Monthly Traffic Safety Analysis

4,440 CRASHES IN
IOWA, IA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

In September 2024, there were 4,440 traffic crashes statewide, a marginal increase of 0.6% from the 4,414 crashes recorded in September 2023. While overall crash volume remained relatively stable, the number of fatalities saw a significant year-over-year increase. There were 39 fatalities in September 2024, compared to 28 in the same month of the prior year, a 39.3% rise.

4,440

▲ 0.6%was 4,414

Total Crash Events

39

▲ 39.3%was 28

Persons Killed

1,576

▼ -0.8%was 1,589

Persons Injured

35

▲ 34.6%was 26

Fatal Crash Events

Note: "Persons Killed" (39) counts individual fatalities across all crash events. "Fatal" in the severity table below (35) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends remained relatively stable year-over-year, with total crashes increasing by a marginal 0.6% from 4,414 in September 2023 to 4,440 in September 2024. However, outcomes worsened, as total fatalities rose by 39.3% from 28 to 39. Total injuries saw a slight decrease of 0.8% from 1,589 to 1,576.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 4↓-100.0%

1

Cyclists Killed

Prior: 0→%

38

Motorists Killed

Prior: 24↑58.3%

0

Other Killed

Prior: 0→0.0%

40

Pedestrians Injured

Prior: 19↑110.5%

42

Cyclists Injured

Prior: 40↑5.0%

1,485

Motorists Injured

Prior: 1,519↓-2.2%

9

Other Injured

Prior: 11↓-18.2%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed a notable shift in the peak day of the week between the two periods. In September 2024, Monday was the busiest day with 743 crashes, whereas in September 2023, Friday saw the highest volume with 893 crashes. The peak hour for crashes remained consistent at 3 p.m. for both years, although the number of crashes during this hour decreased from 407 in 2023 to 360 in 2024.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened in September 2024 compared to the previous year. The number of fatal crashes increased from 26 to 35, and their share of all crashes rose from 0.6% to 0.8%. Similarly, serious injury crashes increased in count from 116 to 126, with their proportion of total crashes edging up from 2.6% to 2.8%. The percentage of crashes resulting in no injuries remained unchanged at 68.7% across both periods.

Severity is per crash event (most severe injury). 35 fatal crash events resulted in 39 persons killed.

Outcome by Severity (Crash Events)

Fatal35fatal crashes0.8%
↑34.6%prior 26
Serious Injury126serious injury crashes2.8%
↑8.6%prior 116
Minor Injury520minor injury crashes11.7%
↑2.8%prior 506
Possible Injury709possible injury crashes16%
↓-3.3%prior 733
No Injury3,050no injury crashes68.7%
↑0.6%prior 3,033

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Top Contributing Factors

The ranking of top contributing factors shifted year-over-year, with 'Followed too close' becoming the leading factor in September 2024 with 525 incidents, a 9.4% increase in count from 480 in the prior year. 'Animal' related incidents, the top factor in 2023 with 521 crashes, decreased slightly in count to 508. Notably, 'Ran Stop Sign' incidents rose by 23.0% from 139 to 171, and crashes attributed to 'Failure to Yield Right of Way from a stop sign' increased by 14.3% from 224 to 256.

Officer-Reported Primary Contributing Cause

Followed too close525 (11.8%)↑9.4%prior 480
Animal508 (11.4%)↓-2.5%prior 521
FTYROW: From stop sign256 (5.8%)↑14.3%prior 224
Ran off road - left245 (5.5%)↑1.2%prior 242
Other (explain in narrative): Other230 (5.2%)↓-15.1%prior 271
FTYROW: Making left turn212 (4.8%)↑2.4%prior 207
Lost Control194 (4.4%)↓-8.1%prior 211
Driver Distraction: Other interior distraction175 (3.9%)↑12.9%prior 155
Ran Stop Sign171 (3.9%)↑23.0%prior 139
Ran Traffic Signal167 (3.8%)↓-8.7%prior 183

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in clear weather and on dry roads was higher in September 2024 compared to the previous year. Crashes in clear weather accounted for 82.1% of all incidents, up from 72.4% in September 2023. Correspondingly, crashes on wet roads dropped from 7.1% to 1.7% of the total, and rain-related crashes fell from 4.3% to just 1.0%. The distribution of crashes by lighting conditions remained largely unchanged year-over-year.

Weather

Clear3,644 (91.8%)
↑14.0%prior 3,196
Cloudy263 (6.6%)
↓-52.7%prior 556
Rain43 (1.1%)
↓-77.6%prior 192
Fog, smoke, smog9 (0.2%)
↓-75.7%prior 37
Other (explain in narrative)5 (0.1%)
↓-28.6%prior 7
Blowing sand, soil, dirt4 (0.1%)
Freezing rain/drizzle2 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight3,008 (75.2%)
↑0.4%prior 2,995
Dark - roadway lighted438 (11.0%)
↓-5.4%prior 463
Dark - roadway not lighted332 (8.3%)
↓-1.2%prior 336
Dusk107 (2.7%)
↓-0.9%prior 108
Dawn91 (2.3%)
↑18.2%prior 77
Dark - unknown roadway lighting23 (0.6%)
↑27.8%prior 18

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry3,805 (95.5%)
↑6.4%prior 3,575
Gravel94 (2.4%)
↓-6.0%prior 100
Wet77 (1.9%)
↓-75.3%prior 312
Mud, dirt4 (0.1%)
↓-33.3%prior 6
Other (explain in narrative)2 (0.1%)
↓-60.0%prior 5
Oil1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes, primarily Ford and Chevrolet, remained consistent year-over-year. The demographic distribution of crash-involved persons by age group also showed little change between the two periods. For instance, the 26-34 age group represented the largest single cohort in both September 2024 (15.4%) and September 2023 (15.0%), and the proportions for other age groups were also stable.

Top Vehicle Makes (7,781 vehicles)

1
FORD1,149 (14.8%)
↓-1.8%prior 1,170
2
CHEV1,090 (14%)
↑4.3%prior 1,045
3
CHEVROLET419 (5.4%)
↑3.5%prior 405
4
TOYT352 (4.5%)
↓-9.7%prior 390
5
JEEP350 (4.5%)
↑4.8%prior 334
6
HOND339 (4.4%)
↑9.4%prior 310
7
NISS290 (3.7%)
↑18.9%prior 244
8
GMC258 (3.3%)
↓-8.5%prior 282
9
DODG244 (3.1%)
↓-11.3%prior 275
10
KIA206 (2.6%)
↑4.0%prior 198

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

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

Sex Distribution (5,040 persons with recorded sex)

Male2,892 (57.4%)
↓-25.0%prior 3,854
Female2,148 (42.6%)
↓-30.5%prior 3,089

Source: Iowa Crash Data · ArcGIS Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,440
  • Total persons involved: 8,133
  • Total vehicles involved: 7,781

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: September 2024." Published September 9, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/september-2024-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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