Monthly Traffic Safety Analysis

5,538 CRASHES IN
IOWA, IA
NOVEMBER 2023

All metrics benchmarked againstNovember 2022

In November 2023, Iowa recorded 5,538 traffic crashes, a slight decrease from the 5,621 crashes reported in November 2022. Despite this overall reduction in collisions, the number of fatal crashes increased significantly, rising from 20 in the prior period to 29 in the current period, a 45% year-over-year increase. Total fatalities also rose from 26 to 30 people.

5,538

▼ -1.5%was 5,621

Total Crash Events

30

▲ 15.4%was 26

Persons Killed

1,486

▲ 5.9%was 1,403

Persons Injured

29

▲ 45.0%was 20

Fatal Crash Events

Note: "Persons Killed" (30) counts individual fatalities across all crash events. "Fatal" in the severity table below (29) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes in Iowa saw a minor decrease in November 2023 compared to the same month in 2022, falling by 1.5% from 5,621 to 5,538. However, the severity of these incidents worsened, with total injuries increasing by 5.9% (from 1,403 to 1,486) and fatalities rising by 15.4% (from 26 to 30).

Vulnerable Road User Casualties

7

Pedestrians Killed

Prior: 1↑600.0%

1

Cyclists Killed

Prior: 0→%

21

Motorists Killed

Prior: 25↓-16.0%

1

Other Killed

Prior: 0→%

37

Pedestrians Injured

Prior: 38↓-2.6%

18

Cyclists Injured

Prior: 17↑5.9%

1,429

Motorists Injured

Prior: 1,347↑6.1%

2

Other Injured

Prior: 1↑100.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · 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 shift between November 2022 and November 2023. While the peak hour for collisions remained the 5 PM evening commute in both periods (633 crashes in 2022, 654 in 2023), the peak day of the week changed from Tuesday (1,115 crashes) in 2022 to Wednesday (918 crashes) in 2023. The distribution of crashes across the week was more spread out in the current period compared to the prior period, which had a significant concentration of crashes on Tuesday and Wednesday.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased in November 2023 compared to the previous year. The fatal crash rate rose from 0.36% to 0.52% of all crashes, corresponding to an increase from 20 to 29 fatal incidents. The proportion of crashes resulting in serious injuries also grew from 1.4% (79 crashes) to 1.8% (98 crashes), while the share of crashes with no injuries saw a slight decrease from 77.3% to 77.0%.

Severity is per crash event (most severe injury). 29 fatal crash events resulted in 30 persons killed.

Outcome by Severity (Crash Events)

Fatal29fatal crashes0.5%
↑45.0%prior 20
Serious Injury98serious injury crashes1.8%
↑24.1%prior 79
Minor Injury440minor injury crashes7.9%
↑9.5%prior 402
Possible Injury707possible injury crashes12.8%
↓-8.8%prior 775
No Injury4,264no injury crashes77%
↓-1.9%prior 4,345

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record

Top Contributing Factors

Collisions involving animals remained the top contributing factor in both periods, with counts increasing from 1,587 to 1,622. "Followed too close" also held its rank as the second most common factor, with its count rising from 439 to 461. A notable shift occurred with "Driving too fast for conditions," which saw its count decrease from 369 in November 2022 to 221 in November 2023, causing it to fall from the 3rd to the 6th most cited factor. Conversely, "Failure to yield right-of-way from a stop sign" increased in count from 227 to 257, moving into the top five factors for the current period.

