Yearly Traffic Safety Analysis

3,146 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Linn County, total crashes decreased slightly from 3,178 in 2022 to 3,146 in 2023, a change of approximately 1.0%. Despite the minor drop in overall collisions, the number of fatalities recorded in these crashes saw a significant year-over-year increase, rising from 14 in 2022 to 27 in 2023.

3,146

▼ -1.0%was 3,178

Total Crash Events

27

▲ 92.9%was 14

Persons Killed

976

▲ 1.1%was 965

Persons Injured

22

▲ 57.1%was 14

Fatal Crash Events

Note: "Persons Killed" (27) counts individual fatalities across all crash events. "Fatal" in the severity table below (22) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in Linn County remained relatively stable, with a 1.0% decrease from 3,178 incidents in 2022 to 3,146 in 2023. However, the outcomes of these crashes worsened significantly. The total number of injuries increased by 1.1% from 965 to 976, while total fatalities rose from 14 to 27 year-over-year.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

24

Motorists Killed

Prior: 14↑71.4%

0

Other Killed

Prior: 0→0.0%

18

Pedestrians Injured

Prior: 25↓-28.0%

18

Cyclists Injured

Prior: 25↓-28.0%

935

Motorists Injured

Prior: 912↑2.5%

5

Other Injured

Prior: 3↑66.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Linn County showed minor shifts between 2022 and 2023. Friday remained the peak day for crashes in both years, with 554 incidents in 2023 compared to 568 in 2022. The peak hour for collisions shifted slightly earlier, from the 4 p.m. hour in 2022 (282 crashes) to the 3 p.m. hour in 2023 (282 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted year-over-year, with a notable increase in fatal outcomes. The number of fatal crashes rose from 14 in 2022 to 22 in 2023, increasing their share of all crashes from 0.4% to 0.7%. Conversely, crashes resulting in serious injuries decreased from 61 to 41. Crashes involving minor injuries increased from 263 to 308, while the proportion of crashes with no injuries remained stable at approximately 74% in both periods.

Severity is per crash event (most severe injury). 22 fatal crash events resulted in 27 persons killed.

Outcome by Severity (Crash Events)

Fatal22fatal crashes0.7%
↑57.1%prior 14
Serious Injury41serious injury crashes1.3%
↓-32.8%prior 61
Minor Injury308minor injury crashes9.8%
↑17.1%prior 263
Possible Injury436possible injury crashes13.9%
↓-8.6%prior 477
No Injury2,339no injury crashes74.3%
↓-1.0%prior 2,363

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes remained largely consistent, with 'Followed too close' being the most cited cause in both 2022 (402 crashes) and 2023 (380 crashes). Crashes involving an animal, the second-ranked factor, increased in count from 283 to 317. Notably, incidents where a driver 'Ran off road - left' decreased from 227 in 2022 to 179 in 2023. Meanwhile, crashes attributed to 'Ran Traffic Signal' increased from 157 to 181 year-over-year.

Officer-Reported Primary Contributing Cause

Followed too close380 (12.1%)↓-5.5%prior 402
Animal317 (10.1%)↑12.0%prior 283
Other (explain in narrative): Other227 (7.2%)↑9.7%prior 207
FTYROW: Making left turn224 (7.1%)↑5.7%prior 212
FTYROW: From stop sign220 (7%)↑10.0%prior 200
Ran Traffic Signal181 (5.8%)↑15.3%prior 157
Ran off road - left179 (5.7%)↓-21.1%prior 227
Driver Distraction: Other interior distraction114 (3.6%)↓-11.6%prior 129
Driving too fast for conditions101 (3.2%)↓-22.9%prior 131
Lost Control92 (2.9%)↓-8.0%prior 100

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather and on dry roads. In 2023, there was a decrease in crashes during adverse weather conditions, with incidents in rain falling from 160 to 110 and crashes in snow decreasing from 115 to 74. Correspondingly, crashes on wet road surfaces dropped from 372 to 263, and those on snow-covered roads fell from 151 to 70.

Weather

Clear2,020 (69.8%)
↑3.9%prior 1,944
Cloudy615 (21.3%)
↓-3.3%prior 636
Rain110 (3.8%)
↓-31.3%prior 160
Snow74 (2.6%)
↓-35.7%prior 115
Freezing rain/drizzle41 (1.4%)
↑2.5%prior 40
Fog, smoke, smog17 (0.6%)
Blowing Snow6 (0.2%)
↓-82.4%prior 34
Other (explain in narrative)4 (0.1%)
Sleet, hail3 (0.1%)
Severe Winds2 (0.1%)
↓-81.8%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight2,099 (72.3%)
↓-2.1%prior 2,144
Dark - roadway lighted447 (15.4%)
↓-10.4%prior 499
Dark - roadway not lighted192 (6.6%)
→0.0%prior 192
Dusk89 (3.1%)
↑23.6%prior 72
Dawn67 (2.3%)
↑76.3%prior 38
Dark - unknown roadway lighting9 (0.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry2,449 (84.4%)
↑7.2%prior 2,285
Wet263 (9.1%)
↓-29.3%prior 372
Snow70 (2.4%)
↓-53.6%prior 151
Ice/frost64 (2.2%)
↓-31.2%prior 93
Gravel24 (0.8%)
↑20.0%prior 20
Slush23 (0.8%)
↓-20.7%prior 29
Sand4 (0.1%)
Mud, dirt2 (0.1%)
Other (explain in narrative)1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The most common vehicle makes involved in crashes remained unchanged, with Ford (946 vehicles), Chevrolet (746), and Toyota (473) leading in 2023, reflecting a similar distribution to 2022. Analysis of persons involved shows a shift in age demographics; the number of individuals aged 16-20 involved in crashes decreased from 1,036 to 974. Conversely, involvement for the 35-44 age group increased from 1,098 to 1,154, and for the 55-64 age group from 775 to 839.

Top Vehicle Makes (5,703 vehicles)

1
FORD946 (16.6%)
↑1.1%prior 936
2
CHEV746 (13.1%)
↓-1.8%prior 760
3
TOYT473 (8.3%)
↓-8.0%prior 514
4
HOND288 (5%)
↓-5.3%prior 304
5
NISS223 (3.9%)
↑10.9%prior 201
6
JEEP204 (3.6%)
↓-15.7%prior 242
7
CHEVROLET204 (3.6%)
↓-3.3%prior 211
8
KIA204 (3.6%)
↑16.6%prior 175
9
DODG203 (3.6%)
↓-2.4%prior 208
10
GMC185 (3.2%)
↑0.5%prior 184

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (5,376 persons with recorded sex)

Male2,912 (54.2%)
↓-4.3%prior 3,044
Female2,464 (45.8%)
↑2.2%prior 2,410

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 3,146
  • Total persons involved: 7,218
  • Total vehicles involved: 5,703

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-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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