Monthly Traffic Safety Analysis

4,992 CRASHES IN
IOWA, IA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

In October 2023, there were 4,992 traffic crashes statewide, a slight decrease of 0.2% from the 5,003 crashes recorded in October 2022. While overall crash volume remained stable, the number of crashes resulting in serious injuries fell from 130 to 82, a 36.9% reduction. Fatalities also decreased from 33 to 28 year-over-year, and total injuries dropped from 1,583 to 1,466.

4,992

▼ -0.2%was 5,003

Total Crash Events

28

▼ -15.2%was 33

Persons Killed

1,466

▼ -7.4%was 1,583

Persons Injured

26

▼ -16.1%was 31

Fatal Crash Events

Note: "Persons Killed" (28) counts individual fatalities across all crash events. "Fatal" in the severity table below (26) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash volume remained stable, with a minor 0.2% decrease from 5,003 crashes in October 2022 to 4,992 in October 2023. However, the severity of these incidents lessened, as total fatalities dropped by 15.2% (from 33 to 28) and total injuries declined by 7.4% (from 1,583 to 1,466) over the same period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Cyclists Killed

Prior: 1→0.0%

27

Motorists Killed

Prior: 32↓-15.6%

0

Other Killed

Prior: 0→0.0%

35

Pedestrians Injured

Prior: 43↓-18.6%

31

Cyclists Injured

Prior: 41↓-24.4%

1,396

Motorists Injured

Prior: 1,497↓-6.7%

4

Other Injured

Prior: 2↑100.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between October 2022 and October 2023. The peak hour for crashes remained consistent at 3 p.m. in both periods, with 447 crashes in 2023 and 435 in 2022. However, the peak day for crashes shifted from Friday (823 crashes) in 2022 to Tuesday (842 crashes) in 2023. Notably, crash counts on Saturdays decreased by 26.6% (from 778 to 571), while Tuesdays saw a 25.1% increase in crashes (from 673 to 842).

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity decreased in October 2023 compared to the previous year. The number of fatal crashes fell from 31 to 26, and the fatal crash rate dropped from 0.62% to 0.52% of all incidents. Crashes involving serious injuries saw a substantial reduction, declining from 130 to 82, with their share of total crashes falling from 2.6% to 1.6%. Consequently, the proportion of crashes with no injuries increased from 72.0% in 2022 to 73.9% in 2023.

Severity is per crash event (most severe injury). 26 fatal crash events resulted in 28 persons killed.

Outcome by Severity (Crash Events)

Fatal26fatal crashes0.5%
↓-16.1%prior 31
Serious Injury82serious injury crashes1.6%
↓-36.9%prior 130
Minor Injury449minor injury crashes9%
↓-6.5%prior 480
Possible Injury745possible injury crashes14.9%
↓-1.7%prior 758
No Injury3,690no injury crashes73.9%
↑2.4%prior 3,604

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors for crashes remained consistent year-over-year, with the top five causes unchanged in their ranking. Collisions involving an animal were the leading factor in both October 2023 (964 crashes) and October 2022 (955 crashes), a 0.9% increase in count. The second-leading factor, 'Followed too close,' also saw a small increase in count from 523 to 535 incidents. 'Failure to yield from a stop sign' increased by 5.1% in count, from 257 to 270 crashes.

Officer-Reported Primary Contributing Cause

Animal964 (19.3%)↑0.9%prior 955
Followed too close535 (10.7%)↑2.3%prior 523
Other (explain in narrative): Other296 (5.9%)↓-5.1%prior 312
FTYROW: From stop sign270 (5.4%)↑5.1%prior 257
Ran off road - left243 (4.9%)↑4.3%prior 233
FTYROW: Making left turn219 (4.4%)↓-2.2%prior 224
Lost Control207 (4.1%)↓-9.2%prior 228
Driver Distraction: Other interior distraction172 (3.4%)↑23.7%prior 139
Ran Traffic Signal169 (3.4%)↑6.3%prior 159
Ran Stop Sign147 (2.9%)↓-2.0%prior 150

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Driving conditions were notably less favorable in October 2023 compared to October 2022. The proportion of crashes occurring in clear weather dropped from 71.7% to 58.3% of all crashes, while incidents in rainy conditions increased from 178 to 318. Similarly, crashes on wet road surfaces increased significantly, accounting for 12.5% of all incidents (623 crashes) compared to just 5.5% (275 crashes) in the prior year. The distribution of crashes by lighting condition remained proportionally similar between the two periods.

Weather

Clear2,910 (69.3%)
↓-18.8%prior 3,585
Cloudy899 (21.4%)
↑95.0%prior 461
Rain318 (7.6%)
↑78.7%prior 178
Snow30 (0.7%)
Freezing rain/drizzle15 (0.4%)
Fog, smoke, smog9 (0.2%)
Severe Winds7 (0.2%)
↓-12.5%prior 8
Other (explain in narrative)4 (0.1%)
↓-33.3%prior 6
Sleet, hail3 (0.1%)
Blowing Snow2 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight2,836 (67.1%)
↑0.7%prior 2,816
Dark - roadway lighted665 (15.7%)
↓-3.9%prior 692
Dark - roadway not lighted516 (12.2%)
↓-0.6%prior 519
Dawn99 (2.3%)
↓-13.2%prior 114
Dusk96 (2.3%)
↑1.1%prior 95
Dark - unknown roadway lighting17 (0.4%)
↑21.4%prior 14

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry3,439 (81.7%)
↓-11.1%prior 3,868
Wet623 (14.8%)
↑126.5%prior 275
Gravel91 (2.2%)
↓-17.3%prior 110
Ice/frost19 (0.5%)
Snow16 (0.4%)
Mud, dirt8 (0.2%)
Slush7 (0.2%)
Other (explain in narrative)3 (0.1%)
Water (standing or moving)1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (8,467 vehicles)

1
FORD1,302 (15.4%)
↓-0.5%prior 1,308
2
CHEV1,143 (13.5%)
↓-8.8%prior 1,253
3
TOYT431 (5.1%)
↑11.1%prior 388
4
CHEVROLET427 (5%)
↓-3.6%prior 443
5
JEEP376 (4.4%)
↑6.8%prior 352
6
HOND364 (4.3%)
↑6.4%prior 342
7
DODG335 (4%)
↑6.0%prior 316
8
GMC302 (3.6%)
↑2.4%prior 295
9
NISS293 (3.5%)
↑9.7%prior 267
10
KIA234 (2.8%)
↓-2.5%prior 240

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

1,268 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (7,713 persons with recorded sex)

Male4,397 (57.0%)
↑0.2%prior 4,390
Female3,316 (43.0%)
↑1.3%prior 3,273

Source: Iowa Crash Data · ArcGIS Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,992
  • Total persons involved: 11,352
  • Total vehicles involved: 8,467

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: October 2023." Published September 9, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/october-2023-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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