Officer-Reported Primary Contributing Cause

Animal1,622 (29.3%)↑2.2%prior 1,587
Followed too close461 (8.3%)↑5.0%prior 439
Other (explain in narrative): Other283 (5.1%)↑1.1%prior 280
Ran off road - left258 (4.7%)↓-17.3%prior 312
FTYROW: From stop sign257 (4.6%)↑13.2%prior 227
Driving too fast for conditions221 (4%)↓-40.1%prior 369
Lost Control216 (3.9%)↓-16.0%prior 257
FTYROW: Making left turn179 (3.2%)↑1.7%prior 176
Driver Distraction: Other interior distraction159 (2.9%)↑21.4%prior 131
Ran Traffic Signal153 (2.8%)↓-1.9%prior 156

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Environmental conditions appeared more favorable in November 2023 compared to the prior year. The proportion of crashes occurring on dry road surfaces increased from 54.0% (3,035 crashes) to 63.7% (3,526 crashes). Correspondingly, crashes on adverse surfaces like wet, snow, and ice/frost all decreased in count. Collisions during snowy weather dropped from 455 to 269 year-over-year. The distribution of crashes by lighting condition remained relatively stable, with a slight decrease in the proportion of daylight crashes from 44.1% to 41.5%.

Weather

Clear3,283 (78.1%)
↑23.7%prior 2,653
Cloudy502 (11.9%)
↓-34.6%prior 768
Snow269 (6.4%)
↓-40.9%prior 455
Rain91 (2.2%)
↓-69.4%prior 297
Freezing rain/drizzle34 (0.8%)
↓-63.4%prior 93
Blowing Snow10 (0.2%)
↓-82.5%prior 57
Other (explain in narrative)8 (0.2%)
↓-42.9%prior 14
Fog, smoke, smog2 (0.0%)
↓-75.0%prior 8
Severe Winds2 (0.0%)
↓-75.0%prior 8
Blowing sand, soil, dirt1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash

Lighting

Daylight2,298 (53.6%)
↓-7.3%prior 2,478
Dark - roadway lighted918 (21.4%)
↑5.4%prior 871
Dark - roadway not lighted720 (16.8%)
↑3.2%prior 698
Dusk172 (4.0%)
↑1.2%prior 170
Dawn112 (2.6%)
↓-13.8%prior 130
Dark - unknown roadway lighting64 (1.5%)
↑146.2%prior 26

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field

Road Surface

Dry3,526 (83.7%)
↑16.2%prior 3,035
Snow222 (5.3%)
↓-28.2%prior 309
Wet187 (4.4%)
↓-66.8%prior 563
Ice/frost181 (4.3%)
↓-48.9%prior 354
Gravel73 (1.7%)
↑2.8%prior 71
Slush19 (0.5%)
↓-40.6%prior 32
Other (explain in narrative)4 (0.1%)
↓-20.0%prior 5
Mud, dirt2 (0.0%)
↓-60.0%prior 5
Sand1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained largely consistent year-over-year, with Ford, Chevrolet, and Toyota representing the top three most common makes in both November 2022 and November 2023. The total number of vehicles involved in collisions saw a slight decrease from 8,868 to 8,794. The age distribution of persons involved in crashes also showed stability, with no significant shifts in representation among the different age groups between the two periods.

Top Vehicle Makes (8,794 vehicles)

1
FORD1,499 (17%)
↑2.4%prior 1,464
2
CHEV1,256 (14.3%)
↓-3.3%prior 1,299
3
CHEVROLET451 (5.1%)
↑7.1%prior 421
4
TOYT421 (4.8%)
↓-13.0%prior 484
5
JEEP401 (4.6%)
↑5.0%prior 382
6
HOND361 (4.1%)
↑7.4%prior 336
7
GMC340 (3.9%)
↓-5.0%prior 358
8
DODG309 (3.5%)
↓-19.9%prior 386
9
NISS298 (3.4%)
↑6.0%prior 281
10
KIA246 (2.8%)
↓-2.8%prior 253

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records

1,208 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (8,073 persons with recorded sex)

Male4,666 (57.8%)
→0.0%prior 4,666
Female3,407 (42.2%)
↓-2.2%prior 3,483

Source: Iowa Crash Data · ArcGIS Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-11-01 through 2023-11-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 5,538
  • Total persons involved: 12,204
  • Total vehicles involved: 8,794

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: November 2023." Published September 9, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/november-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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