to 571 in 2024, marking a 5.7% increase in collision events.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 1↑300.0%

0

Other Killed

Prior: 1↓-100.0%

3

Pedestrians Injured

Prior: 2↑50.0%

1

Cyclists Injured

Prior: 4↓-75.0%

137

Motorists Injured

Prior: 145↓-5.5%

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 shifted between the two periods. The peak day for crashes moved from Wednesday (91 crashes) in 2023 to Friday (119 crashes) in 2024. Similarly, the peak hour for collisions shifted earlier in the day, from the 6 p.m. hour in the prior period (45 crashes) to the 3 p.m. hour in the current period (55 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 worsened year-over-year, with the number of fatal crashes doubling from 2 to 4, and total fatalities increasing from 2 to 4. Consequently, the fatal crash rate increased from 0.4% to 0.7% of all crashes. While the number of serious injury crashes decreased from 16 to 13, minor injury crashes saw a notable increase from 44 to 64.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.7%
↑100.0%prior 2
Serious Injury13serious injury crashes2.3%
↓-18.8%prior 16
Minor Injury64minor injury crashes11.2%
↑45.5%prior 44
Possible Injury52possible injury crashes9.1%
↓-13.3%prior 60
No Injury438no injury crashes76.7%
↑4.8%prior 418

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 top contributing factor in both periods, though the count decreased slightly from 175 to 171. 'Followed too close' also remained the second-ranked factor, with a small drop in incidents from 42 to 40. A notable shift occurred with 'Failure to Yield Right of Way from a stop sign,' which rose to the third-ranked factor with 37 crashes, a 23.3% increase in count from 30 in the prior year. Crashes attributed to 'Lost Control' also increased significantly, rising from 21 to 35 incidents.

Officer-Reported Primary Contributing Cause

Animal171 (29.9%)↓-2.3%prior 175
Followed too close40 (7%)↓-4.8%prior 42
FTYROW: From stop sign37 (6.5%)↑23.3%prior 30
Lost Control35 (6.1%)↑66.7%prior 21
Other (explain in narrative): Other30 (5.3%)↑66.7%prior 18
Driving too fast for conditions23 (4%)↑15.0%prior 20
Ran off road - left23 (4%)↑283.3%prior 6
Operating vehicle in an reckless, erratic, careless, negligent manner19 (3.3%)↓-40.6%prior 32
Ran off road - straight18 (3.2%)↓-14.3%prior 21
Ran Stop Sign17 (3%)↓-10.5%prior 19

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 environmental conditions remained largely consistent year-over-year. The proportion of crashes occurring in daylight increased from 50.0% to 53.9%, while crashes on dry road surfaces saw a smaller increase from 60.0% to 62.2% of the total. The share of crashes happening in adverse weather (such as rain, snow, or fog) was nearly unchanged, accounting for 6.7% of crashes in 2023 and 6.8% in 2024.

Weather

Clear357 (78.5%)
↑15.5%prior 309
Cloudy59 (13.0%)
↓-3.3%prior 61
Snow12 (2.6%)
↓-20.0%prior 15
Rain9 (2.0%)
↓-40.0%prior 15
Fog, smoke, smog7 (1.5%)
Blowing Snow6 (1.3%)
Freezing rain/drizzle3 (0.7%)
Severe Winds2 (0.4%)

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

Lighting

Daylight308 (66.4%)
↑14.1%prior 270
Dark - roadway not lighted91 (19.6%)
↑19.7%prior 76
Dark - roadway lighted30 (6.5%)
↓-25.0%prior 40
Dusk19 (4.1%)
↑5.6%prior 18
Dawn10 (2.2%)
↑66.7%prior 6
Dark - unknown roadway lighting6 (1.3%)

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

Road Surface

Dry355 (77.9%)
↑9.6%prior 324
Wet31 (6.8%)
↓-6.1%prior 33
Gravel26 (5.7%)
↓-13.3%prior 30
Snow25 (5.5%)
↑108.3%prior 12
Ice/frost14 (3.1%)
↑180.0%prior 5
Slush3 (0.7%)
Mud, dirt2 (0.4%)

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

Vehicles & Demographics

Ford and Chevrolet continued to be the top two vehicle makes involved in crashes in both periods, with counts for both increasing slightly year-over-year. The representation of persons in the 65+ age group involved in crashes increased notably, growing from 13.5% of all persons in 2023 to 17.8% in 2024. In contrast, the proportion of individuals in the 16-20 age group decreased from 14.0% to 12.4%.

Top Vehicle Makes (865 vehicles)

1
FORD167 (19.3%)
↑7.1%prior 156
2
CHEV139 (16.1%)
↑6.9%prior 130
3
TOYT41 (4.7%)
↑70.8%prior 24
4
JEEP40 (4.6%)
↑8.1%prior 37
5
DODG37 (4.3%)
↓-19.6%prior 46
6
GMC32 (3.7%)
↓-3.0%prior 33
7
CHEVROLET31 (3.6%)
↑3.3%prior 30
8
HOND28 (3.2%)
↑40.0%prior 20
9
BUIC27 (3.1%)
↑8.0%prior 25
10
NISS27 (3.1%)
→0.0%prior 27

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

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

Sex Distribution (535 persons with recorded sex)

Male307 (57.4%)
↓-30.7%prior 443
Female228 (42.6%)
↓-27.2%prior 313

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: 571
  • Total persons involved: 890
  • Total vehicles involved: 865

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

ThatCarHitMe.com · An Injuria.ai Company