Yearly Traffic Safety Analysis

283 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Mahaska County, total traffic crashes decreased by 4.7%, from 297 incidents in 2021 to 283 in 2022. While overall crashes and injuries declined, the number of crashes involving a driver under the influence of alcohol or drugs rose from 9 to 15, a 66.7% increase. The number of fatalities remained unchanged at two deaths in both periods.

283

▼ -4.7%was 297

Total Crash Events

2

Persons Killed

88

▼ -12.0%was 100

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Mahaska County showed a slight improvement year-over-year. Total crashes fell by 4.7% from 297 to 283, and the number of people injured in these incidents decreased by 12% from 100 to 88. However, the number of fatal crashes and resulting fatalities held steady at 2 for both 2021 and 2022.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 2→0.0%

2

Cyclists Injured

Prior: 2→0.0%

86

Motorists Injured

Prior: 95↓-9.5%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes remained broadly consistent between the two years. Friday was the peak day for crashes in both 2022 (58 crashes) and 2021 (51 crashes). Similarly, the 3 p.m. hour was the most frequent time for a crash in both periods, with 32 incidents in 2022 compared to 27 in 2021. December saw a notable increase in crashes, rising from 21 in 2021 to 32 in 2022.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the number of fatal crashes remained constant at two for both years, the severity distribution of non-fatal crashes shifted. The proportion of crashes resulting in serious injuries decreased from 3.7% (11 crashes) in 2021 to 3.2% (9 crashes) in 2022, and minor injury crashes fell from 9.8% (29 crashes) to 6.7% (19 crashes). Conversely, crashes involving possible injuries increased slightly from 13.8% to 15.2% of all incidents.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.7%
→0.0%prior 2
Serious Injury9serious injury crashes3.2%
↓-18.2%prior 11
Minor Injury19minor injury crashes6.7%
↓-34.5%prior 29
Possible Injury43possible injury crashes15.2%
↑4.9%prior 41
No Injury210no injury crashes74.2%
↓-1.9%prior 214

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes shifted between 2021 and 2022. In 2022, the top cause was 'Failure to Yield Right of Way from a stop sign' with 25 crashes, a slight increase from 23 in the prior year. The factor 'Lost Control' saw a significant decrease, dropping from 30 crashes in 2021 to 13 in 2022. Conversely, incidents where a driver 'Ran Traffic Signal' more than tripled, increasing from 3 crashes in 2021 to 11 in 2022.

Officer-Reported Primary Contributing Cause

FTYROW: From stop sign25 (8.8%)↑8.7%prior 23
Followed too close24 (8.5%)↑14.3%prior 21
Other (explain in narrative): Other22 (7.8%)↓-48.8%prior 43
FTYROW: Making left turn17 (6%)↓-19.0%prior 21
Animal15 (5.3%)↓-25.0%prior 20
Lost Control13 (4.6%)↓-56.7%prior 30
Driving too fast for conditions13 (4.6%)
Ran off road - straight13 (4.6%)↑44.4%prior 9
Ran off road - left12 (4.2%)↓-20.0%prior 15
Ran Stop Sign12 (4.2%)→0.0%prior 12

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained relatively stable year-over-year. In both periods, approximately 70-72% of crashes occurred in daylight and on dry roads. In 2022, 179 crashes (63.3% of total) occurred in clear weather, compared to 196 (66.0% of total) in 2021. Crashes on roads affected by snow, ice, or slush decreased from 36 incidents in 2021 to 31 in 2022.

Weather

Clear179 (67.3%)
↓-8.7%prior 196
Cloudy64 (24.1%)
↑16.4%prior 55
Snow11 (4.1%)
→0.0%prior 11
Blowing Snow5 (1.9%)
Rain4 (1.5%)
↓-50.0%prior 8
Other (explain in narrative)2 (0.8%)
Fog, smoke, smog1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight203 (76.9%)
↓-2.9%prior 209
Dark - roadway not lighted27 (10.2%)
↓-10.0%prior 30
Dark - roadway lighted26 (9.8%)
↓-13.3%prior 30
Dark - unknown roadway lighting3 (1.1%)
Dusk3 (1.1%)
↓-66.7%prior 9
Dawn2 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry209 (78.9%)
↓-2.8%prior 215
Snow21 (7.9%)
↑10.5%prior 19
Wet15 (5.7%)
↓-21.1%prior 19
Gravel9 (3.4%)
↑50.0%prior 6
Ice/frost8 (3.0%)
↓-46.7%prior 15
Slush2 (0.8%)
Other (explain in narrative)1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The demographics of vehicles and persons involved in crashes saw some shifts. Ford became the most common vehicle make in crashes, with its involvement increasing from 85 vehicles in 2021 to 110 in 2022, while Chevrolet's involvement remained flat at 110 vehicles in both years. Among persons involved in crashes, there was a notable increase in the 65+ age group, which grew from 64 individuals in 2021 to 93 in 2022.

Top Vehicle Makes (510 vehicles)

1
FORD110 (21.6%)
↑29.4%prior 85
2
CHEV88 (17.3%)
↑27.5%prior 69
3
DODG30 (5.9%)
↑57.9%prior 19
4
TOYT24 (4.7%)
↑33.3%prior 18
5
CHEVROLET22 (4.3%)
↓-46.3%prior 41
6
JEEP21 (4.1%)
↓-4.5%prior 22
7
NISS18 (3.5%)
↑20.0%prior 15
8
GMC18 (3.5%)
↓-5.3%prior 19
9
CHRY16 (3.1%)
↑14.3%prior 14
10
NR14 (2.7%)
↑100.0%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (456 persons with recorded sex)

Male267 (58.6%)
↓-3.6%prior 277
Female189 (41.4%)
↑8.0%prior 175

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 283
  • Total persons involved: 655
  • Total vehicles involved: 510

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: 2022." Published September 9, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2022-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

ThatCarHitMe.com · An Injuria.ai Company