Yearly Traffic Safety Analysis

265 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Mahaska County, total crashes decreased from 283 in 2022 to 265 in 2023, a decline of 6.4%. Despite the overall reduction in collisions, the number of fatalities doubled from 2 to 4, and total injuries increased by 15.9% from 88 to 102. This indicates that while crashes were less frequent, their severity increased year-over-year.

265

▼ -6.4%was 283

Total Crash Events

4

▲ 100.0%was 2

Persons Killed

102

▲ 15.9%was 88

Persons Injured

3

▲ 50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 traffic collisions in Mahaska County saw a downward trend, with 18 fewer crashes in 2023 (265) compared to 2022 (283), representing a 6.4% decrease. However, this trend did not extend to crash outcomes, as the number of people injured rose from 88 to 102, and fatalities increased from 2 to 4.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 2↑100.0%

3

Pedestrians Injured

Prior: 0→%

2

Cyclists Injured

Prior: 2→0.0%

97

Motorists Injured

Prior: 86↑12.8%

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 showed some consistency and some shifts between the two periods. Friday remained the peak day for crashes in both 2023 (46 crashes) and 2022 (58 crashes), though the volume on that day decreased. The peak hour for collisions shifted slightly from the 3 p.m. hour in 2022 (32 crashes) to the 4 p.m. hour in 2023 (24 crashes). The afternoon commute, from 3 p.m. to 5 p.m., continued to be the most frequent time for crashes in both years.

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

While total crashes declined, the severity of outcomes worsened in 2023 compared to 2022. The number of fatal crashes increased from 2 to 3, and the corresponding fatal crash rate rose from 0.71 to 1.13 per 100 crashes. The proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) also increased, from 25.1% of all crashes in 2022 to 28.3% in 2023. Consequently, the share of no-injury crashes fell from 74.2% to 70.6% year-over-year.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.1%
↑50.0%prior 2
Serious Injury8serious injury crashes3%
↓-11.1%prior 9
Minor Injury28minor injury crashes10.6%
↑47.4%prior 19
Possible Injury39possible injury crashes14.7%
↓-9.3%prior 43
No Injury187no injury crashes70.6%
↓-11.0%prior 210

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 shifted between 2022 and 2023. 'Followed too close' became the primary factor in 2023 with 28 crashes, an increase from 24 crashes in the prior year. 'Failure to yield from a stop sign,' the top factor in 2022 with 25 crashes, fell to the second position in 2023 with 23 crashes. Collisions involving animals saw a notable increase in count, rising from 15 incidents in 2022 to 20 in 2023, while 'Driver Distraction: Other interior distraction' also grew from 9 to 20 crashes.

Officer-Reported Primary Contributing Cause

Followed too close28 (10.6%)↑16.7%prior 24
FTYROW: From stop sign23 (8.7%)↓-8.0%prior 25
Animal20 (7.5%)↑33.3%prior 15
Driver Distraction: Other interior distraction20 (7.5%)↑122.2%prior 9
Other (explain in narrative): Other18 (6.8%)↓-18.2%prior 22
Ran Stop Sign18 (6.8%)↑50.0%prior 12
Driving too fast for conditions17 (6.4%)↑30.8%prior 13
Lost Control13 (4.9%)→0.0%prior 13
Ran off road - left12 (4.5%)→0.0%prior 12
Operating vehicle in an reckless, erratic, careless, negligent manner11 (4.2%)↑22.2%prior 9

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 years occurred in clear weather and on dry roads. In 2023, 75.1% of crashes happened on dry surfaces, a similar proportion to 73.9% in 2022, though crashes on snow-covered roads decreased in count from 21 to 10. Regarding lighting, the proportion of crashes occurring in daylight decreased from 71.7% in 2022 to 64.2% in 2023. Concurrently, the share of crashes in dark, unlighted conditions increased from 9.5% to 14.3% of the total.

Weather

Clear168 (68.6%)
↓-6.1%prior 179
Cloudy51 (20.8%)
↓-20.3%prior 64
Rain9 (3.7%)
Snow6 (2.4%)
↓-45.5%prior 11
Fog, smoke, smog5 (2.0%)
Freezing rain/drizzle2 (0.8%)
Blowing Snow2 (0.8%)
↓-60.0%prior 5
Other (explain in narrative)1 (0.4%)
Severe Winds1 (0.4%)

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

Lighting

Daylight170 (68.5%)
↓-16.3%prior 203
Dark - roadway not lighted38 (15.3%)
↑40.7%prior 27
Dark - roadway lighted26 (10.5%)
→0.0%prior 26
Dusk7 (2.8%)
Dawn6 (2.4%)
Dark - unknown roadway lighting1 (0.4%)

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

Road Surface

Dry199 (80.6%)
↓-4.8%prior 209
Wet20 (8.1%)
↑33.3%prior 15
Gravel12 (4.9%)
↑33.3%prior 9
Snow10 (4.0%)
↓-52.4%prior 21
Slush4 (1.6%)
Ice/frost2 (0.8%)
↓-75.0%prior 8

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

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford, Chevrolet, and Dodge being the most common in both years. In 2023, Chevrolet (87 vehicles) narrowly surpassed Ford (86 vehicles) for the most involvements, a reversal from 2022 when Ford led with 110 vehicles to Chevrolet's 88. The demographic profile of individuals involved in crashes showed little change; the 16-20 age group remained one of the most represented, with 100 individuals in 2023 compared to 98 in 2022. The number of males involved was nearly unchanged (263 vs. 267), while female involvement decreased from 189 to 163.

Top Vehicle Makes (457 vehicles)

1
CHEV87 (19%)
↓-1.1%prior 88
2
FORD86 (18.8%)
↓-21.8%prior 110
3
DODG25 (5.5%)
↓-16.7%prior 30
4
JEEP23 (5%)
↑9.5%prior 21
5
GMC22 (4.8%)
↑22.2%prior 18
6
CHEVROLET18 (3.9%)
↓-18.2%prior 22
7
HOND14 (3.1%)
↑55.6%prior 9
8
NISS12 (2.6%)
↓-33.3%prior 18
9
CHRY11 (2.4%)
↓-31.3%prior 16
10
RAM10 (2.2%)
↑25.0%prior 8

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

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

Sex Distribution (426 persons with recorded sex)

Male263 (61.7%)
↓-1.5%prior 267
Female163 (38.3%)
↓-13.8%prior 189

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: 265
  • Total persons involved: 602
  • Total vehicles involved: 457

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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